Araştırma Makalesi
BibTex RIS Kaynak Göster

Emotion Map of Dialogues in Old Age Themed Cinema Films

Yıl 2024, Sayı: 66, 1 - 20, 26.03.2024
https://doi.org/10.47998/ikad.1284248

Öz

The effects of media messages on individuals' perceptions have been theorized through various approaches. Gerbner's Cultivation Theory is one of them. The theory argues that television significantly affects individuals' perceptions of social reality. Based on the impact of media messages on individuals' perceptions, the idea of old age produced through movies shapes our understanding of old age in real life. On the other hand, emotions play a significant role in media messages transforming the audience. From his point of view, in order to develop a different perspective on how the idea of old age constructed through movies shapes our understanding of old age in real life, this study investigated the emotional structure in the dialogues of films about old age. To this end, using the text mining method, an emotional analysis was carried out in the dialogues of all old age-themed films produced over one century. The results are interpreted with a descriptive approach from a historical perspective and within the framework of country cinemas. Our study is expected to set an example for text-mining research in cinema and offer an alternative view to the discussions on the phenomenon of old age in cinema.

Proje Numarası

-

Kaynakça

  • Baek, K. (2018). The geographic dimension of citizenship in digital activism: Analysis of the relationships among local and global citizenship, the use of social networking sites, and participation in the occupy movement. American Behavioral Scientist, 62(8), 1138-1156.
  • Bryant, J., & Miron, D. (2004). Theory and research in mass communication. Journal of Communication.
  • Casado-Gual, N. (2020). Ageing and romance on the big screen: the ‘silvering romantic comedy’ Elsa & Fred. Ageing & Society, 40(10), 2257-2265.
  • Chang, B. L., Chang, A. F., & Shen, Y. (1984). Attitudes toward aging in the United States and Taiwan. Journal of Comparative Family Studies, 15(1), 109-130.
  • Chivers, S. (2011). The silvering screen: Old age and disability in cinema. University of Toronto Press.
  • Cohen-Shalev, A. (2009). Visions of aging: Images of the elderly in film. Apollo Books.
  • Cowgill, D. O., & Holmes, L. D. (1972). Summary and conclusions: The theory in review. Aging and Modernization, 305-323.
  • Crosthwaite, A. (2014). “Visions of Aging in U.S. Cinema.” L’invecchiamento-Aging, 10 (3): 27–32.
  • Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017, May). Automated hate speech detection and the problem of offensive language. İçinde Proceedings of the international AAAI conference on web and social media, 11 (1), 512-515.
  • Dolan, J. (2018). Contemporary cinema and 'old age': Gender and the silvering of stardom. Springer Press.
  • Edström, M. (2018). Visibility patterns of gendered ageism in the media buzz: A study of the representation of gender and age over three decades. Feminist Media Studies, 18 (1), 77-93.
  • Ekman, P. (2000). Basic emotions. In Dalgleish, T. & Power, M. (Edt.). Handbook of Cognition and Emotion, 98(45-60), 16, John Wiley & Sons.
  • Ekman, P. (1992a). An argument for basic emotions. Cognition & Emotion, 6(3-4), 169-200.
  • Ekman, P. (1992b). Are there basic emotions? Psychological Review, 99(3), 550–553.
  • Ekman, P. & Cordaro, D. (2011). What is meant by calling emotions basic? Emotion Review: Journal of the International Society for Research on Emotion 3(4), 364–370.
