Keywords
Adolescence, youth, polarity, Twitter, YouTube, Instagram
Abstract
Social networking sites are a new ecosystem of social relations in which adolescents follow public figures or influencers: instagrammers, tweeters and youtubers. Their behaviour in the posts they publish become a trend and a model for the new generations. In order to explore these behaviours and their consequences, it is useful to study the behaviour of the 10 instagramers, 10 tweeters and 10 youtubers with the largest number of followers in the world. A mixed method was employed, combining: social media analysis (SNA) methodology executed by monitoring Twitter, Instagram and YouTube accounts and their publications (300 posts with the highest number of likes). The FanapageKarma tool was used to capture data by applying data mining techniques. Subsequently, sentiment analysis was performed using Meaning Cloud software, determining sentiment polarity analysis quantitatively. Finally, a semantic analysis of the content was performed using Nvivo. The results of multi-regression and sentiment’s analysis show clear differences between social networking sites. Twitter is a space for critical analysis of information and social movements, especially climate change. In this space adolescents defend their values and ideology. Instagram is a showcase for fashion and beauty, where brands support an idealised and desirable lifestyle. YouTube is a space for entertainment and comedy. It concludes that despite their differences there is one univocal feature, the effort of influencers to capture audiences and establish parasocial relationships.
References
Anderson, M., & Jiang, J. (2018, May 31). Teens, social media & technology. Pew Research Center. https://pewrsr.ch/3aRyOSL
Link Google Scholar
Aran-Ramspott, S., Fedele, M., & Tarragó, A. (2018). YouTubers' social functions and their influence on pre-adolescence. [Funciones sociales de los Youtubers y su influencia en la preadolescencia]. Comunicar, 57, 71-80. https://doi.org/10.3916/C57-2018-07
Link DOI | Link Google Scholar
Ashman, R., Patterson, A., & Brown, S. (2018). ‘Don’t forget to like, share and subscribe’: Digital autopreneurs in a neoliberal world. Journal of Business Research, 92, 474-483. https://doi.org/10.1016/j.jbusres.2018.07.055
Link DOI | Link Google Scholar
Bakir, A., Gentina, E., & de-Araújo-Gil, L. (2020). What shapes adolescents’ attitudes toward luxury brands? The role of self-worth, self-construal, gender and national culture. Journal of Retailing and Consumer Services, 57, 102208. https://doi.org/10.1016/j.jretconser.2020.102208
Link DOI | Link Google Scholar
Barton, A.H., & Lazarsfeld, P.F. (1955). Some functions of qualitative analysis in social research. Bobbs Merrill.
Link Google Scholar
Bhatia, A. (2018). Interdiscursive performance in digital professions: The case of YouTube tutorials. Journal of Pragmatics, 124, 106-120. https://doi.org/10.1016/j.pragma.2017.11.001
Link DOI | Link Google Scholar
Blasco-García, J. (2020). Nuevas formas de ausencia: Las redes sociales. [Doctoral Dissertation, Universitat Politécnica de Valencia]. https://bit.ly/3JplAJN
Link Google Scholar
Boerman, S.C. (2020). The effects of the standardized Instagram disclosure for micro- and meso-influencers. Computers in Human Behavior, 103, 199-207. https://doi.org/10.1016/j.chb.2019.09.015
Link DOI | Link Google Scholar
Burgess, J., & Green, J., (2009). YouTube: Online video and participatory culture. Cambridge Polity Press. https://bit.ly/3Qfi1rs
Link Google Scholar
Burnette, C.B., Kwitowski, M.A., & Mazzeo, S.E. (2017). “I don’t need people to tell me I’m pretty on social media:” A qualitative study of social media and body image in early adolescent girls. Body Image, 23, 114-125. https://doi.org/10.1016/j.bodyim.2017.09.001
Link DOI | Link Google Scholar
Castillo-Abdul, B., Romero-Rodríguez, L.M., & Larrea-Ayala, A. (2020). Kid influencers in Spain: Understanding the themes they address and preteens’ engagement with their YouTube channels. Heliyon, 6(9). https://doi.org/10.1016/j.heliyon.2020.e05056
Link DOI | Link Google Scholar
Davis, K. (2012). Friendship 2.0: Adolescents’ experiences of belonging and self-disclosure online. Journal of Adolescence, 35(6), 1527-1536. https://doi.org/10.1016/j.adolescence.2012.02.013
Link DOI | Link Google Scholar
