Achterberg, P., & Houtman, D. (2006). Why do so many people vote ‘unnaturally’? A cultural explanation for voting behaviour. European Journal of Political Research, 45(1), 75-92. doi: 10.1111/j.1475-6765.2005.00291.x
Bond, R. M., Fariss, C. J., Jones, J. J., Kramer, A. D. I., Marlow, C., Settle, J. E., & Fowler, J. H. (2012). A 61-million-person experiment in social influence and political mobilization. Nature, 489(7415), 295-298. doi: 10.1038/nature11421
Brennan, J. (2012). The Ethics of Voting: Princeton University Press.
Bruter, M., & Harrison, S. (2017). Understanding the emotional act of voting. Nature Human Behaviour, 1(0024), 1-3.
Cammaerts, B., Bruter, M., Banaji, S., Harrison, S., & Anstead, N. (2016). Youth participation in democratic life: Stories of hope and disillusion: Springer.
Carroll, N. (2003). The philosophy of horror: Or, paradoxes of the heart: Routledge.
Chatterjee, A., Mitrović, M., & Fortunato, S. (2013). Universality in voting behavior: an empirical analysis. Scientific Reports, 3(1), 1049. doi: 10.1038/srep01049
Crull, R., Miller, B., Kenney, A., & Martin, T. (2007). Social network-enabled interactive media player: Google Patents.
Dovey, J., & Rose, M. (2012). We're happy and we know it: Documentary, data, montage. Studies in Documentary Film, 6(2), 159-173. doi: 10.1386/sdf.6.2.159_1
Downs, A. (1957). An economic theory of political action in a democracy. Journal of political economy, 65(2), 135-150.
Druckman, J. N., & McGrath, M. C. (2019). The evidence for motivated reasoning in climate change preference formation. Nature Climate Change, 9(2), 111-119. doi: 10.1038/s41558-018-0360-1
Esser, A. (2010). Television formats: Primetime staple, global market. Popular Communication, 8(4), 273-292.
FCC. (2019). Federal Communications Commission: Implementation of the Consolidated Appropriations Act of 2019; Report on Television Ratings and The Oversight Monitoring Board. https://docs.fcc.gov/public/attachments/DA-19-423A1.pdf.
Fischer, M., Ekenel, H. K., & Stiefelhagen, R. (2011). Person re-identification in tv series using robust face recognition and user feedback. Multimedia Tools and Applications, 55(1), 83-104.
Galesic, M., Bruine de Bruin, W., Dumas, M., Kapteyn, A., Darling, J. E., & Meijer, E. (2018). Asking about social circles improves election predictions. Nature Human Behaviour, 2(3), 187-193. doi: 10.1038/s41562-018-0302-y
Gallup. (2019). Abortion Trends by Party Identifcation (Gallup, 2019);.
Galton, F. (1907). Vox populi (the wisdom of crowds). Nature, 75(7), 450-451.
Garcφa, A. N. (2016). Emotions in Contemporary TV Series: Springer.
Ginsburgh, V., & Weyers, S. (1999). On the perceived quality of movies. Journal of Cultural Economics, 23(4), 269-283.
Greenberg, B. S., Sherry, J., Lachlan, K., Lucas, K., & Holmstrom, A. (2010). Orientations to Video Games Among Gender and Age Groups. Simulation & Gaming, 41(2), 238-259. doi: 10.1177/1046878108319930
Guess, A., Nyhan, B., & Reifler, J. (2018). Selective exposure to misinformation: Evidence from the consumption of fake news during the 2016 US presidential campaign. European Research Council, 9.
Gustafson, A., Rosenthal, S. A., Ballew, M. T., Goldberg, M. H., Bergquist, P., Kotcher, J. E., . . . Leiserowitz, A. (2019). The development of partisan polarization over the Green New Deal. Nature Climate Change, 9(12), 940-944. doi: 10.1038/s41558-019-0621-7
Haan, M. A., Dijkstra, S. G., & Dijkstra, P. T. (2005). Expert judgment versus public opinion–evidence from the Eurovision song contest. Journal of Cultural Economics, 29(1), 59-78.
