Motion, screen size, and emotion

This week some very interesting papers on how movement and screen size impacts on our experience and understanding of motion pictures. Particularly interesting is the paper that indicates small screens can be more immersive than big screens

Bellman S, Schweda A, and Varan D 2009 Viewing angle matters – screen type does not, Journal of Communication 59 (3): 609-634.

Increasingly, television content is available to viewers across 3 different screen types: TVs, personal computers (PCs), and portable devices such as mobile phones and iPods. The purpose of this study was to see what effect physical and apparent screen size has upon ad effectiveness. Using a sample of 320 members of the Australian public, we found that TV ads can be just as effective on PCs and iPods. However, controlling for screen type, ads viewed from a closer distance (i.e. with a wider viewing angle) were more likely to be recalled the next day, and were associated with more favorable brand attitudes. Shorter programs, product relevance, and use of close-ups and detailed images made no difference to this general viewing-angle effect.

Bracken C and Pettey G 2007 It is REALLY a smaller (and smaller) world: presence and small Screens,  PRESENCE 2007: 10th International Workshop on Presence, Barcelona, Spain, 25-27 October 2007.

This study moved Presence into the realm of the smaller video format—comparing Apple iPod with a standard television presentation. Ninety-six students were exposed to one of two presentations on either an iPod or on a 32-inch television. Students saw either a 10-minute fast-paced (multiple cut) action sequence or a 10-minute slow-paced (long cut) conversation sequence from a feature length motion picture. The 2 x 2 design looked at differences in immersion, spatial presence and social realism. While previous research suggests that larger format presentations should generally result in higher levels of presence, this study found that subjects viewing the iPod reported higher levels of immersion. Social realism had a significant interaction with content/pace, and there was no significant difference between iPod and the 32-inch television in spatial presence.

Detenber BH and Reeves B 1996 A bio‐informational theory of emotion: motion and image size effects on viewers, Journal of Communication 46 (3): 66-84.

Detenber BH, Simons RF, and Bennet Jr GG 1998 Roll ‘em!: the effects of picture motion on emotional responses, Journal of Broadcasting and Electronic Media 42 (1): 113-127.

An experiment investigated the effects of picture motion on individuals’ emotional reactions to images. Subjective measures (self-reports) and physiological data (skin conductance and heart rate) were obtained to provide convergent data on affective responses. Results indicate that picture motion significantly increased arousal, particularly when the image was already arousing. This finding was supported by the both skin conductance and the self-report data. Picture motion also tended to prompt more heart-rate deceleration, most likely reflecting a greater allocation of attention to the more arousing images. In this study, the influence of picture motion on affective valence was evident only in the self-report measures – positive images were experienced as more positive and negative images as more negative when the image contained motion. Implications of the results and suggestions for future research are discussed.

Ravaja N 2004 Effects of image motion on a small screen on emotion, attention, and memory: moving-face versus static-face newscaster, Journal of Broadcasting and Electronic Media 48 (1): 108-133.

We examined the modulating influence of a small moving vs. static facial image on emotion- and attention-related subjective and physiological responses to financial news read by a newscaster, and on memory performance among 36 young adults. A moving-face newscaster was associated with high self-reported pleasure and arousal, but not with physiological arousal (electrodermal activity). Facial electromyographic responses to facial image motion were at variance with pleasure ratings. Facial motion was associated with decreased respiratory sinus arrhythmia, an index of attention, and improved memory performance for positive messages. A talking facial image on a small screen increases attention and knowledge acquisition.

Reeves B, Lang A, Kim EY and Tatar D 1999 The effects of screen size and message content on attention and arousal, Media Psychology 1 (1): 49-67.

The number of different screens that people confront is increasing. One potentially important difference in the psychological impact of screen displays is their size; new screens are both larger and smaller than older ones. A between-subjects experiment (n = 38) assessed viewer’s attention and arousal in response to three different size screens (56-inch, 13-inch, and 2-inch picture heights). Viewers responded to video images from television and film that displayed different emotions (# video segments = 60). Attention was measured by heart rate deceleration in response to the onset of pictures, and arousal was measured by skin conductance aggregated during viewing. Results showed that the largest screen produced greater heart rate deceleration than the medium and small screens. The large screen also produced greater skin conductance than the medium and small screens. For skin conductance, screen size also interacted with the emotional content of the stimuli such that the most arousing pictures (e.g., pictures of violence and sex) showed the highest levels of arousal on the large screen compared to the medium and small screens.

Simons RF, Detenber BH, Roedema TM and Reiss JE 1999 Emotion processing in three systems: the medium and the message, Psychophysiology 36: 619-627.

In the context of picture viewing, consistent and specific relationships have been found between two emotion dimensions ~valence and arousal! and self-report, physiological and overt behavioral responses. Relationships between stimulus content and the emotion-response profile can also be modulated by the formal properties of stimulus presentation such as screen size. The present experiment explored the impact of another presentation attribute, stimulus motion, on the perceived quality of the induced emotion and on its associated physiological response pattern. Using a within-subject design, moving and still versions of emotion-eliciting stimuli were shown to 35 subjects while facial muscle, heart rate, skin conductance, and emotion self-reports were monitored. The impact of motion was dramatic. Self-report and physiological data suggested strongly that motion increased arousal, had little impact on valence, and captured and sustained the subject’s attention to the image.

The DCMS Film Policy Review I

This week the Department of Culture, Media, and Sport published the latest review of film policy in the UK. The report is titled A Future for British Film: It Begins with the Audience, and you can access it here. This week’s post covers just a few first impressions I have formed having read the report once. A more detailed and more considered reflection on the issues raised will have to wait for a couple of weeks.

This is the first wide-ranging report on film policy in the UK since A Bigger Picture was published in 1998, though there have been numerous reports covering  a broad range of topics in the past 14 years. This report should of course been undertaken before the dismantling of the UK Film Council because now it is a case of tailoring policy to the institutions we have rather than being able to flexibly adapt to new demands. And it is the new that wrecks policy maker’s fun. A Bigger Picture was almost immediately rendered obsolete by the arrival of digital technology. 3D was old technology in 1998, and now its at the top of the box office charts.

So, first impressions.

1. I like the demand-side approach rather than the focus on production typical of these sorts of reports. The report doesn’t ignore production, but the re-orientation of film policy away from ‘lets produce more British films that on-one will see’ to ‘let’s get people watching films the British films that are available’ is much needed. British film production has been reasonably healthy since the mid-1990s (at least compared to the dark days 1980s), but a long-standing problem is getting screen time in a multiplex dominated market. There’s no point making films people can’t see and there’s no point in making MORE films can’t see which has been UK film policy since 1985. There’s always the possibility that some more British films will make money and so reduce their demands on lottery funding.

The only concern is that focussing resources on independent and specialised film will produce limited benefits from a lot of investment. Audiences for these types of films are smaller than audiences for mainstream cinema, and so there may not be much growth in audiences to be had. The report says that it is important to increase audience choice, and who would disagree with that. But how do you measure the potential for audience growth of specialised films? How do you judge how much money to invest in developing this audience given that audience growth might be quite small? And what if the audience doesn’t want to watch these films?

And how do you get cinema chains to stop showing crap like Green Lantern? Especially when it turns out the average occupancy rate of cinema auditoria in the UK is 20 per cent! Solving the problem of too many bad Hollywood films on British cinema screens would go much further than anything the BFI could ever do. The problem of release windows is recognised in the report and reforming this aspect of the UK film sector in a distribution-led industry will have more impact than simply focussing on production. This is to be applauded. But release windows are determined in Hollywood by multinational corporations who have the power to dictate terms to exhibitors, and why should they care about a policy framework that offers no advantage to them? US producers come to the UK for the quality of the filmmakers, the facilities, and the tax incentives. Where are the incentives for distribution that will make them care?

2. I also like the commitment to ensuring the important role of the BFI Research and Statistics Unit in recommendation 53 (see below), though the suggestion the BFI establishes a ‘research and knowledge’ does raise the questions, doesn’t the RSU already exist and isn’t already fulfilling this function? I’m also a little confused by the recommendation

the BFI be designated a ‘producer of official statistics’ under the Statistics and Registration Service Act 2007, as was the UK Film Council up until 2011.

Wasn’t this function taken over by the BFI? And if not, why not?

But a revved up RSU means more statistical fun for me, and that’s something to look forward to.