De-Bérail, P., Guillon, M., & Bungener, C. (2019). The relations between YouTube addiction, social anxiety and parasocial relationships with Youtubers: A moderated-mediation model based on a cognitive-behavioral framework. Computers in Human Behavior, 99, 190-204. https://doi.org/10.1016/j.chb.2019.05.007
Link DOI | Link Google Scholar
Du?cu, M., & Günneç, D. (2020). Polarity classification of Twitter messages using audio processing. Information Processing & Management, 57(6), 102346. https://doi.org/10.1016/j.ipm.2020.102346
Link DOI | Link Google Scholar
Erz, A., Marder, B., & Osadchaya, E. (2020). Hashtags: Motivational drivers, their use, and differences between influencers and followers. Computers in Human Behavior, 89, 48-60. https://doi.org/10.1016/j.chb.2018.07.030
Link DOI | Link Google Scholar
Ferchaud, A., Grzeslo, J., Orme, S., & LaGroue, J. (2018). Parasocial attributes and YouTube personalities: Exploring content trends across the most subscribed YouTube channels. Computers in Human Behavior, 80, 88-96. https://doi.org/10.1016/j.chb.2017.10.041
Link DOI | Link Google Scholar
Genç, M., & Öksüz, B. (2019). An analysis on collaborations between Turkish beauty YouTubers and cosmetic brands. Procedia Computer Science, 158, 745-750. https://doi.org/10.1016/j.procs.2019.09.110
Link DOI | Link Google Scholar
Harb, J., 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. https://doi.org/10.1016/j.ipm.2020.102372
Link DOI | Link Google Scholar
Hartmann, T. (2016). Parasocial interaction, parasocial relationships, and well-being. In L. Reinecke, & M.B. Oliver (Eds.), The Routledge handbook of media use and well-being: International perspectives on theory and research on positive media effects (pp. 131-144). Routledge. https://bit.ly/3zP0GjL
Link Google Scholar
Hu, M., & Liu, B. (2004). Mining and summarizing customer reviews. In Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining (KDD '04) (pp. 168-177). Association for Computing Machinery. https://doi.org/10.1145/1014052.1014073
Link DOI | Link Google Scholar
Jerslev, A. (2016). Media times. In the time of the microcelebrity: Celebrification and the YouTuber zoella. International Journal of Communication, 10, 5233-5251. https://bit.ly/3ySPG3r
Link Google Scholar
Kale, G., & Jayanth, J. (2019). Introduction to research. In V. Bairagi, & M. Munot (Eds.), Research Methodology. A Practical and Scientific Approach. CRC Press. https://doi.org/10.1201/9781351013277-1
Link DOI | Link Google Scholar
Keegan, B.J., & Rowley, J. (2017). Evaluation and decision making in social media marketing. Management Decision, 55(1), 15-31. https://doi.org/10.1108/MD-10-2015-0450
Link DOI | Link Google Scholar
Kim, D.H., Seely, N.K., & Jung, J.H. (2017). Do you prefer, Pinterest or Instagram? The role of image-sharing SNSs and self-monitoring in enhancing ad effectiveness. Computers in Human Behavior, 70, 535-543. https://doi.org/10.1016/j.chb.2017.01.022
Link DOI | Link Google Scholar
Kim, J., & Kim, Y. (2019). Instagram user characteristics and the color of their photos: Colorfulness, color diversity, and color harmony. Information Processing & Management, 56(4), 1494-1505. https://doi.org/10.1016/j.ipm.2018.10.018
Link DOI | Link Google Scholar
Krippendorff, K. (1980). Content analysis: An introduction to its methodology. Sage. https://bit.ly/3bmaPv0
Link Google Scholar
Lange, P.G. (2014). Commenting on YouTube rants: Perceptions of inappropriateness or civic engagement? Journal of Pragmatics, 73, 53-65. https://doi.org/10.1016/j.pragma.2014.07.004
Link DOI | Link Google Scholar
Latorre-Martínez, P., Orive-Serrano, V., & Íñiguez-Dieste, D. (2018). Measurement and analysis of the presence in Facebook and Twitter in the regional television broadcaster’s context in Spain. Profesional de la Información, 27(5), 1061-1070. https://doi.org/10.3145/epi.2018.sep.10
Link DOI | Link Google Scholar
León, O.G., & Montero, I. (2015). Métodos de investigación en Psicología y Educación. Las tradiciones cuantitativa y cualitativa. McGraw Hill. https://bit.ly/3BCmP6w
Link Google Scholar
Lipsman, A., Mudd, G., Rich, M., & Bruich, S. (2012). The power of “like”: How brands reach (and influence) fans through social-media marketing. Journal of Advertising Research, 52(1), 40-52. https://doi.org/10.2501/JAR-52-1-040-052
Link DOI | Link Google Scholar