Haidt, J., McCauley, C., & Rozin, P. (1994). Individual differences in sensitivity to disgust: A scale sampling seven domains of disgust elicitors. Personality and Individual differences, 16(5), 701-713.
Hill, A. (2014). Reality tv: Routledge.
Hills, T. T., Proto, E., Sgroi, D., & Seresinhe, C. I. (2019). Historical analysis of national subjective wellbeing using millions of digitized books. Nature Human Behaviour. doi: 10.1038/s41562-019-0750-z
Hoekstra, S. J., Harris, R. J., & Helmick, A. L. (1999). Autobiographical memories about the experience of seeing frightening movies in childhood. Media Psychology, 1(2), 117-140.
Jakob, N., Weber, S. H., Müller, M. C., & Gurevych, I. (2009). Beyond the stars: exploiting free-text user reviews to improve the accuracy of movie recommendations. Paper presented at the Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion.
Ji, S., & Waterman, D. (2010). Production technology and trends in movie content: An empirical study: Working Paper, Department of Telecommunications, Indiana University ….
Koenker, R. (2005). Quantile regression: Cambridge university press.
Koh, N. S., Hu, N., & Clemons, E. K. (2010). Do online reviews reflect a product’s true perceived quality? An investigation of online movie reviews across cultures. Electronic Commerce Research and Applications, 9(5), 374-385. doi: https://doi.org/10.1016/j.elerap.2010.04.001
Kostakos, V. (2009). Is the crowd's wisdom biased? A quantitative analysis of three online communities. Paper presented at the 2009 International Conference on Computational Science and Engineering.
Krutnik, F., & Neale, S. (2006). Popular film and television comedy: Routledge.
Lago, I. (2019). A Research Agenda in Elections and Voting Behavior in a Global and Changing World. Frontiers in Political Science, 1, 1.
Leduc, L. (2002). Opinion change and voting behaviour in referendums. European Journal of Political Research, 41(6), 711-732. doi: 10.1111/1475-6765.00027
Liu, C.-L., Hsaio, W.-H., Lee, C.-H., Lu, G.-C., & Jou, E. (2011). Movie rating and review summarization in mobile environment. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 42(3), 397-407.
McMurria, J. (2008). Desperate Citizens and Good Samaritans:Neoliberalism and Makeover Reality TV. Television & New Media, 9(4), 305-332. doi: 10.1177/1527476408315115
Mehr, S. A., Singh, M., Knox, D., Ketter, D. M., Pickens-Jones, D., Atwood, S., . . . Glowacki, L. (2019). Universality and diversity in human song. Science, 366(6468), eaax0868. doi: 10.1126/science.aax0868
Moustakas, A., Daliakopoulos, I. N., & Benton, T. G. (2019). Data-driven competitive facilitative tree interactions and their implications on nature-based solutions. Science of The Total Environment, 651, 2269-2280. doi: https://doi.org/10.1016/j.scitotenv.2018.09.349
Moustakas, A., & Evans, M. R. (2016). Regional and temporal characteristics of bovine tuberculosis of cattle in Great Britain. Stochastic Environmental Research and Risk Assessment, 30(3), 989-1003. doi: 10.1007/s00477-015-1140-3
Moustakas, A., & Katsanevakis, S. (2018). Editorial: Data Mining and Methods for Early Detection, Horizon Scanning, Modelling, and Risk Assessment of Invasive Species. Frontiers in Applied Mathematics and Statistics, 4(5). doi: 10.3389/fams.2018.00005
Ng, B. D., & Wiemer-Hastings, P. (2005). Addiction to the internet and online gaming. Cyberpsychology & behavior, 8(2), 110-113.
Nielsen, R. K. L., & Grabarczyk, P. (2019). Are Loot Boxes Gambling? Random reward mechanisms in video games. Transactions of the Digital Games Research Association, 4(3).
Nisbet, M. C., & Aufderheide, P. (2009). Documentary Film: Towards a Research Agenda on Forms, Functions, and Impacts. Mass Communication and Society, 12(4), 450-456. doi: 10.1080/15205430903276863
Petrova, E., Gross, N., & Insights, G. (2017). 4 reasons people watch gaming content on youtube.
