Analysis of Temperament and Perception of Social Support for Online Social Networks
DOI:
https://doi.org/10.5753/isys.2024.3880Keywords:
Sentiment Analysis, Text Mining, Online Social Networks, Unsupervised Models, Perception of Social Support, ESSS, TemperamentAbstract
This study proposes a method to contrast the behavior of a user on the online social networks X and Instagram with their perception of social support and temperament, measured through questionnaires. An unsupervised model for classifying the polarity of posts was introduced, achieving superior results compared to the Vader and SentiStrength models. To contrast questionnaire results with user behavior on X and Instagram, analyses of graphs and tables were conducted, along with calculations of Pearson and Point-Biserial correlations, and an ANOVA. The results of the contrast analysis provided valuable insights into understanding the relationship between the real and online worlds, complementing the information obtained through questionnaires.
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Brum, H. and Volpe Nunes, M. d. G. (2018). Building a sentiment corpus of tweets in Brazilian Portuguese. In Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018), Miyazaki, Japan. European Language Resources Association (ELRA).
Burth, D., Godoy, A., Zuben, F. J. V., and Somvir, K. S. (2019). Online social network analysis: A survey of research applications in computer science. Social network services and Libraries.
Castells, M. and Blackwell, C. (1998). The information age: economy, society and culture. volume 1. the rise of the network society. Environment and Planning B: Planning and Design, 25:631–636.
de Alcantara, C., de Faria Paiva, E. R., Barioni, M. C. N., and Junior, L. C. O. (2023). Método para contrastar percepção de suporte social com dados extraı́dos do twitter em português. In Anais do XII Brazilian Workshop on Social Network Analysis and Mining, pages 31–42. SBC.
Dembińska-Krajewska, D. and Rybakowski, J. (2014). The temperament evaluation of memphis, pisa and san diego autoquestionnaire (temps-a)–an important tool to study affective temperaments. Psychiatr Pol, 48(2):261–276.
Freitas, C. (2013). Sobre a construção de um léxico da afetividade para o processamento computacional do português. Revista Brasileira de Linguı́stica Aplicada, 13:1031–1059.
Hohaus, L. and Berah, E. (1996). Stress, achievement, marriage and social support: effects on the psychological well-being of physicians entering midlife/mid-career. Psychology and Health, 11(5):715–731.
Hott, B., Santos, B. P., Loures, T. C., Benevenuto, F., and Vaz-de Melo, P. O. (2022). Polarização em redes sociais: Conceitos, aplicações e desafios. Sociedade Brasileira de Computação.
Hutto, C. and Gilbert, E. (2014). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the international AAAI conference on web and social media, volume 8, pages 216–225.
Karam, E. G., Mneimneh, Z., Salamoun, M., Akiskal, K. K., and Akiskal, H. S. (2005). Psychometric properties of the lebanese–arabic temps-a: a national epidemiologic study. Journal of affective disorders, 87(2-3):169–183.
Lima, A. C. E. and de Castro, L. N. (2019). Tecla: A temperament and psychological type prediction framework from twitter data. Plos one, 14(3).
Maia, M., Oliveira, E., and Gallegos, L. (2021). Covid-19 e tweets no brasil: coleta, tratamento e análise de textos com evidências de estados afetivos alterados em momentos impactantes. In Anais do X Brazilian Workshop on Social Network Analysis and Mining, pages 79–90. SBC.
Martins, L. M., De Alcantara, C., Nardini Barioni, M. C., De Oliveira Júnior, L. C., and Faria, E. R. (2022). A method for analysis of human temperament in contrast to social network data. In Proceedings of the Brazilian Symposium on Multimedia and the Web, pages 19–27.
Mikolajczyk, R. T. and Kretzschmar, M. (2008). Collecting social contact data in the context of disease transmission: prospective and retrospective study designs. Social Networks, 30(2):127–135.
Myers, I. B. (1962). The myers-briggs type indicator: Manual (1962).
Plank, B. and Hovy, D. (2015). Personality traits on twitter—or—how to get 1,500 personality tests in a week. In Proceedings of the 6th workshop on computational approaches to subjectivity, sentiment and social media analysis, pages 92–98.
Ribeiro, J. L. P. (1999). Escala de satisfação com o suporte social (esss).
Rothbart, M. K. and Derryberry, D. (1981). Development of individual differences in temperament. In Lamb, M. E. and Brown, A. L., editors, Advances in developmental psychology, volume 1, pages 37–86. Lawrence Erlbaum Associates.
Silva, E. d., Malheiros, Y., Nunes, R., Antunes, I., and Rêgo, T. (2019). Um conjunto de dados extraı́do do twitter para análise de sentimentos na lı́ngua portuguesa. Trabalho de Conclusão de Curso em Sistemas de Informação da Universidade Federal da Paraı́ba.
Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., and Kappas, A. (2010). Sentiment strength detection in short informal text. Journal of the American society for information science and technology, 61(12):2544–2558.
Thoits, P. A. (2011). Mechanisms linking social ties and support to physical and mental health. Journal of Health and Social Behavior, 52(2):145–161.
Vioules, M. J., Moulahi, B., Azé, J., and Bringay, S. (2018). Detection of suicide-related posts in twitter data streams. IBM Journal of Research and Development, 62(1):7–1.
Woodruff, E., Genaro, L. T., Landeira-Fernandez, J., Cheniaux, E., Laks, J., Jean-Louis, G., Nardi, A. E., Versiani, M. C., Akiskal, H. S., and Mendlowicz, M. V. (2011). Validation of the brazilian brief version of the temperament auto-questionnaire temps-a: the brief temps-rio de janeiro. Journal of affective disorders, 134(1-3):65–76.
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