3. I don’t like the make up of the panel that produced the report:

• Rt Hon Lord Smith of Finsbury, former Secretary of State for Culture, Media and Sport (Chairman)
• Will Clarke, Independent film distributor, founder and former CEO, Optimum Releasing
• Lord Julian Fellowes, Oscar® winning writer and actor
• Matthew Justice, UK film producer and Managing Director, Big Talk
• Michael Lynton, Chairman & Chief Executive Officer, Sony Pictures Entertainment
• Tim Richards, Chief Executive, Vue Entertainment
• Tessa Ross, CBE, Controller of Film and Drama, Channel 4
• Libby Savill, Head of Film and Television, Olswang LLP
• Iain Smith, OBE, film producer and Chair, the British Film Commission Advisory Board

There is, of course, no reason why any of these people should not have been involved in the review process, but who is missing from this list?

That’s right, academics. There is no one from film studies specialising in film industries, film policy, or British cinema; and there is no economist, sociologist, or geographer specialising in film/media/creative/cultural industries.

There is a great deal of research on the film industry in the UK and yet very little of this is cited by the report. The report contains a list of references 108 references, including a handful to Margaret Dickinson and Sylvia Harvey, Rob Cheek, Maud Mansfield, and Joe Lampel. (None of these references are properly referenced. If this were submitted by a student you would fail it on grounds of not having a proper bibliography. It really is awful). There are no references to the wider body of research of the film industry in the UK, and this is curious because one of the recommendations addresses precisely this issue.

53. The Panel notes the need for a strong evidence base for film policy and recommends the BFI establishes a ‘Research and Knowledge’ function to a) collaborate with industry and stakeholders to generate robust information and data on which to base policy interventions, b) assist in the design of BFI policy and funding interventions from the outset to produce learning that can inform future policy, c) actively disseminate results and learning from funding interventions, and d) over time build and maintain a valuable and accessible knowledge base for the benefit of the public, the BFI, Government, industry, academia and all other stakeholders in film.

It seems odd to recommend that we need a strong evidence base when the existing available research is largely ignored. This problem was raised at the symposium on research and policy making I attended last October (you can read about it here), and it’s nice to see the above recommendation in the report as it means there is a greater chance progress will be made in this area. But this type of report is precisely the sort of situation in which this type of research should have been used, and it would have been nice to see the panel take the opportunity to do just that. Otherwise, what’s the point in doing research?

But what I really don’t like about recommendation 53 is that it envisages academia as a consumer of data produced by the BFI’s ‘research and knowledge’ function rather than being fully integrated into the policy making framework. Academics shouldn’t be sat on the sidelines of film policy. Any future panel reporting on film policy should include academics among its membership – if only to recommend the relevant research outputs to the rest of the panel. It is the BFI’s responsibility to make sure this is achieved sooner rather than not at all. Who else do they think is going create and fulfil the ‘research and knowledge’ function?

It seems odd to say it, but I think the case for film studies could be put to the BFI more strongly.

4. Finally, this report presents a great deal of statistical information and therefore makes the assumption that its readership will be statistically literate enough to understand it. I raised the issue of statistical literacy at last year’s symposium but didn’t get much of response. Given the use of tables, graphs (which I do NOT like), and numerical summaries in this report it is not an issue than can be ignored. The place of statistical literacy in film studies needs to be addressed by the BFI, and I will have more to say on this topic over the next few weeks.

Genre and the UK box office 2011

The top 50 grossing films in 2011 at the UK box office account for a total of $1264 million (approximately £813 million at £1=$1.5547). A breakdown of the total gross by genre is given in Table 1. (For consistency, I’ve employed the same genre classifications that used in earlier posts).

The highest grossing film by quite some distance was Harry Potter and the Deathly Hallows (Part 2) with $117.2 million (~£75.4 million), easily outstripping The King’s Speech ($75.0 million/£48.2 million).

Table 1 Top 50 UK grossing films 2011 by genre (Source: Box Office Mojo)

Two of the top 10 films were action/adventure films: Pirates of the Caribbean: On Stranger Tides (3D) (4th) and Transformers 3 (7th). The performance of the third Transformers film is comparable to the first two (give or take an adjustment for inflation): Transformers grossed $49.9 million in 2007 and Revenge of the Fallen grossed $44.4 million in 2009 (these figures are in 2010 US dollars), while T3 grossed $45.1 million (in 2011 dollars). In contrast, Pirates of the Caribbean: On Stranger Tides grossed only $54.2 million (2011 dollars) compared to $106.8 million for Dead Man’s Chest in 2006 and $85.6 million for At World’s End in 2007 (both in 2010 dollars). Thus the Transformers franchise has maintained its level from film to film, whereas the gap between the 2007 and 2011 films and the loss of key cast members (Orlando Bloom, Keira Knightly) for On Stranger Tides has seen the Pirates franchise shed a substantial part of its value in the UK market.

2011 was comedy’s year. Comedy just beat out action/adventure as the second highest grossing genre and accounted for seven films in the top 50, but of these four made it into the top 10: The Inbetweeners Movie, The Hangover Part II, Bridesmaids, and Johnny English Reborn. The median gross for 54 comedy films to make the top 50 in the UK from 2006 to 2010, inclusive, is $12.84 million (in 2010 dollars); but the median gross last year (in 2011 dollars) was $32.0 million. The Inbetweeners Movie is the highest grossing comedy film in the UK in the past six years with $71.2 million/£45.8 million, easily beating Borat into second place (which grossed $49.8 million in 2006, in 2010 dollars). No matter how you look at it, that’s a big success for a movie based on a British TV show. Paul (21st), Horrible Bosses (27th), and Bad Teacher (37th) were less impressive, but comedy was the big story at the UK box office in 2011.

The most frequently occurring genre is family films accounting for 15 films, which have not performed outstandingly well. In fact this genre did not perform even close to family films in recent years, when Toy Story 3, Shrek 3, Ice Age: Dawn of the Dinosaurs, and Up have been amongst the very highest grossing films in the UK. The highest grossing family film in 2011 was Tangled, which was only the ninth highest grossing film of the year. Eight of the family films grossed less than $15.54 million or £10 million pounds. Why might this be the case? Well, if we look at the family films that made it into the top fifty (Table 2) we note that many of them are animated films while very few are love action films. It may be that the family genre suffered from a lack of variety with a glut of animation and too few other types of family films to attract a diverse audience. There is no Night at the Museum film in this year’s top 50, and Mr. Popper’s Penguins is too close to Happy Feet to make the difference worth noting. Horrid Henry seems to have performed particularly poorly. It is also interesting that The Lion King outperformed many new films, but then it would not be unfair to state that, compared to recent years, this year’s animated offerings were not as good as in recent years. Certainly, there is no Ponyo or Up amongst those films listed in Table 2.

Table 2 Rank and total grosses of family films in the UK 2011 (Source: Box Office Mojo)

As noted above the top grossing film last year was a fantasy/science fiction film, but Harry Potter accounted for 65% of the total gross for this genre in the top 50. Rise of the Planet of the Apes performed respectably as the 11th highest grossing film, but the other three films (Super 8, Source Code, and The Immortals) all feature in the bottom 10 films. In fact, Source Code and The Immortals were ranked 49th and 50th respectively.

The King’s Speech accounts for 51% of the gross of drama films, with the three other films performing modestly. The Black Swan ranked 15th, grossing $26.0 million ($16.7 million), but I can’t decide if this is a good performance of a film about ballet or a disappointment for an Academy Award winning film. 127 Hours (39th) and The Fighter (47th) also performed poorly despite Oscar nominations and awards.

Beyond these five genres, there is very little to note about the others.

The majority of the gross for romance films is accounted for The Twilight Saga: Breaking Dawn Part 1, the 6th highest grossing film of the year. This Twilight film achieved similar rankings to Eclipse (2010 – 6th) and New Moon (2009 – 7th); and achieved similar grosses. The other romance films – One Day (38th) and Friends with Benefits (46th) – aren’t worth commentating on.

Only two horror films made the top 50: Paranormal Activity 3 (26th) and Insidious (42nd). Measured in 2010 dollars, Paranormal Activity grossed $16.3 million in 2009 and Paranormal Activity 2 grossed $17.5 million in 2010. The third instalment in the series grossed $17.0 million in the UK (in 2011 dollars), and so while this series is not troubling the upper reaches of the box office charts it is consistent in the level of its gross from film to film and year to year.

The one film classed as ‘other’ is the Coen Brother’s version of True Grit, which ranked 35th.

