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Cultural Differences Demonstrated by TV Series: A Cross-Cultural Analysis of Multimodal Features

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Cross-Cultural Design. Experience and Product Design Across Cultures (HCII 2021)

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Abstract

TV series is one of the most popular entertainment media globally and is a representation of popular culture. It reflects a specific group's daily life culture and certain characteristics of society such as social norms. This paper improved and verified a new cross-cultural analysis method by analyzing facial expressions, original text features and audio features extracted from TV series datasets. We adopted the TV series from America, Japan, and Korea and extracted the textual features from the original text database rather than the translated one. We added the emotional frequency of text and part-of-speech frequency in the text modality. The emotional frequency of facial expressions and text were combined to explore the relation between nonverbal and verbal expressions. In addition, the feasibility of using audio features to further extend the new cross-cultural analysis method were explored. Overall, 1656 features extracted from 90 TV dramas were analyzed, including 42 facial features, 32 text features and 1582 audio features. The statistical results of the feature comparisons revealed the similarities and differences between the three countries and agreed with many existing theories, which resulted in traditional cross-cultural studies. Machine learning models of random forest and support vector machine were used for feature selection and classification to enhance the understanding of important features and conduct country classification.

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References

  1. Tylor, E.B.: Primitive culture: researches into the development of mythology, philosophy, religion, art, and custom. J. Murray 1, 1 (1871)

    Google Scholar 

  2. Rohner, R.P.: Toward a conception of culture for cross-cultural psycholog. J. Cross-Cult. Psychol. 15(2), 111–138 (1984)

    Article  Google Scholar 

  3. Ilesanmi, O.O.: What is cross-cultural research? Int. J. Psychol. Stud. 1(2), 82 (2009)

    Article  Google Scholar 

  4. Black, J.S., Mendenhall, M.: Cross-cultural training effectiveness: a review and a theoretical framework for future research. Acad. Manag. Rev. 15(1), 113–136 (1990)

    Article  Google Scholar 

  5. Hofstede, G.: Culture’s Consequences: International Differences in Work-Related Values. Sage, Beverly Hills (1980)

    Google Scholar 

  6. Chang, L.: Socialization and social adjustment of single children in China. Int. J. Psychol. 39, 390 (2004)

    Google Scholar 

  7. Li, H.Z.: Culture and gaze direction in conversation. RASK 20, 3–26 (2004)

    Google Scholar 

  8. Ji, L.J., Nisbett, R.E., Su, Y.J.: Culture, change and prediction. Psychol. Sci. 12, 450–456 (2001)

    Article  Google Scholar 

  9. Sternberg, R.J.: Culture and intelligence. Am. Psychol. 59, 325–338 (2004)

    Article  Google Scholar 

  10. Mundy-Castle, A.C.: Social and technological intelligence in Western and non-Western cultures. Universitas Univ. Ghana Legos 4, 42–45 (1974)

    Google Scholar 

  11. Smith, P.B., Bond, M.H., Kağitçibasi, C.: Understanding Social Psychology Across Cultures. SAGE Publications Ltd. (2006)

    Google Scholar 

  12. Treisman, A.: The effects of redundancy and familiarity on translating and repeating back a foreign and a native language. Br. J. Psychol. 56, 369–379 (1965)

    Article  Google Scholar 

  13. Nida, E.: Toward a science of translation. E, J. Brill, Leiden, Netherlands (1964)

    Google Scholar 

  14. Miller, G.A., Beebe-Center, J.G.: Some psychological methods for evaluating the quality of translations. Mech. Transl. 3, 73–80 (1956)

    Google Scholar 

  15. Williams, R.: Keywords. Fontana, London (1983)

    Google Scholar 

  16. Storey, J.: Cultural Theory and Popular Culture: An Introduction, 8th edn., p. 2. Routledge (2018)

    Google Scholar 

  17. Weber, E., Ames, D., Blais, A.-R.: “How do i choose thee? Let me count the ways”: a textual analysis of similarities and differences in modes of decision-making in China and the United States. Manag. Organ. Rev. 1(01), 87–118 (2005)