  • Ekman, P. & Friesen, W. V. (1982). Felt, false, and miserable smiles. Journal of Nonverbal Behavior, 6 (4), 238–52.
  • Fernández-Gavilanes, M., Juncal-Martínez, J., García-Méndez, S., Costa-Montenegro, E., & González-Castano, F. J. (2018). Creating emoji lexica from unsupervised sentiment analysis of their descriptions. Expert Systems with Applications, 103, 74-91.
  • Gerbner, G. (1977). Television: The new state religion? Review of General Semantics, 34 (2), 145–50.
  • Gerbner, G. & Gross, L. (1976). Living with television: The violence profile, Journal of Communication, 26 (2), pp. 172–199
  • Ge, Y., Qiu, J., Liu, Z., Gu, W., & Xu, L. (2020). Beyond negative and positive: Exploring the effects of emotions in social media during the stock market crash. Information Processing & Management, 57(4), 102218.
  • Greenberg, L. S. (2004). Emotion–focused therapy. Clinical Psychology & Psychotherapy: An International Journal of Theory & Practice, 11(1), 3-16.
  • Gross, J. J., & Levenson, R. W. (1995). Emotion elicitation using films. Cognition & Emotion, 9(1), 87-108.
  • Gruebner, O., Lowe, S. R., Sykora, M., Shankardass, K., Subramanian, S. V., & Galea, S. (2017). A novel surveillance approach for disaster mental health. PLoS One, 12(7), 0181233.
  • Harb, J. G., Ebeling, R., & Becker, K. (2020). A framework to analyze the emotional reactions to mass violent events on Twitter and influential factors. Information Processing & Management, 57(6), 102372.
  • Hofstede, G. (1984). The cultural relativity of the quality of life concept. Academy of Management Review, 9(3), 389-398.
  • Hou, L. (2020). Rewriting “the personal is political”: young women's digital activism and new feminist politics in China. Inter-Asia Cultural Studies, 21(3), 337-355.
  • Hungwe, K. N. (2005). Narrative and ideology: 50 years of film-making in Zimbabwe. Media, Culture & Society, 27(1), 83-99.
  • Izard, C. E. (2007). Basic emotions, natural kinds, emotion schemas, and a new paradigm. Perspectives on Psychological Science, 2(3), 260-280.
  • Kanavos, A., Perikos, I., Hatzilygeroudis, I., & Tsakalidis, A. (2018). Emotional community detection in social networks. Computers & Electrical Engineering, 65, 449-460.
  • Kozloff, S. (2000). Overhearing film dialogue. University of California Press.
  • Kracauer, S. (1997). Theory of film: The redemption of physical reality. Princeton University Press.
  • Kubrak, T. (2020). Impact of films: Changes in young people’s attitudes after watching a movie. Behavioral Sciences, 10(5), 86.
  • Levy, B. R., & Myers, L. M. (2004). Preventive health behaviors influenced by self-perceptions of aging. Preventive medicine, 39(3), 625-629.
  • Levy, B., & Langer, E. (1994). Aging free from negative stereotypes: Successful memory in China among the American deaf. Journal of Personality and Social Psychology, 66(6), 989.
  • Loos, E. & Ekström, M. (2014) Visually representing the generation of older consumers as a diverse audience: Towards a multidimensional market segmentation typology. Participations: Journal of Audience and Reception Studies, 11(2), 258-273.
  • Luhmann, N. (2000). The reality of the mass media. Stanford University Press.
  • Matsumoto, D., Hwang, H. C., & Frank, M. G. (2013). Emotional language and political aggression. Journal of Language and Social Psychology, 32(4), 452-468.
  • Maydanchik, A. (2007). Data quality assessment. Technics publications.
