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Guntuku, Sharath Chandra; Scott, Michael; Lin, Weisi; Ghinea, Gheorghita (2015)
Publisher: IEEE
Languages: English
Types: Conference object
Subjects: cs, Multimedia, Personality, Affect, Culture, QoE
Affect is evoked through an intricate relationship between the characteristics of stimuli, individuals, and systems of perception. While affect is widely researched, few studies consider the combination of multimedia system characteristics and human factors together. As such, this paper explores the influence of personality (Five-Factor Model) and cultural traits (Hofstede Model) on the intensity of multimedia-evoked positive and negative affects (emotions). A set of 144 video sequences (from 12 short movie clips) were evaluated by 114 participants from a cross-cultural population, producing 1232 ratings. On this data, three multilevel regression models are compared: a baseline model that only considers system factors; an extended model that includes personality and culture; and an optimistic model in which each participant is modelled. An analysis shows that personal and cultural traits represent 5.6% of the variance in positive affect and 13.6% of the variance in negative affect. In addition, the affect-enjoyment correlation varied across the clips. This suggests that personality and culture play a key role in predicting the intensity of negative affect and whether or not it is enjoyed, but a more sophisticated set of predictors is needed to model positive affect with the same efficacy.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • [1] “Dove, unilever,” Accessed: 2015-04-20.
    • [2] Jacquelyn Smith, “The most unforgettable ad campaigns of 2013,” December 2013.
    • [3] Peter Noel Murray, “How emotions influence what we buy,” February 2013.
    • [4] Susan T Fiske, Amy JC Cuddy, and Peter Glick, “Universal dimensions of social cognition: Warmth and competence,” Trends in cognitive sciences, vol. 11, no. 2, pp. 77-83, 2007.
    • [5] Kathy A Winter and Nicholas A Kuiper, “Individual differences in the experience of emotions,” Clinical psychology review, vol. 17, no. 7, pp. 791-821, 1997.
    • [6] Wonhee Choe, Hyo-Sun Chun, Junhyug Noh, Seong-Deok Lee, and Byoung-Tak Zhang, “Estimating multiple evoked emotions from videos,” in Proceedings of Annual Meeting of the Cognitive Science Society, 2013, pp. 2046-2051.
    • [7] Gerald Matthews, Ian J Deary, and Martha C Whiteman, Personality traits, Cambridge University Press, 2003.
    • [8] Geert Hoftede, Gert Jan Hofstede, and Michael Minkov, Cultures and organizations: software of the mind: intercultural cooperation and its importance for survival, McGraw-Hill, 2010.
    • [9] Zhihong Zeng, Maja Pantic, Glenn I Roisman, and Thomas S Huang, “A survey of affect recognition methods: Audio, visual, and spontaneous expressions,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 31, no. 1, pp. 39-58, 2009.
    • [10] Luca Canini, Sergio Benini, and Riccardo Leonardi, “Affective recommendation of movies based on selected connotative features,” Circuits and Systems for Video Technology, IEEE Transactions on, vol. 23, no. 4, pp. 636-647, 2013.
    • [11] Subhabrata Bhattacharya, Behnaz Nojavanasghari, Tao Chen, Dong Liu, Shih-Fu Chang, and Mubarak Shah, “Towards a comprehensive computational model foraesthetic assessment of videos,” in Proceedings of the 21st ACM international conference on Multimedia. ACM, 2013, pp. 361-364.
    • [12] Cheng-Yu Wei, Nevenka Dimitrova, and Shih-Fu Chang, “Colormood analysis of films based on syntactic and psychological models,” in Multimedia and Expo, 2004. ICME'04. 2004 IEEE International Conference on. IEEE, 2004, vol. 2, pp. 831-834.
    • [13] Sergio Benini, Luca Canini, and Riccardo Leonardi, “A connotative space for supporting movie affective recommendation,” Multimedia, IEEE Transactions on, vol. 13, no. 6, pp. 1356-1370, 2011.
    • [14] Bjo¨rn Schuller, Michel Valstar, Florian Eyben, Gary McKeown, Roddy Cowie, and Maja Pantic, “Avec 2011-the first international audio/visual emotion challenge,” in Affective Computing and Intelligent Interaction, pp. 415-424. Springer, 2011.
    • [15] Rajitha Navarathna, Patrick Lucey, Peter Carr, Elizabeth Carter, Sridha Sridharan, and Iain Matthews, “Predicting movie ratings from audience behaviors,” in Applications of Computer Vision (WACV), 2014 IEEE Winter Conference on. IEEE, 2014, pp. 1058-1065.
    • [16] Mohammad Soleymani, Maja Pantic, and Thierry Pun, “Multimodal emotion recognition in response to videos,” Affective Computing, IEEE Transactions on, vol. 3, no. 2, pp. 211-223, 2012.
    • [17] Sander Koelstra, Christian Muhl, Mohammad Soleymani, Jong-Seok Lee, Ashkan Yazdani, Touradj Ebrahimi, Thierry Pun, Anton Nijholt, and Ioannis Patras, “Deap: A database for emotion analysis; using physiological signals,” Affective Computing, IEEE Transactions on, vol. 3, no. 1, pp. 18-31, 2012.
    • [18] Yoann Baveye, J-N Bettinelli, Emmanuel Dellandre´a, Liming Chen, and Christel Chamaret, “A large video database for computational models of induced emotion,” in Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on. IEEE, 2013, pp. 13- 18.