    Article  Google Scholar 

  18. Hatzithomas, L., Zotos, Y., Boutsouki, C.: Humor and cultural values in print advertising: a cross-cultural study. Int. Mark. Rev. 28(1), 57–80 (2011)

    Article  Google Scholar 

  19. Xu, X.: A new cross-cultural research method based on multimodal features. [I], pp. 6–12. Tsinghua University, Beijing (2018)

    Google Scholar 

  20. Kashima, Y., Kashima, E.: Culture and language: the case of cultural dimensions and personal pronoun use. J. Cross-Cult. Psychol. 29, 461–468 (1998)

    Article  Google Scholar 

  21. Semin, G.R., Gorts, C.A., Nandram, S., Semin-Goossens, A.: Cultural perspectives on the linguistic representation of emotion and emotion events. Cogn. Emot. 16, 11–28 (2002)

    Article  Google Scholar 

  22. Bostanov, V., Kotchoubey, B.: Recognition of affective prosody: continuous wavelet measures of event-related brain potentials to emotional exclamations. Psychophysiology 41(2), 259–268 (2004)

    Article  Google Scholar 

  23. Trompenaars, F., Hampden-Turner, C.: Riding the waves of culture: understanding diversity in global business. Nicholas Brealey International (2011)

    Google Scholar 

  24. Smee, A., Brennan, M., Hoek, J., Macpherson, T.: A test of procedures for collecting survey data using electronic mail. In: Refereed WIP Paper, Australian and NewZealand Marketing Academy (ANZMAC) Conference Proceedings, 30 November– 2 December, pp. 2447–2452. University of Otago, Dunedin, New Zealand (1998)

    Google Scholar 

  25. Comley, P.: The Use of the Internet as a Data Collection Method, Media Futures Report. Henley Centre, London (1996)

    Google Scholar 

  26. Tanzer, N., Sim, C.Q.E., Spielberger, C.D.: Experience and expression of anger in a Chinese society: the case of Singapore. In: Spielberger, C.D., Sarason, I.G., et al. (eds.) Stress and Emotion: Anxiety, Anger and Curiosity, vol. 16, pp. 51–65. Taylor & Francis, Washington, DC (1996)

    Google Scholar 

  27. Smith, P.B., Peterson, M.F., Schwartz, S.H., et al.: Cultural values, sources of guidance and their relevance to managerial behavior: A 47-nation study. J. Cross-Cult. Psychol. 33, 188–208 (2002)

    Article  Google Scholar 

  28. Israel, J., Tajfel, H.: Context of Social Psychology: A Critical Assessment. Academic Press, London (1972)

    Google Scholar 

  29. Moscovici, S.: Society and theory in social psychology. In: Israel, J., Tajfel, H. (eds.) The Context of Social Psychology: A Critical Assessment, pp. 17–68. Academic Press, London (1972)

    Google Scholar 

  30. Matsumoto, D.: More evidence for the universality of a contempt expression. Motiv. Emot. 16, 363–368 (1992)

    Article  Google Scholar 

  31. Ekman, P.: Universals and cultural differences in facial expressions of emotion. In: Cole, J. (ed.) Nebraska Symposium on Motivation, vol. 19, pp. 207–282. University of Nebraska Press, Lincoln (1972)

    Google Scholar 

  32. Ekman, P., Friesen, W.V., O'Sullivan, M., et al.: Universals and cultural differences in the judgment of facial expressions of emotion. J. Pers. Soc. Psychol. S3, 712-71 (1987)

    Google Scholar 

  33. Koopmann-Holm, B., Matsumoto, D.: Values and display rules for specific Emotions. J. Cross-Cult. Psychol. 42(3), 355–371 (2011)