  • Meneghel, S. N., & Minayo, M. C. D. S. (2021). Dependent aging: what does cinema show?. Ciência & Saúde Coletiva, 26, 67-76.
  • Morgan. 2009. “Cultivation Analysis and Media Effects.” The SAGE Handbook of Media Processes and Effects, 69–82.
  • Munezero, M., Montero, C. S., Sutinen, E., & Pajunen, J. (2014). Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text. IEEE Transactions on Affective Computing, 5(2), 101-111.
  • Nelson, T. D. (Edt.). (2004). Ageism: Stereotyping and prejudice against older persons. MIT Press.
  • Olesen, C. G., & Kisjes, I. (2018). From Text Mining to Visual Classification: Rethinking Computational New Cinema History with Jean Desmet’s Digitised Business Archive. TMG Journal for Media History, 21(2).
  • Pain, P. (2021). It took me quite a long time to develop a voice: Examining feminist digital activism in the Indian #MeToo movement. New Media & Society, 23(11), 3139-3155.
  • Pérez, J. M., Giudici, J. C., & Luque, F. (2021). Pysentimiento: A python toolkit for sentiment analysis and socialnlp tasks. arXiv preprint, arXiv:2106.09462.
  • Piçarra, N., Reis, E., Chambel, T., & Arriaga, P. (2022). Searching, Navigating, and Recommending Movies through Emotions: A Scoping Review. Human Behavior and Emerging Technologies.
  • Rancière, J. (2019). The intervals of cinema. Verso Books.
  • Ren, G., & Hong, T. (2019). Examining the relationship between specific negative emotions and the perceived helpfulness of online reviews. Information Processing & Management, 56(4), 1425-1438.
  • Roberts, K., Roach, M. A., Johnson, J., Guthrie, J., & Harabagiu, S. M. (2012, May). EmpaTweet: Annotating and Detecting Emotions on Twitter. In Lrec, 12(12), 3806-3813.
  • Schmitz, H. P., Dedmon, J. M., Bruno-van Vijfeijken, T., & Mahoney, J. (2020). Democratizing advocacy?: How digital tools shape international non-governmental activism. Journal of Information Technology & Politics, 17(2), 174-191.
  • Shanahan, J., Shanahan, J., James, S., & Morgan, M. (1999). Television and its viewers: Cultivation theory and research. Cambridge University Press.
  • Shen, C. W., Chen, M., & Wang, C. C. (2019). Analyzing the trend of O2O commerce by bilingual text mining on social media. Computers in Human Behavior, 101, 474-483.
  • Shrum, L. J. (2017). Cultivation theory: Effects and underlying processes. The International Encyclopedia of Media Effects, 1-12.
  • Simpkins, C. A., & Simpkins, A. M. (2007). El confucianismo y las tradiciones marciales asiáticas. Revista de Artes Marciales Asiáticas, 2(2), 46-53.
  • Sreenivasan, S. (2013). Quantitative analysis of the evolution of novelty in cinema through crowdsourced keywords. Scientific Reports, 3(1), 1-11.
  • Sung, K. T. (1994). A cross-cultural comparison of motivations for parent care: The case of Americans and Koreans. Journal of Aging Studies, 8(2), 195-209.
  • Tan, E. S. (2018). A psychology of the film. Palgrave Communications, 4(1).
  • Tan, E. S. (1995). Film-induced affect as a witness emotion. Poetics, 23(1-2), 7-32.
  • Tello Díaz, L. (2019). Collectivism, Confucian ethics, tradition, and patriarchy in the era of kôreika shakai: Family institutions according to Yasujirô Ozu and Yôji Yamada. Estudios de Asia y África, 54(3), 585-618.
  • Virginia, G. (2016). Sentiment classification of film reviews using IB1. İçinde, 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS) (pp. 78-82). IEEE.
  • Ylänne, V. (2015). Representations of ageing in the media. İçinde Grenier, A (Edt.), Handbook of Cultural Gerontology (pp. 391-398). Routledge Press.