Crime/thriller films are barely worth commenting on. The highest grossing film in this genre (if you don’t consider it be an action/adventure movie) is Sherlock Holes: Games of Shadows (18th) and this film was only released on 16 December 2011. Tinker, Tailor, Soldier, Spy (23rd), Limitless (33rd), and Unknown (44th) did very little business. The television schedules in the UK are full to overflowing with crime dramas – Lewis (and the upcoming Endeavour), Midsommer Murders, New Tricks, Sherlock, and so on, along with masses of imports from America (CSI, Criminal Minds, NCIS, The Closer, etc) and Europe (The Killing, Wallander, Romanzo criminale) – so there is clearly an audience for producers to tap into. But no one makes crime movies anymore. Weird.

Cognitive film theory: 2011 bibliographical update

Last January I post a list of papers from 2010 on the broadly defined topic of cognitive film theory, and this year I’m doing the same for the past twelve months. There is something for everyone here (check out Neal et al‘s paper on eating popcorn in the cinema), but I would particularly point you in the direction of a special issue of Science in Context on ‘Cinematography, Seriality, and the Sciences’ from last year, which you can find here.

As ever, this list is not exhaustive but it should be accurate. I’ve included some interesting sounding papers that can be accessed as e-publications ahead of print, and so the year of publication may change when they move from digital to analogue form.

1. Bacon H 2011 The extent of mental completion of films, Projections 5 (1): 31-50.
2. Berliner T and Cohen DJ 2011 The illusion of continuity: active perception and the classical editing system, Journal of Film and Video 63 (1): 44-63.
3. Brown W2011 Resisting the psycho-logic of intensified continuity, Projections 5 (1): 69-86.
4. Caputo NM and Rouner D 2011 Narrative processing of entertainment media and mental illness stigma, Health Communication 6 (7): 595-604. DOI: 10.1080/10410236.2011.560787.
5. Cartwright L 2011 The hands of the projectionist, Science in Context 24 (3): 443-64. DOI: 10.1017/S0269889711000184.
6. Cook RF 2011 Correspondences in visual imaging and spatial orientation in dreaming and film viewing, Dreaming 21 (2): 89-104. DOI: 10.1037/a0022866.
7. Coyne SM, Nelson DA, Robinson SL, and Gundersen NC 2011 Is viewing ostracism on television distressing?, The Journal of Social Psychology 151 (3): 213-217. DOI: 10.1080/00224540903365570.
8. Curtis S 2011 ‘Tangible as tissue:’ Arnold Gesell, infant behavior, and film analysis, Science in Context 24 (3): 417-442. DOI: 10.1017/S0269889711000172.
9. Edelstein RS, Kean EL, and Chopik WJ 2011 Women with an avoidant attachment style show attenuated estradiol responses to emotionally intimate stimuli, Hormones and Behaviour, in press, DOI:10.1016/j.yhbeh.2011.11.007.
10. Ghazanfar AA and Shepherd SV 2011 Monkeys at the movies: what evolutionary cinematics tells us about film, Projections 5 (2): 1-25.
11. Haxby JV, Guntupalli JS, Connolly AC, Halchenko YO, Conroy BR, Gobbini MI, Hanke M, and Ramadge PJ 2011 A common, high-dimensional model of the representational space in human ventral temporal cortex, Neuron 72 (2): 404-16. DOI: 10.1016/j.neuron.2011.08.026.
12. Hoeckner, B, Wyatt EW, Decety J and Nusbaum H 2011 Film music influences how viewers relate to movie characters, Psychology of Aesthetics, Creativity, and the Arts 5 (2): 146-153. DOI: 10.1037/a0021544
13. Howarth PA 2011 Potential hazards of viewing 3-D stereoscopic television, cinema and computer games: a review, Ophthalmic and Physiological Optics 31 (2): 111-122. DOI: 10.1111/j.1475-1313.2011.00822.x.
14. Jones S 2011 The pure moment of murder: the symbolic function of bodily interactions in horror films, Projections 5 (2): 96-114.
15. Kano F and Tomonaga M 2011 Species difference in the timing of gaze movement between chimpanzees and humans, Animal Cognition 14 (6): 879-892. DOI: 10.1007/s10071-011-0422-5.
16. Kovács AB 2011 Causal understanding and narration, Projections 5 (1): 51-68.
17. Lavaur J-F and Bairstow D 2011 Languages on the screen: is film comprehension related to the viewers’ fluency level and to the language in the subtitles?, International Journal of Psychology, 46 (6): 455-462. DOI:10.1080/00207594.2011.565343.
18. Lerner Y, Honey CJ, Silbert LJ, and Hasson U 2011 Topographic mapping of a hierarchy of temporal receptive windows using a narrated story, The Journal of Neuroscience 31 (8): 2906-2915. DOI:10.1523/JNEUROSCI.3684-10.2011.
19. Magliano JP and Zacks JM 2011 The impact of continuity editing in narrative film on event segmentation, Cognitive Science 35 (8): 1489-1517. DOI: 10.1111/j.1551-6709.2011.01202.x
20. Mital PK, Smith TJ, Hill R, and Henderson JM 2011 Clustering of gaze during dynamic scene viewing is predicted by motion, Cognitive Computation 3 (1): 5-24. DOI: 10.1007/s12559-010-9074-z.
21. Neal DT, Wood W, Wu M, and Kurlander D 2011 The pull of the past: when do habits persist despite conflict with motives?, Personality and Social Psychology Bulletin 37 (11): 1428-1437. DOI: 10.1177/0146167211419863.
22. Nishimoto S, Vu AT, Naselaris T, Benjamini Y, Yu B, and Gallant JL 2011 Reconstructing visual experiences from brain activity evoked by natural movies, Current Biology 21 (19): 1641-1646. DOI: 10.1016/j.cub.2011.08.031.
23. Pannasch S, Selden DL, Velichkovsky BM, and Bridgeman B 2011 Apparent Phi-motion in sequences of Eisenstein’s October, Gestalt Theory 33 (1): 69-80.
24. Pavlović I and Marković S 2011 The effect of music background on the emotional appraisal of film sequences, Psihologija 44 (1): 71-91. DOI: 10.2298/PSI1101071P.
25. Plantinga C 2011 Folk psychology for film critics and scholars, Projections 5 (2): 26-50.
26. Sabbadini A 2011 Cameras, mirrors, and the bridge space: a Winnicottian lens on cinema, Projections 5 (1): 17-30.
27. Shibata H, Inui T, and Ogawa K 2011 Understanding interpersonal action coordination: an fMRI study, Experimental Brain Research 211 (3-4): 569-579. DOI: 10.1007/s00221-011-2648-5.
28. Silvia PJ and Berg C 2011 Finding movies interesting: how appraisals and expertise influence the aesthetic experience of film, Empirical Studies of the Arts 29 (1): 73 – 88.
29. Sonnenschein D 2011 Sound spheres: a model of psychoacoustic space in cinema, The New Soundtrack 1 (1): 13-27. DOI 10.3366/sound.2011.0003.
30. Vandaele J 2011 What meets the eye: cognitive narratology for audio description, Perspectives: Studies in Translation, in press, DOI: 10.1080/0907676X.2011.632683.
31. Wagner DD, Dal Cin S, Sargent JD, Kelley WM, and Heatherton TF 2011 Spontaneous action representation in smokers when watching movie characters smoke, The Journal of Neuroscience 31 (3): 894-898. DOI: 10.1523/​JNEUROSCI.5174-10.2011
32. Wilson RT and Till BD 2011 Recall of preshow cinema advertising: a message processing perspective, Journal of Marketing Communications, in press, DOI: 10.1080/13527266.2010.538071.
33. Zacks JM, Kurby CA, Eisenberg ML, and Haroutunian N 2011 Prediction error associated with the perceptual segmentation of naturalistic events, Journal of Cognitive Neuroscience 23 (12): 4057-4066. DOI: 10.1162/jocn_a_00078.
34. Zumalde-Arregi I 2011 The filmic emotion: a comparative analysis of film theories, Revista Latina de Comunicación Social 66: 326-349. DOI: 10.4185/RLCS-66-2011-936-326-349-EN.

Opinion or fact?

The Artist has been wowing audiences across the world. The film has already won some awards, and is hotly tipped for many more. It has also been attracting much interest in the press, and film scholars have been roped into this.

In an interview with the BBC, silent film expert Bryony Dixon of the BFI made a series of statements that are worth reflecting upon:

1. watching silent films is more rewarding than watching contemporary Hollywood action blockbusters
2. watching a silent film requires more work on the part of the viewer
3. slower edited films require greater concentration than rapidly edited films

You can view the video of the interview here. The text on this web page includes the following sentence:

Bryony Dixon, a silent film expert from the BFI, told BBC News that because silent films require more concentration, the rewards of watching them are richer than action blockbusters.