    Article  Google Scholar 

  34. Matsumoto, D., Kupperbusch, C.: Idiocentric and allocentric differences in emotional expression, experience and the coherence between expression and experience. Asian J. Soc. Psychol. 4, 113–131 (2001)

    Article  Google Scholar 

  35. Agnew, C., Van Lange, P., Rusbult, C., Langston, C., Insko, C.A.: Cognitive interdependence: Commitment and the mental representation of close relationships. J. Pers. Soc. Psychol. 74, 939–954 (1998)

    Article  Google Scholar 

  36. Fitzsimons, G.M., Kay, A.C.: Language and interpersonal cognition: causal effects of variations in pronoun usage on perceptions of closeness. Pers. Soc. Psychol. Bull. 30(5), 547–557 (2004)

    Article  Google Scholar 

  37. Scherer, K.R., Banse, R., Wallbott, H.G.: Emotion inferences from vocal expression correlate across languages and cultures. J. Cross-Cult. Psychol. 32(1), 76–92 (2001)

    Article  Google Scholar 

  38. Thompson, W.F., Balkwill, L.L.: Decoding speech prosody in five languages. Semiotica 158, 407–424 (2006)

    Google Scholar 

  39. Besson, M., Magne, C., Schön, D.: Emotional prosody: sex differences in sensitivity to speech melody. Trends Cogn. Sci. 6(10), 405–407 (2002)

    Article  Google Scholar 

  40. Poriaa, S., Cambriac, E., Bajpaib, R., Hussaina, A.: A review of affective computing: from unimodal analysis to multimodal fusion. Inf. Fusion 37, 98–125 (2017)

    Article  Google Scholar 

  41. Xu, C., Cetintas, S., Lee, K., Li, L.: Visual Sentiment Prediction with Deep Convolutional Neural Networks (2014)

    Google Scholar 

  42. Poria, S., Chaturvedi, I., Cambria, E., Hussain, A.: Convolutional MKL based multimodal emotion recognition and sentiment analysis. In: Proceedings of ICDM, Barcelona (2016)

    Google Scholar 

  43. Mishne, G., et al.: Experiments with mood classification in blog posts. In: Proceedings of ACM SIGIR 2005 Workshop on Stylistic Analysis of Text for Information Access 19, pp. 321–327. Citeseer (2005)

    Google Scholar 

  44. Eyben, F., Wollmer, M., Schuller, B.: Openear—introducing the Munich open-source emotion and affect recognition toolkit. In: 2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops, pp. 1–6. IEEE (2009)

    Google Scholar 

  45. Anand, N., Verma, P.: Convoluted feelings convolutional and recurrent nets for detecting emotion from audio data. Technical report, Stanford University (2015)

    Google Scholar 

  46. Pérez-Rosas, V., Mihalcea, R., Morency, L.: Utterance-level multimodal sentiment analysis. In: ACL, no. 1, pp. 973–982 (2013)

    Google Scholar 

  47. Poria, S., Cambria, E., Gelbukh, A.: Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis. In: Proceedings of EMNLP, pp. 2539–2544 (2015)

    Google Scholar 

  48. Morency, L., Mihalcea, R., Doshi, P.: Towards multimodal sentiment analysis: harvesting opinions from the web. In: Proceedings of the 13th International Conference on Multimodal Interfaces, pp. 169–176. ACM (2011)

    Google Scholar 

  49. Poria, S., Cambria, E., Howard, N., Huang, G.B., Hussain, A.: Fusing audio, visual and textual clues for sentiment analysis from multimodal content. Neurocomputing 174, 50–59 (2016)

    Article  Google Scholar 

  50. Weninger, F., Knaup, T., Schuller, B., Sun, C., Wollmer, M., Sagae, K.: Youtube movie reviews: sentiment analysis in an audio-visual context. Intell. Syst. IEEE 28(3), 46–53 (2013)