Yaşlılık Temalı Sinema Filmlerinde Diyalogların Duygu Haritası

Yıl 2024, Sayı: 66, 1 - 20, 26.03.2024
https://doi.org/10.47998/ikad.1284248

Öz

Medya iletilerinin bireylerin algıları üzerindeki etkileri, çok çeşitli yaklaşımlarla teorileştirilmiştir. Gerbner’in Yetiştirme Teorisi de bunlardan biridir. Teori, televizyonun, bireylerin toplumsal gerçeklik algıları üzerinde önemli etkileri olduğunu savunur. Medya iletilerinin bireylerin algıları üzerindeki etkisinden hareketle, filmler aracılığıyla üretilen yaşlılık fikrinin, yaşlılığa dair gerçek yaşamdaki anlayışımızı şekillendirdiğini söylemek mümkündür. Diğer yandan, medya iletilerinin izler kitleyi dönüştürme sürecinde duyguların rolü oldukça büyüktür. Buradan hareketle çalışmamızda, sinema filmleri aracılığıyla kurulan yaşlılığın gerçek yaşamdaki anlayışımızı nasıl şekillendirdiğine dair farklı bir perspektif geliştirebilmek amacıyla, yaşlılık temalı filmlerin diyaloglarındaki duygu yapısı araştırılmıştır. Bu doğrultuda, bir asırlık zaman diliminde üretilen tüm yaşlılık temalı filmlerin diyaloglarında, metin madenciliği yöntemiyle duygu analizi gerçekleştirilmiştir. Sonuçlar tarihsel perspektifte ve ülke sinemaları çerçevesinde, betimsel bir yaklaşımla yorumlanmıştır. Çalışmamızın, sinemada metin madenciliği araştırmalarına örnek oluşturması ve sinemada yaşlılık olgusuna yönelik tartışmalara alternatif bir bakış açısı sunması beklenmektedir.

Destekleyen Kurum

Destekleyen kurum bulunmamaktadır.