So let’s take these three statements in turn:

1. Watching silent films are more rewarding that watching contemporary Hollywood films

I am aware of no research that compares the viewing pleasures derived from silent films to sound films, and I have not been able to find any such research. In fact, what viewers find rewarding about the film experience is an under-researched area of film studies. If anyone knows of any research in this area please feel free to add a comment to this post listing the appropriate references.

This is just Dixon’s opinion, and we should not be surprised that an expert on silent films should prefer silent films. Other people will have their own opinions, tastes, and preferences. The difference is that other people will not have the opportunity to express them in the BBC under the heading ‘Expert on the rewards of silent film.’ This is problematic because it presents Dixon’s opinion as fact (‘An expert says …’). This may be the fault of the BBC and the way it has presented the interview, but from watching the video I doubt it.

Of course, a factor here  is that there has not been much in the way of silent film since 1930 and so research on what viewers think about silent films has inevitably been extremely limited. The Artist provides an excellent opportunity for researchers to engage with this topic.

2.Watching a silent film requires the viewer to work harder

There is no research that I can find looking at the cognitive load of silent cinema (probably for reasons noted above), and the literature on cognitive load in film viewing is somewhat limited in general.  An interesting place to start is this paper from Nitzan Ben-Shaul:

Ben-Shaul N 2003 Split attention problems in interactive moving audiovisual texts, Fifth International Digital Arts and Culture Conference, Melbourne, Australia, 19-23 May, 2003.

It is also worth reading Julian Hochberg and Virginia Brooks’s work on film viewing and visual momentum as it gives a general description of how observers attend to images (both moving and still) and how we cognitively process this information:

Hochberg J and Brooks V 1978 Film cutting and visual momentum, in JW Senders, DF Fisher, and RA Monty (eds.) Eye-movements and the Higher Psychological Functions. Hillsdale, NJ: Erlbaum: 293-313.

Hochberg J and Brooks V 1996 Movies in the mind’s eye, in D Bordwell and N Carroll (eds.) Post-Theory: Reconstructing Film Studies. Madison, WI: UNiversity of Wisconsin Press: 368-387.

Cognitive load theory (CLT) might support the opposite conclusion to Dixon’s assertion. According to CLT, we have only a limited amount of working memory and the cognitive load of a task is determined by the number and complexity of the steps involved that use up those resources. The following example is from Gutashaw WE and Brigham FJ 2005 Instructional support employing spatial abilities: using complimentary cognitive pathways to support learning in students with achievement deficits, in TE Scruggs, MA Mastropieri (eds.) Cognition and Learning in Diverse Settings: Amsterdam: Elsevier: 47-70.

Watching a film in a language one does not understand but with subtitles is an example of an increased cognitive load over watching the same film in one’s own language. Now image watching a subtitled film with poor reading skills. The cognitive load increases dramatically (66).

Thinking along similar lines, we might think that because we do not have to attend to dialogue as well as images that the cognitive load in watching a silent film is lower than that when watching a film with synchronised dialogue that requires attention to multiple sensory modalities.

There has been no direct research on cognitive load that could answer this question, and so I make this argument as a hypothesis only, but as we see in relation to the next point the evidence indicates it is faster editing that increases the cognitive load on the viewer.

Cognitive load theory does play an important role in the media theory of Richard Mayer and Roxana Moreno, and you can find an introduction their research here: Mayer RE and Moreno R 1998 A cognitive theory of multimedia learning: implications for design principles, ACM SIGCHI Conference on Human Factors in Computing Systems, 18-23 April 1998, Los Angeles.

Dixon’s statement sound plausible, but without supporting research it is nothing more than a hypothesis and there are other hypotheses to be made and tested on this point. Of course, it may be that I just haven’t been looking for research in the right places and so if anyone knows of research demonstrating if this statement is true or not then please let me know.

3. Films edited more slowly require more concentration than rapidly cut films

There are a couple of things to consider here. First, contemporary film audiences are less likely to be familiar with silent films than they are with modern action blockbusters. Therefore, they may concentrate  more on something unfamiliar than something commonplace and this would account for a difference in viewers’ experience. We may find that with increasing experience viewing habits may change so that viewers familiar with both silent films and contemporary cinema watch them in the same way. Again, this relates to the cognitive load placed in the viewer. This sounds plausible, but as noted above I have been able to find no research in this topic. In fact I can find no research on viewers’ ‘concentration’ in the cinema, and this leads us to our second problem: what is meant by ‘concentration?’ Dixon never defines the terms she uses, and it may mean the number of times a viewer looks at the screen, the length of time the viewer looks at a screen, the focus of the viewer’s attention when looking at the screen, etc.

If we take concentration to mean something similar to attention, then there is some research on this topic and it contradicts Dixon’s assertion that slower films require more concentration than fast edited films. Research on the limited capacity model of viewership has shown that rapid pacing in motion pictures requires increased allocation of perceptual resources. The research can be read in this paper:

Lang A, Bolls P, Potter RF, and Kawahara K 1999 The effects of production pacing and arousing content on the information processing of television messages, Journal of Broadcasting and Electronic Media 43 (4): 451-475.

The limited capacity model defines the viewer as an information processor faced with a variably redundant ongoing stream of audio-visual information, in the message content is the topic, genre, and information contained in a message. Therefore, ‘viewing is the continuous allocation of a limited pool of processing resources to the cognitive process required for viewers to make sense of a message.’ (I don’t like this definition of message content – it seems somewhat circular to me).

This research looked at the effect of production pacing and content on attention in the cinema, testing the hypothesis that both pacing and arousing content should increase the level of resources automatically allocated to processing the message. The results showed this is indeed the case: arousing content and fast pace increased self-reported arousal in television viewers, and that both factors increase the allocation of resources to processing messages.

This is also discussed in a subsequent paper (below), which showed that faster pacing resulted in the allocation of greater resources by viewers in attending to a television message and that self-reported arousal also increased with editing pace.

Lang A, Zhou S, Schwartz N, Bolls PD, and Potter RF 2000 The effects of edits on arousal, attention, and memory for television messages: when an edit is an edit can an edit be too much?, Journal of Broadcasting and Electronic Media 44 (1): 94-109.

In summary, there is no evidence that slower films require greater concentration by film viewers but there is evidence that faster paced films – such as (but obviously not limited to) action blockbusters – do elicit greater allocation of information processing resources (including attention).

A final point to make is that we do not yet know what the distribution of shot lengths in The Artist, and so comparing its pace to other films is not yet possible. It will be interesting when the film comes out on DVD and we can look at it frame-by-frame to see whether its editing style is compatible with contemporary cinema or with silent films of the 1920s. However, as yet we cannot make any empirical statement about the contribution of editing to the pace of this film.

Dixon’s comments raise some interesting questions about the nature of film viewing and silent cinema, but in the absence of supporting evidence they are opinions and not facts. The danger comes when we accept the former as the latter without asking questions or referring to the existing research in this area. Empirical research leads us to reject incorrect and empty opinions by establishing the nature of those facts. This is what film studies is supposed to be for.

Research on blockbusters

As we all know blockbusters are the bane of the film industry: a recent article in The Telegraph quoted Steven Spielberg’s opinion that contemporary Hollywood has produced few films that will still be viewed in 20 years time. The article can be read here. I think that in general, Spielberg has a point about the general quality of Hollywood films since the mid-1990s. Personally, I just do not find the cinema of the past few years as exciting as I did when I was 18 and going to Canterbury to study film, and the endless repetition and extension of comic book adaptations is evidence of a great amount tedium that I just do not want to watch. (And it’s not like I don’t own scores of comics books and graphic novels). However, much of the blame can be laid at Spielberg’s feet for encouraging big-budget franchise films (Indiana Jones, Jurassic Park). Some of Spielberg’s comments are remarkably self-serving and more than a little disingenuous:

Attacking the prevalence of film franchises – movies based on toys, or video games, that are intended to sell a product as much as they are to entertain – Spielberg said: “I think producers are more interested in backing concepts than directors and writers.

“I don’t think that’s the right way of making a decision about whether you’re going to back a film or not, but a lot of these hedge funds – these independent groups that are coming up with the money – are looking at the big idea more than who the director or writer is. And of course, they all want the guarantee of a big actor.

“My whole career has survived without big movie stars. Yes, I’ll do movies with Tom Cruise and Tom Hanks, and I enjoy that, but most of my movies have had unknowns in them. And they’ve done pretty well.”

Make of that what you will.