    Article  Google Scholar 

  51. Eyben, F, Wollmer, M., Schuller, B.: OpenSMILE-The Munich versatile and fast open-source audio feature extractor. In: Proceedings of ACM Multimedia (MM), Florence, Italy, pp. 1459–1462 (2010)

    Google Scholar 

  52. Cambria, E., Poria, S., Hazarika, D., Kwok, K.: SenticNet 5: discovering conceptual primitives for sentiment analysis by means of context embeddings. In: AAAI, pp. 1795–1802 (2018)

    Google Scholar 

  53. Chen, S., Hsu, C., Kuo, C., Ting-Hao, T., Huang, H., Ku, L.: Emotionlines: an emotion corpus of multi-party conversations (2018). arXiv preprint arXiv:1802.08379

  54. Poria, S., Hazarika, D., Majumder, N., Naik, G., Cambria, E., Mihalcea, R.: MELD: a multimodal multi-party dataset for emotion recognition in conversation. In: ACL (2019)

    Google Scholar 

  55. Bird, S., Loper, E., Klein, E.: Natural Language Processing with Python. O’Reilly Media Inc. (2009)

    Google Scholar 

  56. Kudo, T.: Mecab: yet another part-of-speech and morphological analyzer (2006). https://mecab.sourceforge.net

  57. Kitayama, S., Markus, H.R., Kurokawa, M.: Culture, emotion, and well-being: good feelings in japan and the United States. Cogn. Emot. 14(1), 93–124 (2000)

    Article  Google Scholar 

  58. Markus, H.R., Kitayama, S.: Culture and the self: implications for cognition, emotion, and motivation. Psychol. Rev. 98(2), 224 (1991)

    Article  Google Scholar 

  59. Fiske, A.P., Kitayama, S., Markus, H.R., Nisbett, R.E.: The cultural matrix of social psychology. In: Gilbert, D.T., Fiske, S.T., Lindzey, G. (eds.) The Handbook of Social Psychology, vol. 2, 4th edn., pp. 915–981. McGraw Hill, New York (1998)

    Google Scholar 

  60. Park, H.S., Levine, T.R.: The theory of reasoned action and selfconstrual: evidence from three cultures. Commun. Monogr. 66(3), 199–218 (1999)

    Article  Google Scholar 

  61. Singelis, T.M., Sharkey, W.F.: Culture, self-construal, and embarrassability. J. Cross-Cult. Psychol. 26(6), 622–644 (1995)

    Article  Google Scholar 

  62. Hofstede, G.: Culture’s Consequences: COMPARING values, Behaviours, Institutions and Organizations Across Nations, 2nd edn. Sage, Thousand Oaks (2001)

    Google Scholar 

  63. Hall, E.T.: Beyond Culture. Anchor Books/Doubleday, Garden City (1976)

    Google Scholar 

  64. Abramson, P.R., Pinkerton, S.D.: Sexual Nature/Sexual Culture. [S.l.]: University of Chicago Press (1995)

    Google Scholar 

  65. Soh, C.S.: The Comfort Women: Sexual Violence and Postcolonial Memory in Korea and Japan. [S.l.]: University of Chicago Press (2008)

    Google Scholar 

  66. Robertson, J.: Takarazuka: Sexual Politics and Popular Culture in Modern Japan. [S.l.]: University of California Press (1998)

    Google Scholar 

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Correspondence to Pei-Luen Patrick Rau .

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Lai, X., Qie, N., Rau, PL.P. (2021). Cultural Differences Demonstrated by TV Series: A Cross-Cultural Analysis of Multimodal Features. In: Rau, PL.P. (eds) Cross-Cultural Design. Experience and Product Design Across Cultures. HCII 2021. Lecture Notes in Computer Science(), vol 12771. Springer, Cham. https://doi.org/10.1007/978-3-030-77074-7_34

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  • DOI: https://doi.org/10.1007/978-3-030-77074-7_34

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