Proje Numarası

-

Kaynakça

  • Baek, K. (2018). The geographic dimension of citizenship in digital activism: Analysis of the relationships among local and global citizenship, the use of social networking sites, and participation in the occupy movement. American Behavioral Scientist, 62(8), 1138-1156.
  • Bryant, J., & Miron, D. (2004). Theory and research in mass communication. Journal of Communication.
  • Casado-Gual, N. (2020). Ageing and romance on the big screen: the ‘silvering romantic comedy’ Elsa & Fred. Ageing & Society, 40(10), 2257-2265.
  • Chang, B. L., Chang, A. F., & Shen, Y. (1984). Attitudes toward aging in the United States and Taiwan. Journal of Comparative Family Studies, 15(1), 109-130.
  • Chivers, S. (2011). The silvering screen: Old age and disability in cinema. University of Toronto Press.
  • Cohen-Shalev, A. (2009). Visions of aging: Images of the elderly in film. Apollo Books.
  • Cowgill, D. O., & Holmes, L. D. (1972). Summary and conclusions: The theory in review. Aging and Modernization, 305-323.
  • Crosthwaite, A. (2014). “Visions of Aging in U.S. Cinema.” L’invecchiamento-Aging, 10 (3): 27–32.
  • Davidson, T., Warmsley, D., Macy, M., & Weber, I. (2017, May). Automated hate speech detection and the problem of offensive language. İçinde Proceedings of the international AAAI conference on web and social media, 11 (1), 512-515.
  • Dolan, J. (2018). Contemporary cinema and 'old age': Gender and the silvering of stardom. Springer Press.
  • Edström, M. (2018). Visibility patterns of gendered ageism in the media buzz: A study of the representation of gender and age over three decades. Feminist Media Studies, 18 (1), 77-93.
  • Ekman, P. (2000). Basic emotions. In Dalgleish, T. & Power, M. (Edt.). Handbook of Cognition and Emotion, 98(45-60), 16, John Wiley & Sons.
  • Ekman, P. (1992a). An argument for basic emotions. Cognition & Emotion, 6(3-4), 169-200.
  • Ekman, P. (1992b). Are there basic emotions? Psychological Review, 99(3), 550–553.
  • Ekman, P. & Cordaro, D. (2011). What is meant by calling emotions basic? Emotion Review: Journal of the International Society for Research on Emotion 3(4), 364–370.
  • Ekman, P. & Friesen, W. V. (1982). Felt, false, and miserable smiles. Journal of Nonverbal Behavior, 6 (4), 238–52.
  • Fernández-Gavilanes, M., Juncal-Martínez, J., García-Méndez, S., Costa-Montenegro, E., & González-Castano, F. J. (2018). Creating emoji lexica from unsupervised sentiment analysis of their descriptions. Expert Systems with Applications, 103, 74-91.
  • Gerbner, G. (1977). Television: The new state religion? Review of General Semantics, 34 (2), 145–50.
  • Gerbner, G. & Gross, L. (1976). Living with television: The violence profile, Journal of Communication, 26 (2), pp. 172–199
  • Ge, Y., Qiu, J., Liu, Z., Gu, W., & Xu, L. (2020). Beyond negative and positive: Exploring the effects of emotions in social media during the stock market crash. Information Processing & Management, 57(4), 102218.
  • Greenberg, L. S. (2004). Emotion–focused therapy. Clinical Psychology & Psychotherapy: An International Journal of Theory & Practice, 11(1), 3-16.
  • Gross, J. J., & Levenson, R. W. (1995). Emotion elicitation using films. Cognition & Emotion, 9(1), 87-108.
  • Gruebner, O., Lowe, S. R., Sykora, M., Shankardass, K., Subramanian, S. V., & Galea, S. (2017). A novel surveillance approach for disaster mental health. PLoS One, 12(7), 0181233.
  • Harb, J. G., Ebeling, R., & Becker, K. (2020). A framework to analyze the emotional reactions to mass violent events on Twitter and influential factors. Information Processing & Management, 57(6), 102372.
  • Hofstede, G. (1984). The cultural relativity of the quality of life concept. Academy of Management Review, 9(3), 389-398.
  • Hou, L. (2020). Rewriting “the personal is political”: young women's digital activism and new feminist politics in China. Inter-Asia Cultural Studies, 21(3), 337-355.
  • Hungwe, K. N. (2005). Narrative and ideology: 50 years of film-making in Zimbabwe. Media, Culture & Society, 27(1), 83-99.
  • Izard, C. E. (2007). Basic emotions, natural kinds, emotion schemas, and a new paradigm. Perspectives on Psychological Science, 2(3), 260-280.
  • Kanavos, A., Perikos, I., Hatzilygeroudis, I., & Tsakalidis, A. (2018). Emotional community detection in social networks. Computers & Electrical Engineering, 65, 449-460.
  • Kozloff, S. (2000). Overhearing film dialogue. University of California Press.
  • Kracauer, S. (1997). Theory of film: The redemption of physical reality. Princeton University Press.
  • Kubrak, T. (2020). Impact of films: Changes in young people’s attitudes after watching a movie. Behavioral Sciences, 10(5), 86.
  • Levy, B. R., & Myers, L. M. (2004). Preventive health behaviors influenced by self-perceptions of aging. Preventive medicine, 39(3), 625-629.
