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  • Writer's pictureDarien Smith

Critical Research Methods Review

Updated: Dec 13, 2022

A methodological analysis of: do film soundtracks contain nonlinear analogues to influence emotion?


Daniel T. Blumstein, Richard Davitian and Peter D. Kaye conducted a study titled ‘Do film soundtracks contain nonlinear analogues to influence emotion?’. The aim of this study was to identify the use of nonlinear analogues across many of the world’s most ‘popular’ films and their respective genres in order to establish trends between the outlined film genres and the filmmakers use of nonlinearity as a means to influence human emotion.

Materials and Methods

The methodology used in this study is a form or content analysis, and theoretical review, (Columbia Public Health, 2019); “A research technique for the objective, systematic and quantitative description of the manifest content of communication.” (Berelson, 1952)

In order to gather data on nonlinearity between different genres of film, Blumstein et al. used popular film websites (,,,,,,,,,,,,, to Find out the ‘best’ films by genera (adventure, dramatic, horror, war), voted by the public. After finding the most popular 102 films across the aforementioned genres, Blumstein selected 30 seconds of an iconographic scene that best epitomized each film’s genre. These 102, 30-second scenes were extracted with ‘HandBreak v. 0.9.3’ (an open-source video transcoder) at a sample rate of 48 kHz, and a bit rate of 160 Kbps. The researchers then made spectrograms using ‘Raven Pro v. 1.3’ (software to visualise, measure, and analyse sounds), and ‘PRAAT v. 5.1.11’ (speech analysis software).

With all the film clips extracted, analysed, and visualised, the researchers had to decipher nonlinear sounds from the rich tapestry of audio contained in the films’ soundtracks. They found automatic feature extraction was impossible due to the soundtrack’s complexity, thus, they worked together to define quantifiable criteria and then applied those criteria to soundtracks until they were scored consistently.

Noise was scored as present when there were observed to be no defined spectral bands. Abrupt amplitude fluctuations were scored as present when the amplitude changed by more than 10% of the clip’s total mean amplitude in less than 500ms. Abrupt frequency fluctuations were scored as present when visible tonal frequency bands were seen to suddenly shift leading to a change in the overall frequency. Musical sidebands were scored by following musical frequency contours. Non-musical sidebands were scored when they observed bands of non-harmonic sound surrounded by a frequency band. Regarding screams, they scored male and female screams (when present), as noisy or tonal.

With the results of this analysis at hand, the researchers conducted Chi-squared (χ²) tests, a common test used by researchers to compare the distribution of a categorical variable to another (Plackett, 1983). In the case of this study, Chi-squared tests were used to discern if the proportion of films within their particular genres presented nonlinear analogues more or less likely than expected by chance.

What Type of Knowledge Was This Methodology Able to Produce?

The methodology in this study shows auditory scene analysis; a proposed model for the basis of auditory perception (Bregman, 1990). The data produced in the study is of a qualitative nature, outlining trends between the 102 tested films and their respective genres.

Compared to naturally produced nonlinear sounds caused by vocals, the simulated nonlinear sounds were hypothesised to be non-random and appeared to be specifically used to enhance the emotional impact of the tested scenes.

Looking at the musical aspects of the study, Blumstein et al. suggested that orchestras deliberately use a variety of nonlinear/noisy instruments (e.g., various gongs and cymbals) in order to create an emotional response. With specific deliberate use of nonlinearity and abrupt frequency changes used across dramatic, adventure, horror and war films, Blumstein et al.’s results suggest that filmmakers are selective with their sounds, and deliberately create nonlinear analogues in order to manipulate their audience’s emotional response.

Advantages and Limitations of the Methodology

A big advantage of their methodology is efficiency. 102 films were tested in this study, but instead of sampling the entire soundtrack for each film, Blumstein sampled a 30-second iconographic scene that best epitomized the film’s genre. Only processing 30 seconds of audio per film, this presumably saved a significant amount of time in the analysis stage of the study. Though efficient on time and able to capture what they consider the most relevant scenes in each film, this method left most of the films’ soundtracks unanalysed, and much of the data was missed. Perhaps this is a point for further study.

The method used by the researchers to detect the nonlinear analogues within the tested soundtracks neglects the ability to read the context behind the sound. For example, there may be use of non-linear audio, but if the context behind the sound is unconventional given its nonlinear sounding characteristic, then the use of that particular nonlinear sound may not be to manipulate our emotional responses in the way the study suggests, if at all.

Another disadvantage of the method was outlined in the study itself (p 751). Blumstein used popular internet film sites to find the most popular films per category for their testing, however this method of data collection had its flaws, Blumstein et al. stated “Because we relied on the popular vote, some films might better fit in different categories (e.g., Lawrence of Arabia might be more accurately adventure, Aliens might be more accurately under horror).” These few inaccurately categorised films may have negatively impacted the results of the testing and could likely be avoided had the researchers put more time into the manual aspect of the data collection.

Finally, there was no qualitative data collected for this study. As this study is primarily focused on human emotion, qualitative data would be very valuable. Without it, the precise effects of the nonlinear analogues are left to presumption. Qualitative data collection regarding the emotions elicited from an audience viewing the tested film clips could be an effective means to further indicate whether the researcher’s results are correct or not; perhaps this could be a point for further study.

The Study’s Form of Communication

Being that this study’s method of communication is text-based with a single image, I felt interpreting the data to be without some auditory examples to be a little difficult, and I come from an audio background. Someone without prior knowledge of audio jargon may struggle to understand the study. I believe a creative output in the form of a soundscape would be an effective way to communicate the study’s results. Sound can be used as an effective educational tool (Gershon, 2017) capable of demonstrating the study’s non-linear analogues in a format we are more familiar with perceiving them, not through academic text, but through listening. This way people might experience what the study is outlining intermittently with reading it. This could be a valuable output as emotional experiences are often more memorable than non-emotional experiences (Hopkins, 2007) This may also help people better understand the study if they are less academically inclined or know little about audio and its jargon.


Berelson, B. (1952) Content Analysis in Communication Research. New York: Free Press,

Blumstein, D., Davitian, R., Kaye, P. (2010). Do film soundtracks contain nonlinear analogues to influence emotion?. Biology Letters.

Bregman, A. (1990). Auditory Scene Analysis: The Perceptual Organization of Sound.

Columbia Public Health. (2019). Content Analysis. Columbia Public Health: Population Health Methods.

Gershon, W.S. (2017). Sound Curriculum. Sonic Studies in Educational Theory, Method, & Practice. pp 26-42.

Hopkins, J. (2007, October 7). Why Emotionally Charged Events Are So Memorable. ScienceDaily.

Plackett, R. L. (1983). Karl Pearson and the Chi-Squared Test. International Statistical Review. pp 59-72.

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