Pinheiro, J. C., & Bates, D. M. (2000). Mixed-Effects Models in S and S-PLUS. New York: Springer Verlag.
Prelec, D., Seung, H. S., & McCoy, J. (2017). A solution to the single-question crowd wisdom problem. Nature, 541(7638), 532-535. doi: 10.1038/nature21054
PTC. (2019). Parents Television Council: A Decade of Deceit: How TV Content Ratings Have Failed Families. https://go.parentstv.org/decades-report/documents/Decades-Report.pdf.
Ramos, M., Calvão, A. M., & Anteneodo, C. (2015). Statistical Patterns in Movie Rating Behavior. Public Library of Science One, 10(8), e0136083. doi: 10.1371/journal.pone.0136083
Raney, A. A. (2009). The effects of viewing televised sports. The SAGE handbook of media processes and effects, 439-453.
Redfern, N. (2012). Genre trends at the US box office, 1991 to 2010. European Journal of American Culture, 31(2), 145-167.
Ruby, J. (1977). The image mirrored: Reflexivity and the documentary film. Journal of the University Film Association, 29(4), 3-11.
Russell, D. E. (1980). Pornography and violence: What does the new research say. Take back the night: Women on pornography, 218-238.
Scott, A. J., & Knott, M. (1974). A cluster analysis method for grouping means in the analysis of variance. Biometrics, 507-512.
Simonton, D. K. (2002). Collaborative aesthetics in the feature film: Cinematic components predicting the differential impact of 2,323 Oscar-nominated movies. Empirical Studies of the Arts, 20(2), 115-125.
Smith, T., Obrist, M., & Wright, P. (2013). Live-streaming changes the (video) game. Paper presented at the Proceedings of the 11th european conference on Interactive TV and video.
Soroka, S., Young, L., & Balmas, M. (2015). Bad news or mad news? Sentiment scoring of negativity, fear, and anger in news content. The ANNALS of the American Academy of Political and Social Science, 659(1), 108-121.
Squire, K. (2008). Open-ended video games: A model for developing learning for the interactive age. The ecology of games: Connecting youth, games, and learning, 167-198.
Squire, K. (2011). Video games and learning. Teaching and participatory culture in the digital age.
Stewart, A. J., Mosleh, M., Diakonova, M., Arechar, A. A., Rand, D. G., & Plotkin, J. B. (2019). Information gerrymandering and undemocratic decisions. Nature, 573(7772), 117-121. doi: 10.1038/s41586-019-1507-6
Sunstein, C. R. (2006). Infotopia: How many minds produce knowledge: Oxford University Press.
Surowiecki, J. (2005). The wisdom of crowds: Anchor.
Tapaswi, M., Bäuml, M., & Stiefelhagen, R. (2012). “Knock! Knock! Who is it?” probabilistic person identification in TV-series. Paper presented at the 2012 IEEE Conference on Computer Vision and Pattern Recognition.
Thompson, K. M., & Yokota, F. (2004). Violence, sex and profanity in films: correlation of movie ratings with content. MedGenMed : Medscape general medicine, 6(3), 3-3.
Tian, Q., & Hoffner, C. A. (2010). Parasocial Interaction With Liked, Neutral, and Disliked Characters on a Popular TV Series. Mass Communication and Society, 13(3), 250-269. doi: 10.1080/15205430903296051
Turel, O., & Bechara, A. (2019). Little video-gaming in adolescents can be protective, but too much is associated with increased substance use. Substance use & misuse, 54(3), 384-395.
Williams, D., Martins, N., Consalvo, M., & Ivory, J. D. (2009). The virtual census: representations of gender, race and age in video games. New Media & Society, 11(5), 815-834. doi: 10.1177/1461444809105354
Winstead, A. F. (2011). The Devil Made Me Do It! The Devil in 1960s–1970s Horror Film. Vader, Voldemort, and Other Villains: Essays on Evil in Popular Media, 28-45.
Wu, F., & Huberman, B. A. (2008). How public opinion forms. Paper presented at the International Workshop on Internet and Network Economics.
You, C., Lin, D. K. J., & Young, S. S. (2018). Time series smoother for effect detection. Public Library of Science One, 13(4), e0195360. doi: 10.1371/journal.pone.0195360