The problem isn’t ‘blockbusters’ per se, but rather the lack of diversity in the film industry. As I showed here, the action/adventure, family, and fantasy/science fictions films have become increasingly dominant at the US box office at the expense of crime/thriller films, dramas, and (to a lesser extent) comedies.

But we shouldn’t always be disappointed with blockbusters – they can be great movies, and the scale of the cinema is one thing that makes experiencing a film on the big screen so thrilling. They are also the focus of a number interesting research papers that cover many different aspects of the cinema, and a selection are set out below.

As ever, the version linked to may not be the final published version.

Aldred J 2006 All aboard The Polar Express: a ‘playful’ change of address in the computer-generated blockbuster, Animation: An Interdisciplinary Journal 1(2): 153-172.

Following Tom Gunning’s assertion that each change in film history implies a change in its address to the spectator, this article closely analyses The Polar Express (Robert Zemeckis, 2004) in order to interrogate what kinds of changes are at stake for the contemporary spectator of the wholly computer generated blockbuster. The article also considers the extent to which the immersive, video game-like visual aesthetic and mode of address present in The Polar Express strive to naturalize viewer relations with digital spaces and characters such as those inherent to both computer-generated films and the ‘invisible’ virtual realm of cyberspace. Finally, the article argues that The Polar Express functions as a compelling historical document of an era when cinema and video games have never been more intertwined in terms of aesthetics, character construction, and narrative, and raises compelling questions about whether video games have begun to exert the type of formative influence upon cinema that cinema previously exerted on video games.

Elsaesser T 2001 The blockbuster: everything connects, but not everything goes, in J Lewis (ed.) The End of Cinema as We Know It. New York: New York University Press: 11-22.

… What characterizes a blockbuster? First, a big subject and a big budget (world war, disaster, end of the planet, monster from the deep, holocaust, death battle in the galaxy). Second, a young male hero, usually with lots of firepower, or secret knowledge, or an impossibly difficult mission. The big movie is necessarily based on traditional stories, sometimes against the background of historical events, more often a combination of fantasy or sci-fi, with the well-known archetypal heroes from Western mythology on parade. In one sense, this makes blockbusters the natural, that is, technologically more evolved, extension of fairy tales. In another sense, these spectacle “experiences,” these “media events,” are also miracles, and not at all natural. Above all, they are miracles of engineering and industrial organization. They are put together like supertankers, aircraft carriers or skyscrapers, office blocks, shopping malls. They resemble military campaigns, and that’s one of the main reasons they cost so much to make. …

Fernandez-Blanco V, Ginsburgh V, Prieto-Rodriguez J, and Weyers S 2011 As good as it gets? Blockbusters and the inequality of box office results since 1950, in J Kaufman and D Simonton (eds.) The Social Science of the Cinema.  Oxford: Oxford University Press.

This paper analyses how success, measured by box office revenues, is distributed in the movie industry. The idea that “the winner takes all” is pervasive in describing the high degree of inequality in revenues, since we are all subject to the cognitive bias known as “recency effect,” and have myopic perceptions which make us think that recent events are more relevant. This makes us believe that inequalities are much more important today than they used to be. Blockbusters such as Avatar, The Black Knight, Pirates of the Caribbean, Dead Man’s Chest or even Titanic lead us to overestimate revenue inequality. As is the case with many simplifications, this one is also misleading.

Glastein J, Ludomirsky O, Lyettefi D, Vaish P, Joglekar NR 2003 Blockbusters: building perceptions and delivering at the box office, 21st System Dynamics Conference, 20-24 July 2004, New York.

The Hollywood Stock Exchange (HSX) is an on-line market that tracks the perceived value of movie talent and their product: the movies themselves, while they are in development or production. We model the decision rules that drive this market place and estimate the underlying decision parameters by calibrating the evolution of a selected sample of 23 movies released in 2001-2002. Our results show systematic differences in the decision rules followed by the market for the eventual winners (a.k.a. the blockbusters) and the losers at the box office. Regression analysis of combined decision parameters for winners and losers cannot explain the variance in the box office performance. However, segmenting these data between winners and losers provides selective insights about how the aggregate market perceptions evolve.

Mélat H 2007 Order and disorder in contemporary Russian blockbusters, Przeglad Rusycystyczny 120: 90-98.

One of the most striking phenomena in the Russian culture at the turn of the 21st century is the explosion of popular culture (detective literature and cinema, romance, fantasy) and its diversification. For a scholar, popular culture is interesting because, on the one hand, it reflects the state of mind of the population and, on the other hand, it helps to create a special ‘populous’ state of mind. It is a powerful tool for the political establishment that helps to convey an ideology because it is both entertaining and easily accessible. In this vein, modern fairy tales for adults can tell us a lot about the Russian society of our days.

Due to the powerful changes within the Russian society at the beginning of the 1990s, the market for literature and cinema was heavily influenced by the Western type bestsellers and blockbusters. For example, first introduced in translation, the crime fiction became an almost universally celebrated genre, and by the middle of the 1990s, Russia’s own crime fiction, represented by the novels by Aleksandra Marinina, Dar’a Dontsova, and Boris Akunin, dominated the literary scene. The television and cinema adaptations of these books only further promoted this genre.

…

In this paper, I intend to focus on the few Russian blockbusters and their sequels that are traditionally qualified as thrillers. My analyses will deal with the direct correlation between those films and their sequels, and, first and foremost, how the artistic universe created in these first films evolves and changes in their sequels. I would like to suggest that this evolution is highly reflective of the ideological changes within the Russian society itself.

Ravid SA 1999 Information, blockbusters, and stars: a study of the film industry, Journal of Business 72 (4): 463-492.

This article presents two alternative explanations for the role of stars in motion pictures. Either informed insiders signal project quality by hiring an expensive star, or stars capture their expected economic rent. These approaches are tested on a sample of movies produced in the 1990s. Means comparisons suggest that star-studded films bring in higher revenues. However, regressions show that any big budget investment increases revenues. Sequels, highly visible films and ‘‘family oriented’’ ratings also contribute to revenues. A higher return on investment is correlated only with G or PG ratings and marginally with sequels. This is consistent with the ‘‘rent capture’’ hypothesis.

Riegg RM 2009 Opportunism, uncertainty, and relational contracting – antitrust rules in the film industry, unpublished article.

For a long time, economists and investors have been baffled as to why Studios continue to produce movies with “blockbuster”-sized budgets (i.e. movies with budgets over $100 million) when producing those movies expose Studios to considerable economic risk.

By explaining the unique economics of the Film industry, and the effect of the Paramount (antitrust) rules on Film distribution contracts, this article provides an explanation to the puzzle of the blockbuster that is confirmed by recent trends in Film industry. Additionally, by using the Film industry as a model, this article also demonstrates how relational contracting can be understood as a means of coping with extreme uncertainty and under what circumstances relational contracting can be more efficient than formal contracts.

As a practical resource, this article has several uses. First, the article can provide support to attorneys concerned about a revival of stiff antitrust rules in the Film industry. Second, it can provide a potential guide to investment for Studio executives deciding how to best allocate their resources. Third, it can provide a model of contracting for businesses concerned with preventing opportunism in those industries marked by extreme uncertainty.

Correspondence analysis of genre preferences in UK film audiences

Genre provides viewers with a first reference point for a film, and functions as a ‘quasi-search’ characteristic through which audiences assess product traits without having seen a particular film (Hennig-Thurau et al. 2001). In a market place comprising a large number of unique cultural products with no unambiguous reference brand, audiences form experience-based norms at the aggregate level of genre rather than the specific level of individual films (Desai & Basuroy 2005). Consequently, genre is the means by which the film industry alerts viewers that pleasures similar to those previously enjoyed are available without compromising the need for novel products; and empirical research has shown that genre is an important factor – if not the most important – in audiences’ decision making about which film to see (Litman 1983, Da Silva 1998).

Understanding audience preferences for certain types of films is therefore a priority for film producers and distributors as this will be a factor in deciding which films to produce and how to market them effectively. In this short paper we analyze the genre preferences of UK film audiences, applying correspondence analysis to data produced by the British Film Institute’s research into the cultural contribution of film in the UK. Specifically, we focus on how genre preferences vary with gender and age when treated as a single composite variable.

The BFI dataset

In July 2011, the British Film Institute (BFI) published a report, Opening Our Eyes (Northern Alliance/Ipsos Media CT 2011), examining the cultural contribution of film in the UK [1]. This report analysed how audiences consume films and attitudes to the impact of film based on a series of qualitative ‘paired depth’ interviews and an online survey of 2036 UK adults aged between 15 and 74.