    • [19] Yu-Gang Jiang, Baohan Xu, and Xiangyang Xue, “Predicting emotions in user-generated videos,” in Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014.
    • [20] Jussi Tarvainen, Mats Sjoberg, Stina Westman, Jorma Laaksonen, and Pirkko Oittinen, “Content-based prediction of movie style, aesthetics and affect: Data set and baseline experiments,” 2014.
    • [21] Julien Fleureau, Philippe Guillotel, and Izabela Orlac, “Affective benchmarking of movies based on the physiological responses of a real audience,” in Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on. IEEE, 2013, pp. 73-78.
    • [22] Alexandre Schaefer, Fre´de´ric Nils, Xavier Sanchez, and Pierre Philippot, “Assessing the effectiveness of a large database of emotion-eliciting films: A new tool for emotion researchers,” Cognition and Emotion, vol. 24, no. 7, pp. 1153-1172, 2010.
    • [23] Mojtaba Khomami Abadi, Seyed Mostafa Kia, Ramanathan Subramanian, Paolo Avesani, and Nicu Sebe, “User-centric affective video tagging from meg and peripheral physiological responses,” in Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on. IEEE, 2013, pp. 582-587.
    • [24] Julia Wache, “The secret language of our body: Affect and personality recognition using physiological signals,” in Proceedings of the 16th International Conference on Multimodal Interaction. ACM, 2014, pp. 389-393.
    • [25] Geert Hofstede, “Dimensionalizing cultures: The hofstede model in context,” Online readings in psychology and culture, vol. 2, no. 1, pp. 8, 2011.
    • [26] Shlomo Argamon, Sushant Dhawle, Moshe Koppel, and James Pennebaker, “Lexical predictors of personality type,” 2005.
    • [27] Gelareh Mohammadi and Alessandro Vinciarelli, “Humans as feature extractors: combining prosody and personality perception for improved speaking style recognition,” in Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on. IEEE, 2011, pp. 363-366.
    • [28] Sharath Chandra Guntuku, Sujoy Roy, and Weisi Lin, “Personality modeling based image recommendation,” in MultiMedia Modeling. Springer, 2015, pp. 171-182.
    • [29] Jennifer Golbeck, Cristina Robles, and Karen Turner, “Predicting personality with social media,” in CHI'11 extended abstracts on human factors in computing systems. ACM, 2011, pp. 253-262.
    • [30] Alessandro Vinciarelli and Gelareh Mohammadi, “A survey of personality computing,” 2014.
    • [31] Saham Barza and Mehran Memari, “Movie genre preference and culture,” Procedia-Social and Behavioral Sciences, vol. 98, pp. 363- 368, 2014.
    • [32] C Samuel Craig, William H Greene, and Susan P Douglas, “Culture matters: consumer acceptance of us films in foreign markets,” Journal of International Marketing, vol. 13, no. 4, pp. 80-103, 2005.
    • [33] Geert Hofstede, Gert Jan Hofstede, Michael Minkov, and Henk Vinken, “Values survey module 2013,” URL: http://www.geerthofstede.nl/vsm2013, 2013.
    • [34] Samuel D Gosling, Peter J Rentfrow, and William B Swann, “A very brief measure of the big-five personality domains,” Journal of Research in personality, vol. 37, no. 6, pp. 504-528, 2003.
    • [35] Gregory J McHugo, Craig A Smith, and John T Lanzetta, “The structure of self-reports of emotional responses to film segments,” Motivation and Emotion, vol. 6, no. 4, pp. 365-385, 1982.
    • [36] Lewis R Goldberg, “An alternative” description of personality”: the bigfive factor structure.,” Journal of personality and social psychology, vol. 59, no. 6, pp. 1216, 1990.
    • [37] George Ghinea and Johnson P Thomas, “Qos impact on user perception and understanding of multimedia video clips,” in Proceedings of the sixth ACM international conference on Multimedia. ACM, 1998, pp. 49-54.
    • [38] Nick Yeung and Alan G Sanfey, “Independent coding of reward magnitude and valence in the human brain,” The Journal of Neuroscience, vol. 24, no. 28, pp. 6258-6264, 2004.
    • [39] Luiz Pessoa, “On the relationship between emotion and cognition,” Nature Reviews Neuroscience, vol. 9, no. 2, pp. 148-158, 2008.
    • [40] Carroll E Izard, Deborah Z Libero, Priscilla Putnam, and O Maurice Haynes, “Stability of emotion experiences and their relations to traits of personality.,” Journal of personality and social psychology, vol. 64, no. 5, pp. 847, 1993.
    • [41] Roel Bosker and Tom Snijders, “Multilevel analysis: An introduction to basic and advanced multilevel modeling, 2nd ed,” New York, 2012.
    • [42] Maria Teresa Soto Sanfiel, Laura Aymerich Franch, F Xavier Ribes Guardia, and J Reinaldo Martinez Fernandez, “Influence of interactivity on emotions and enjoyment during consumption of audiovisual fictions,” International Journal of Arts and Technology, vol. 4, no. 1, pp. 111-129, 2011.
    • [43] Randy J Larsen and Timothy Ketelaar, “Personality and susceptibility to positive and negative emotional states.,” Journal of personality and social psychology, vol. 61, no. 1, pp. 132, 1991.
    • [44] Ed Diener, Shigehiro Oishi, and Richard E Lucas, “Personality, culture, and subjective well-being: Emotional and cognitive evaluations of life,” Annual review of psychology, vol. 54, no. 1, pp. 403-425, 2003.
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