  • Levy, B., & Langer, E. (1994). Aging free from negative stereotypes: Successful memory in China among the American deaf. Journal of Personality and Social Psychology, 66(6), 989.
  • Loos, E. & Ekström, M. (2014) Visually representing the generation of older consumers as a diverse audience: Towards a multidimensional market segmentation typology. Participations: Journal of Audience and Reception Studies, 11(2), 258-273.
  • Luhmann, N. (2000). The reality of the mass media. Stanford University Press.
  • Matsumoto, D., Hwang, H. C., & Frank, M. G. (2013). Emotional language and political aggression. Journal of Language and Social Psychology, 32(4), 452-468.
  • Maydanchik, A. (2007). Data quality assessment. Technics publications.
  • Meneghel, S. N., & Minayo, M. C. D. S. (2021). Dependent aging: what does cinema show?. Ciência & Saúde Coletiva, 26, 67-76.
  • Morgan. 2009. “Cultivation Analysis and Media Effects.” The SAGE Handbook of Media Processes and Effects, 69–82.
  • Munezero, M., Montero, C. S., Sutinen, E., & Pajunen, J. (2014). Are they different? Affect, feeling, emotion, sentiment, and opinion detection in text. IEEE Transactions on Affective Computing, 5(2), 101-111.
  • Nelson, T. D. (Edt.). (2004). Ageism: Stereotyping and prejudice against older persons. MIT Press.
  • Olesen, C. G., & Kisjes, I. (2018). From Text Mining to Visual Classification: Rethinking Computational New Cinema History with Jean Desmet’s Digitised Business Archive. TMG Journal for Media History, 21(2).
  • Pain, P. (2021). It took me quite a long time to develop a voice: Examining feminist digital activism in the Indian #MeToo movement. New Media & Society, 23(11), 3139-3155.
  • Pérez, J. M., Giudici, J. C., & Luque, F. (2021). Pysentimiento: A python toolkit for sentiment analysis and socialnlp tasks. arXiv preprint, arXiv:2106.09462.
  • Piçarra, N., Reis, E., Chambel, T., & Arriaga, P. (2022). Searching, Navigating, and Recommending Movies through Emotions: A Scoping Review. Human Behavior and Emerging Technologies.
  • Rancière, J. (2019). The intervals of cinema. Verso Books.
  • Ren, G., & Hong, T. (2019). Examining the relationship between specific negative emotions and the perceived helpfulness of online reviews. Information Processing & Management, 56(4), 1425-1438.
  • Roberts, K., Roach, M. A., Johnson, J., Guthrie, J., & Harabagiu, S. M. (2012, May). EmpaTweet: Annotating and Detecting Emotions on Twitter. In Lrec, 12(12), 3806-3813.
  • Schmitz, H. P., Dedmon, J. M., Bruno-van Vijfeijken, T., & Mahoney, J. (2020). Democratizing advocacy?: How digital tools shape international non-governmental activism. Journal of Information Technology & Politics, 17(2), 174-191.
  • Shanahan, J., Shanahan, J., James, S., & Morgan, M. (1999). Television and its viewers: Cultivation theory and research. Cambridge University Press.
  • Shen, C. W., Chen, M., & Wang, C. C. (2019). Analyzing the trend of O2O commerce by bilingual text mining on social media. Computers in Human Behavior, 101, 474-483.
  • Shrum, L. J. (2017). Cultivation theory: Effects and underlying processes. The International Encyclopedia of Media Effects, 1-12.
  • Simpkins, C. A., & Simpkins, A. M. (2007). El confucianismo y las tradiciones marciales asiáticas. Revista de Artes Marciales Asiáticas, 2(2), 46-53.
  • Sreenivasan, S. (2013). Quantitative analysis of the evolution of novelty in cinema through crowdsourced keywords. Scientific Reports, 3(1), 1-11.
  • Sung, K. T. (1994). A cross-cultural comparison of motivations for parent care: The case of Americans and Koreans. Journal of Aging Studies, 8(2), 195-209.
  • Tan, E. S. (2018). A psychology of the film. Palgrave Communications, 4(1).
  • Tan, E. S. (1995). Film-induced affect as a witness emotion. Poetics, 23(1-2), 7-32.
  • Tello Díaz, L. (2019). Collectivism, Confucian ethics, tradition, and patriarchy in the era of kôreika shakai: Family institutions according to Yasujirô Ozu and Yôji Yamada. Estudios de Asia y África, 54(3), 585-618.
  • Virginia, G. (2016). Sentiment classification of film reviews using IB1. İçinde, 2016 7th International Conference on Intelligent Systems, Modelling and Simulation (ISMS) (pp. 78-82). IEEE.
  • Ylänne, V. (2015). Representations of ageing in the media. İçinde Grenier, A (Edt.), Handbook of Cultural Gerontology (pp. 391-398). Routledge Press.
Toplam 61 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İletişim ve Medya Çalışmaları
Bölüm Araştırma Makaleleri
Yazarlar

Duygu Ergün Takan 0000-0002-5639-8615

Savaş Takan 0000-0002-7718-9476

Kamile Oya Paker 0000-0003-2104-4267

Proje Numarası -
Yayımlanma Tarihi 26 Mart 2024
Gönderilme Tarihi 16 Nisan 2023
Yayımlandığı Sayı Yıl 2024 Sayı: 66

Kaynak Göster

APA Ergün Takan, D., Takan, S., & Paker, K. O. (2024). Yaşlılık Temalı Sinema Filmlerinde Diyalogların Duygu Haritası. İletişim Kuram Ve Araştırma Dergisi(66), 1-20. https://doi.org/10.47998/ikad.1284248