Question C.1 in the questionnaire invited respondents to express preferences for their favourite genres/type of films from a list comprising action/adventure, animation, art house/films with particular artistic value, comedy, comic book movie, classic films, documentary, drama, family film, fantasy, foreign language film, horror, musicals, romance, romantic comedy, science fiction, suspense/thriller, other, none, and don’t know. Respondents were able to select as many genres as they wished, and the data represents the number of respondents expressing a preference for that genre. Figure 7 in the final report presents the breakdown of genre preferences by gender, concluding that male audience members exhibit stronger preferences for science fiction, action/adventure, and horror films while women preferred romantic comedies, family films, romances, and musicals [2]. In an additional detailed summary made available online, genre preferences were broken down by age group. These results showed younger respondents were more likely select comedy, horror, animation, and comic book as their favourite genres, whereas older audience members were more likely to select dramas, documentaries, and classic films.

The report did not present any findings regarding genre preferences based on the combination of the gender and the age of the subjects, and it is this interaction analysed here. In addition to publishing the final report the BFI has made the full set of result tables from the quantitative survey available to researchers freely online. Table 416 of this output contains the data on gender, age, and genre preferences, and is the basis for our correspondence analysis. We use nineteen of the categories listed above, with ‘don’t knows’ excluded from the analysis. Table 416 lists the additional genre categories of westerns, historical, war, and gangster films, and these have been included in the category ‘other.’

Correspondence analysis

Correspondence analysis (CA) is a multivariate technique for exploring and describing frequency data defined by two or more categorical variables in a contingency table. By calculating chi-square distances between the row and column profiles in a table, CA determines the (dis)similarity of the reported frequencies. CA aims to reveal the structure inherent in the data, and does not assume an underlying probability distribution. Consequently, CA requires that all of the relevant variables are included in the analysis and that the entries in the data matrix are nonnegative, but makes no other assumptions. CA does not support hypothesis testing, and cannot be used to determine the statistical significance of relationships between variables. Here we describe the outputs of the correspondence analysis and their interpretation, and the reader can find introductions to the theory and mathematics of CA in Clausen (1998), Beh (2004), and Greenacre (2007).

The first output of the correspondence analysis is a table describing the variation in the contingency table, referred to as the inertia. The total inertia in the table is equal to the chi-square statistic divided by the total sample size:  Φ² = χ²/N. This variation is decomposed into the principal inertias of a set of dimensions, each accounting for a percentage of the total inertia. For an r × c table, the maximum number of dimensions is min(r-1, c-1). The number of dimensions retained for analysis is based on the first k dimensions to cumulatively exceed a threshold (typically 80 or 90 per cent of the total inertia), all those individual dimensions accounting for more than 1/(min[r, c] – 1)% of the total inertia, or by reference to a scree plot of the inertias to determine where the drop in the percentage accounted for by a dimension drops away less rapidly. It is also dependent on our ability to give a meaningful interpretation to the dimensions selected. In selecting only a subset of the available we lose some of the information contained in the original table, but in discarding some dimensions we are able to see structure of the data more clearly for as little cost as possible.

As a form of geometric data analysis, correspondence analysis enables the information in a contingency table to be represented as clouds of points in low-dimensional graphical displays (see Le Roux & Rouanet 2005, Greenacre 2010: 79-88). The origin of the graph represents the average row (column) profile, and by assessing the distance of points from the centroid of the clouds we describe the variation within the table and their similarity. Row (column) points that lie close to the origin are similar to the average profile of the row (columns). Data points that lie far from the origin indicate categories for which the observed counts differ from the expected values under independence and account for a larger portion of the inertia. Points from the same data set lying close together represent rows (columns) that have similar profiles, and data points that are distant from one another indicate that the rows (columns) are remote. The distance between row points and column points cannot be interpreted as meaningful as they do not represent a defined quantity. The angle (θ) subtended at the origin defines the association between row and column points: when the angle is acute (θ < 90°) points are interpreted as positively correlated, points are negatively correlated if the angle between them is obtuse (θ > 90°), and points that subtend a right angle (θ = 90°) are not associated (Pusha et al. 2009).

In addition to the graphical displays, a detailed numerical summary of the correspondence analysis is produced. The mass of a row (column) indicates the proportion accounted for by that category with respect to all the rows (columns), and is simply the row (column) total of divided by the total sample size; while the inertia of a data point is its contribution to the overall inertia. The squared correlation describes that part of the variation of a data point explained by a particular dimension. The quality of a data point measures how well it is represented by the graph, and is equal to the sum of the squared correlations of the dimensions retained for the analysis. The higher the quality of a data point the better the extracted dimensions represent it, and ranges from 0 (completely unrepresentative) and 1 (perfectly represented). The absolute contribution of a data point describes the proportion of the inertia of each dimension it explains, and is determined by both the mass of the data point and its distance from the centroid.

Gender, age, and genre preferences

Table 416 of the BFI’s results output presents counts of genre preferences sorted by gender, by age, and by gender and age. As our interest lies in the variation of genre preferences (19 categories) among UK audiences based on both gender and age we use only this last part of the table, treating ‘gender-age’ as an interactively coded variable with 10 categories combining all the levels of the variables gender (2 categories) and age (5 categories) (Greenacre 2007: 121-128). We apply correspondence analysis to this table using the ca package (version 0.33; see Nenadić & Greenacre 2007) in R (version 2.13.0).

Table 1 presents the 10 × 19 cross-tabulation of ‘gender-age’ with genre. The chi-square statistic for this table is 1312.28 (N = 13086, df = 162, p = <0.01), and we therefore conclude that there is a statistically significant association between gender-age and genre preferences for UK film audiences. However, there is only a weak correlation between ‘gender-age’ and genre preference, with just 10% of the variation in Table 1 due to dependence: Φ² = χ²/N = 1312.28/13086 = 0.1003.

Table 1 Cross-tabulation of interactively-coded gender-age variable with genre. Cell counts represent the number of respondents in each group expressing a preference for a genre. Source: BFI/Northern Alliance/Ipsos Media CT. Click on the table to see it full size.

Table 2 shows the principal inertias, percentages, and cumulative percentage of each dimension, with a scree plot of the inertias. The first two dimensions account for 90.6 per cent of the inertia and the scree plot flattens out after the second dimension. Consequently, these dimensions were retained for analysis and the remainder were discarded.

Table 2 Principal inertias of the correspondence analysis applied to Table 1 explained by dimensions with scree plot

Figure 1 is the resulting symmetric map based on these two dimensions. Tables 3a and 3b present the detailed numerical summary of the results for the rows (gender-age categories) and columns (genre categories), respectively. Click on the graph to see it full size.

Figure 1 Symmetric correspondence analysis map of interactively coded ‘gender-age’ cross-tabulated with genre for UK film audiences

Table 3a Detailed numerical summary of correspondence analysis by gender-age. Click on the table to see it full size.

Table 3b Detailed numerical summary of correspondence analysis by genre. Click on the table to see it full size.

From Table 3a and Figure 1 we see a clear horizontal separation between the male and female respondents, with points arranged vertically by age group from youngest to oldest within each gender category. Consequently, we interpret the principal axes in terms of the rows of Table 1, with the first dimension understood as gender and the second dimension as age. As gender accounts for 64.3 per cent of the total inertia compared to 26.3 per cent for age, this factor is dominant and explains the major part of the variation in Table 1. The quality for the gender-age groups is high (see Table 3a), and these factors are well represented in two dimensions. The points for all gender-age groups are distant from the origin, indicating that no group is close to the average profile in either dimension and that all the groups contribute to the overall inertia.

From Figure 1 we see the distance between the points representing male audience members greater as the age of the respondents increases. The points for males aged 15-24 and 25-34 are very close indicating they have similar row profiles and, therefore, similar genre preferences. The two middle-aged groups are distant from both the youngest and the oldest, while also being remote from one another. Males over the age of 55 are remote from the other age groups, indicating that their genre preferences are substantially different from those of younger male audience members. The points representing female respondents show a similar pattern with the middle-aged groups distant from both youngest and oldest and with over 55s are remote from younger female audience members in their preferences. The greatest contrasts in genre preferences are observed when taking gender and age together: females over 55 are most different from males aged 15-24, and males aged 55+ are most different from young women.

A key difference between audience groups is how the importance of the factors of gender and age vary in explaining their genre preferences. Age becomes increasingly important in the representation of the points for male audience categories. The squared correlations for the three youngest male groups are greatest for dimension 1, indicating that their gender is more important in explaining their preferences than age; for males aged 45-54 gender is still the dominant component albeit to a lesser extent than younger cohorts and the influence of age becomes more apparent in the raised squared correlation for dimension 2; while for males aged 55+ age is the dominant factor. This pattern is not evident for female respondents, and looking at the squared correlations in Table 3a we see the opposite pattern to male audience members. The squared correlations for women aged 35-44, 45-54, and 55+ are dominated by the dimension of gender, whereas age is the main factor for the two youngest groups. However, it should be noted that for the females aged 15-24, gender does contribute substantially to the representation of this point.

Although the correlation between gender-age and genre preference is low, it is clear from these results that the variation within Table 1 is highly structured in terms of the gender and age of the respondents. Describing the preferences of UK cinemagoers therefore requires taking both these factors into account and failure to do so leads to much useful information being obscured. The headline percentages reported by the BFI give only a partial picture of the genre preference of UK film audiences that fails to adequately capture that structure.

Turning to the genre categories themselves we see that the quality of these points is high (see Table 3b), indicating they are well represented in two dimensions and that gender and age are good predictors of the genre preferences of UK audiences. However, we note the quality of the representation for foreign (0.41) and art-house (0.14) films by these two dimensions is very low. This indicates gender and age do not explain variation in audience preferences for these types of films, and that some other factor should be considered. Based on other data available in the BFI’s results output, level of educational attainment is a better predictor of audience preference for these types of films: Table 20 of the results output cross-tabulates level of education and type of film most often watched, with 68 per cent of respondents selecting foreign language films educated to degree level. These two categories are typically applied to films to distinguish them from mainstream cinema (i.e. Hollywood films), and may not function as genre labels in the same context as terms such as ‘comedy,’ ‘drama,’ etc.

The quality of the categories ‘other’ and ‘none’ are also much lower than the mainstream genres, but as these points represent indistinct categories we do not discuss them further.

Gender is the most important factor in determining genre preference, with the cloud of points representing genres orientated along the first principal axis. Family films, romance, and romantic comedies are all associated with female audiences. In fact, 83 per cent of respondents to express a preference for romance films were female, and the corresponding figures are also high for family films (64%) and romantic comedies (72%). Musicals are also strongly associated with female audiences (71%), but this category is dominated by over 55s: over a quarter of respondents expressing a preference for this genre are in this age group. Drama also lies along the same direction as females over 55 indicating that this group is associated with this genre, but the distance from the origin is smaller reflecting a smaller effect. The proportion of males over 55 selecting drama films as a preferred genre is also greater than younger male viewers, but not to the same extent as their female counterparts. In fact, female viewers in each age group expressed a stronger preference for drama films than male viewers of the same age.

Genres associated with male audiences tend to be action-based and technology-driven. Of respondents expressing a preference for science fiction films, 65 per cent were male and there is little variation between age groups within this gender category. Consequently, this genre is very well represented by the first principal axis and age is not a significant factor. This is also the case for action/adventure films (58%), albeit it to a lesser degree as this point lies nearer the origin. Comic book, fantasy, and horror films are strongly correlated with male audiences, and lie along the same direction as males aged 15-24 and 25-34 indicating that age also a key factor here. The squared correlations for gender are the dominant factors for these genres, but age also contributes a substantial part of these points’ representation.

It is interesting that genres we associate with male audiences appear to have broader appeal than genres we associate with female audiences. Dividing the cells by the column totals to give the proportion of respondents in each gender-age group expressing a preference for a genre, we see that no male age group accounts for more 4 per cent of the total for romance films compared to the very large proportion for female audiences noted above. Although female associated, family films do not show the extreme divide as romance films, romantic comedies, and musicals. For science fiction films, the female respondents account for a total of 35 per cent of the expressed preferences for this genre, with each age group within this gender category contributing between 5 and 8 per cent of the total. This is also the case for comic book and action/adventure films. We conclude that so-called ‘female genres’ hold very little appeal to male audiences; and that while similar patterns are certainly evident for ‘male genres’ the effect is much smaller.

Three genres show high squared correlations with age. In all the cases the contribution of the first principal axis is small, and we conclude that gender is relatively unimportant in explaining audience preferences for these films. Animation is associated with under 35s, though female viewers aged 35-44 account 13 per cent of the column total in Table 1 possibly due to selecting these films for family viewing. Documentaries and classic films are associated with over 55s. Of those expressing a preference for documentaries, 18 per cent were males over 55 and 17 per cent were females in the same age group. There is no specific trend among the other age groups, which show roughly equal levels of interest in these films. It is noticeable that proportion selecting classic films increases with age, though this may reflect the aging of the audience rather than a clear genre preference as the new films of one’s youth become classics with time.

Two genres – comedy and suspense/thriller – lie near the origin. These points also have the lowest quality of the mainstream genres, though both are still well represented in Figure 1. Both dimensions contribute to the representation of these points, indicating that gender and age are relevant factors. Gender makes a larger contribution to comedy than age, with males under 35 slightly more likely to express a preference for this genre than males over 35 or female viewers; while for suspense/thrillers over 55s of both genders account for slightly greater proportion of the preferences expressed for this category. However, it is their closeness to the average profile that is most informative about these points, indicating that all gender-age groups enjoy these types of films. This does not mean that they are watching the same films within these genres – it is very unlikely males aged 15-24 are watching the same comedy films, for example, as women over 55; but the BFI’s data cannot help us to explore this aspect.

Conclusion

This study analyzed the genre preferences of British film audiences. We have replicated the results originally presented by the BFI, and have extended them to reveal additional patterns in the data. Correspondence analysis enables us to obtain an overview of how different sections of the audience for films in the UK relate to one another, and to assess the relative importance of different factors in explaining the variation among audiences and their genre preferences. The study showed that gender is the dominant factor in determining audience preferences, with age an important but secondary factor. Most genres can be identified as either ‘male’ or ‘female’ with clear age profiles evident within gender categories, though preferences for animated films, classic movies, and documentaries are determined by age alone. These factors do not adequately explain variation among audiences when applied to categories of films that lie outside mainstream cinema.

Notes

1.The report, the research questionnaire, the detailed summary, and the full set of result tables are available at http://www.bfi.org.uk/publications/openingoureyes/, accessed 21 November, 2011.

2. The report also presents results based on respondents’ ethnic minority but these will not be discussed here.

References

Beh EJ 2004 Simple correspondence analysis: a bibliographic review, International Statistical Review 72 (2): 257-284.

Clausen S-E 1998 Applied Correspondence Analysis: An Introduction. Thousand Oaks, CA: Sage.

Da Silva I 1998 Consumer selection of motion pictures, in BR Litman (ed.) The Motion Picture Mega-industry. Boston: Allen and Bacon: 144-171.

Desai KK and Basuroy S 2005 Interactive influence of genre familiarity, star power, and critics’ reviews in the cultural goods industry: the case of motion pictures, Psychology and Marketing 22 (3): 203-223.

Greenacre M 2007 Correspondence Analysis in Practice, second edition. Boca Raton, FL: Chapman & Hall/CRC.

Greenacre M 2010 Biplots in Practice. Bilbao: Fundación BBVA.

Hennig-Thurau T, Walsh G, and Wruck O 2001 An investigation into the factors determining the success of service innovations: the case of motion pictures, Academy of Marketing Science Review 6: http://www.amsreview.org/articles/henning06-2001/pdf, accessed 24 May 2011.

Le Roux B and Rouanet H 2005 Geometric Data Analysis: From Correspondence Analysis to Structural Data Analysis. Dordrecht: Kluwer Academic Publishers.

Litman BR 1983 Predicting success of theatrical movies: an empirical study, Journal of Popular Culture 16 (4): 159-175.

Nenadić O and Greenacre M 2007 Correspondence analysis in R, with two- and three-dimensional graphics: the ca package, Journal of Statistical Software 20 (3), http://www.jstatsoft.org/v20/i03/paper, accessed 6 September 2011.

Northern Alliance/Ipsos Media CT 2011 Opening Our Eyes: How Film Contributes to the Culture of the UK, July 2011.

Pusha S, Gudi R, and Noronha S 2009 Polar classification with correspondence analysis for fault isolation, Journal of Process Control 19 (4): 656-663.

Statisical Resources: Open Learn

Open Learn is a group of FREE courses from the Open University. As you would expect from a major educational institution with a long and proud history of providing high quality education, these offerings are a real gem and it would be foolish to pass up the opportunity to make the most of them.

You can access the site here.

Open Learn offers many different courses covering many different subjects – but not film studies, which is a shame. It does, however, include a whole series of mathematics and statistics modules aimed at students of different levels covering everything from descriptive statistics and graphs to statistical modelling. Many of these courses are interactive, and they are designed to provoke you. Courses worth checking out are:

• Finding information in mathematics and statistics (Introductory)
• Diagrams, charts, and graphs (Introductory)
• Exploring data: graphs and numerical summaries (Introductory)
• Interpreting data: boxplots and tables (Intermediate)

The focus of these courses is more on learning statistical concepts and how to use the tools of statistics effectively than the procedural knowledge of performing calculations. There is no assumption of prior knowledge of statistical methods. Key concepts are explained clearly and simply, and best of all they come in small chunks that avoid the over-designed deluge of information you get from a lot of statistics textbooks. Consequently, you can get learn a great deal very quickly and very simply.

There are also forums for discussing the content of the courses, but there is not tutorial support. These are only open to registered participants, but you do not have to register to follow the courses.

This is an excellent place to begin if you want to start developing some of the research skills you will need in film studies (but which you will not be taught on film studies degrees). Working through the courses listed above will make life so much easier when starting a more formal course in statistics. Taking some time to work through the basic modules will certainly put you in a better position to interpret empirical research in film studies, to be able to use information more judiciously and thereby to distinguish good research from bad, and eventually to be able to do some research using statistical methods.

A very good thing indeed.

 

Time series analysis of ITV news bulletins

Back in the summer I wrote a post looking at the relationship between the discourse structure and the formal structure of BBC news bulletins (see here). This week I have the first draft of a similar paper looking at news bulletins from ITV.

The pdf file can be accessed here: Nick Redfern – Time series analysis of ITV news bulletins

Abstract

We analyze shot length data from the three main daily news bulletins broadcast on ITV 1 from 8 August 2011 to 12 August 2011, inclusive. In particular, we are interested to compare the distribution of shot lengths of bulletins broadcast on different days and at different times across this time period, and to examine the time series structure by identifying clusters of shots of shorter and longer duration in order to understand the relationship between this aspect of the formal structure to the discourse structure of these broadcasts. The discourse structure of the bulletins in this sample is fixed, and remains constant irrespective of the subject of news items themselves suggesting that content is adapted to meet the needs of this structure. The statistical results show that neither the day nor the time of broadcast has any impact on the distribution of shot lengths, and the editing style is consistent across the whole sample. There is no common pattern to the time series of these bulletins, but there are some consistent features in the time series for these bulletins: clusters of longer takes are associated with static shots of people talking on-screen, while clusters of shorter takes occur with montage sequences, sports reports, series of news items, and footage from non-ITN sources. Consequently, the presence and order of discourse elements in a bulletin shapes its formal structure.

The data for the bulletins used in this study can be accessed as an Excel 2007 file here: Nick Redfern – ITV News Bulletins

I’m a little wary of making direct comparisons between this data and that of the BBC news bulletins as they are separated by three months and deal with news presentation in very different circumstances. The data used in the ITV study covers the week of the riots in the UK this August, and this presents a very different news cycle to that seen in the BBC data from April. However, some general points can be made:

• In both samples clusters of longer shots are associated with people speaking at length on camera, and these shots are framed in the same way.
• In both samples clusters of shorter shots are often associated with montage sequences accompanied by a description from an off-screen reporter or with footage that is derived from other sources (e.g. library footage, other broadcasters).
• In both samples, there is no evidence of any trends or cycles in the time series.
• There is no significant difference in the median shot lengths and dispersion of shot lengths in the two samples of bulletins (BUT remember these are from different times of the year, so this information is only of limited use).
• Day and time of broadcast have no impact on news bulletins for either broadcaster (but again the comparison is not as direct as I would like).

Overall, there is some evidence that news bulletins are stylistically homogenous across these broadcasters. I will do another study looking at the comparing the bulletins from the both the BBC and ITV from a single week, but this will have to wait for another day.

Analysing film texts

The statistical analysis of literary style was initiated by Augustus De Morgan in 1851, when he observed that ‘I should expect to find that one man writing on two different subjects agrees more nearly with himself than two different men writing on the same subject’ and suggested that average word length word be an appropriate indicator of style.This was followed up by TC Mendenhall, who analysed the works of William Shakespeare and Sir Francis Bacon by looking at the frequency distributions of word lengths.

It may seem that focussing on literary style will be of little use when dealing with films, but there is a body of research that examines film scripts and audio descriptions in order to understand the structure of narrative cinema. This post presents links to some of this material. I had intended to include this research in some of the earlier posts on empirical studies of film style, but it never quite seemed to fit (and I may have forgotten on more than one occasion). Besides it deserves a post of its own.

The best place to start is probably Andrew Vassiliou’s Ph.D thesis:

Vassiliou A 2006 Analysing Film Content: A Text Based Approach. University of Surrey, unpublished Ph.D thesis.

The aim of this work is to bridge the semantic gap with respect to the analysis of film content. Our novel approach is to systematically exploit collateral texts for films, such as audio description scripts and screenplays. We ask three questions: first, what information do these texts provide about film content and how do they express it? Second, how can machine-processable representations of film content be extracted automatically in these texts? Third, how can these representations enable novel applications for analysing and accessing digital film data? To answer these questions we have analysed collocations in corpora of audio description scripts (AD) and screenplays (SC), developed and evaluated an information extraction system and outlined novel applications based on information extracted from AD and SC scripts.

We found that the language used in AD and SC contains idiosyncratic repeating word patterns, compared to general language. The existence of these idiosyncrasies means that the generation of information extraction templates and algorithms can be mainly automatic. We also found four types of event that are commonly described in audio description scripts and screenplays for Hollywood films: Focus_of_Attention, Change_of_Location, Non-verbal_Communication and Scene_Change events. We argue that information about these events will support novel applications for automatic film content analysis. These findings form our main contributions. Another contribution of this work is the extension and testing of an existing, mainly-automated method to generate templates and algorithms for information extraction; with no further modifications, these performed with around 55% precision and 35% recall. Also provided is a database containing information about four types of events in 193 films, which was extracted automatically. Taken as a whole, this work can be considered to contribute a new framework for analysing film content which synthesises elements of corpus linguistics, information extraction, narratology and film theory.

These papers present different aspects of the approach, using written texts to distinguish between film genres, to explore the clustering of narrative events, and the emotion responses of viewers.

Salway A, Lehane B, and O’Connor NE 2007 Associating characters with events in films, 6th ACM International Conference on Image and Video Retrieval, 9-11 July 2007, Amsterdam.

The work presented here combines the analysis of a film’s audiovisual features with the analysis of an accompanying audio description. Specifically, we describe a technique for semantic-based indexing of feature films that associates character names with meaningful events. The technique fuses the results of event detection based on audiovisual features with the inferred on-screen presence of characters, based on an analysis of an audio description script. In an evaluation with 215 events from 11 films, the technique performed the character detection task with Precision = 93% and Recall = 71%. We then go on to show how novel access modes to film content are enabled by our analysis. The specific examples illustrated include video retrieval via a combination of event-type and character name and our first steps towards visualization of narrative and character interplay based on characters occurrence and co-occurrence in events.

Salway A, Vassiliou A, and Ahmad K 2005 What happens in films?, IEEE International Conference on Multimedia and Expo, 6-8 July 2005, Amsterdam.

This paper aims to contribute to the analysis and description of semantic video content by investigating what actions are important in films. We apply a corpus analysis method to identify frequently occurring phrases in texts that describe films – screenplays and audio description. Frequent words and statistically significant collocations of these words are identified in screenplays of 75 films and in audio description of 45 films. Phrases such as `looks at’, `turns to’, `smiles at’ and various collocations of `door’ were found to be common. We argue that these phrases occur frequently because they describe actions that are important story-telling elements for filmed narrative. We discuss how this knowledge helps the development of systems to structure semantic video content.

Vassiliou A, Salway A, and Pitt D 2004 Formalizing stories: sequences of events and state changes, IEEE International Conference on Multimedia and Expo, 27-30 June 2004, Taipei, Taiwan.

An attempt is made here to synthesise ideas from theories of narrative and computer science in order to model high level semantic video content, especially for films. A notation is proposed for describing sequences of interrelated events and states in narratives. The investigation focuses on the idea of modelling video content as a sequence of states: sequences of characters’ emotional states are considered as a case study. An existing method for extracting information about emotion in film is formalised and extended with a metric to compare the distribution of emotions in two films.

Finally, a PowerPoint presentation by Andrew Salway that covers the topic fairly extensively can be accessed here.