Lozano-Blasco, R., Quilez-Robres, A., Delgado-Bujedo, D., & Latorre-Martínez, M.P. (2021). YouTube's growth in use among children 0–5 during COVID19: The Occidental European case. Technology in society, 66, 101648. https://doi.org/10.1016/j.techsoc.2021.101648
Link DOI | Link Google Scholar
McGoogan, C. (2017, August 17). Hashtag turns 10: Seven facts you didn't know about the trending symbol. The Telegraph. https://bit.ly/3coL51b
Link Google Scholar
Mäntymäki, M., & Riemer, K. (2014). Digital natives in social virtual worlds: A multi-method study of gratifications and social influences in Habbo Hotel. International Journal of Information Management, 34(2), 210-220. https://doi.org/10.1016/j.ijinfomgt.2013.12.010
Link DOI | Link Google Scholar
Neu, D., Saxton, G., Rahaman, A., & Everett, J. (2019). Twitter and social accountability: Reactions to the Panama Papers. Critical Perspectives on Accounting, 61, 38-53. https://doi.org/10.1016/j.cpa.2019.04.003
Link DOI | Link Google Scholar
Nguyen, H., & Le-Nguyen, M. (2018). Multilingual opinion mining on YouTube – A convolutional N-gram BiLSTM word embedding. Information Processing & Management, 54(3), 451-462. https://doi.org/10.1016/j.ipm.2018.02.001
Link DOI | Link Google Scholar
Ofcom (Eds.) (2017). Children and parents: Media use and attitudes report. Ofcom. https://bit.ly/3IRiG05
Link Google Scholar
Oramas-Bustillos, R., Zatarain-Cabada, R., Barrón-Estrada, M.L., & Hernández-Pérez, Y. (2019). Opinion mining and emotion recognition in an intelligent learning environment. Computer Applications in Engineering Education, 27(1), 90-101. https://doi.org/10.1002/cae.22059
Link DOI | Link Google Scholar
Peres, R., Talwar, S., Alter, L., Elhanan, M., & Friedmann, Y. (2020). Narrowband influencers and global icons: Universality and media compatibility in the communication patterns of political leaders worldwide. Journal of International Marketing, 28(1), 48-65. https://doi.org/10.1177/1069031X19897893
Link DOI | Link Google Scholar
Reyes-Menéndez, A., Saura, J.R., & Alvarez-Alonso, C. (2018). Understanding #WorldEnvironmentDay user opinions in Twitter: A topic-based sentiment analysis approach. International Journal of Environmental Research and Public Health, 15(11), 2537. https://doi.org/10.3390/ijerph15112537
Link DOI | Link Google Scholar
Saura, J.R., Debasa, F., & Reyes-Menendez, A. (2019). Does user generated content characterize Millennials’ generation behavior? Discussing the relation between SNS and open innovation. Journal of Open Innovation: Technology, Market, and Complexity, 5(4), 1-15. https://doi.org/10.3390/joitmc5040096
Link DOI | Link Google Scholar
Scannell, P. (2000). For-anyone-as-someone structures. Media, Culture & Society, 22(1), 5-24. https://doi.org/10.1177/016344300022001001
Link DOI | Link Google Scholar
Schmuck, D., Karsay, K., Matthes, J., & Stevic, A. (2019). ‘Looking up and feeling down’. The influence of mobile social networking site use on upward social comparison, self-esteem, and well-being of adult smartphone users. Telematics and Informatics, 42, 101240. https://doi.org/10.1016/j.tele.2019.101240
Link DOI | Link Google Scholar
Schouten, A.P., Janssen, L., & Verspaget, M. (2020). Celebrity vs. influencer endorsements in advertising: The role of identification, credibility, and product-endorser fit. International Journal of Advertising, 39(2) 258-281. https://doi.org/10.1080/02650487.2019.1634898
Link DOI | Link Google Scholar
Shane-Simpson, C., Manago, A., Gaggi, N., & Gillespie-Lynch, K. (2018). Why do college students prefer Facebook, Twitter, or Instagram? Site affordances, tensions between privacy and self-expression, and implications for social capital. Computers in Human Behavior, 86, 276-288. https://doi.org/10.1016/j.chb.2018.04.041
Link DOI | Link Google Scholar
Sharma, S.K., & Hoque, X. (2017). Sentiment predictions using support vector machines for odd-even formula in Delhi. International Journal of Intelligent Systems and Applications, 9(7), 61-69. https://doi.org/10.5815/ijisa.2017.07.07
Link DOI | Link Google Scholar
Smith, A., & Anderson, M. (2018, March 1). Social media use in 2018. Pew Research Center. https://pewrsr.ch/3v4hmBn
Link Google Scholar
Song, L., Li, R.Y.M., & Yao, Q. (2022). An informal institution comparative study of occupational safety knowledge sharing via French and English Tweets: Languaculture, weak-strong ties and AI sentiment perspectives. Safety Science, 147, 105602. https://doi.org/10.1016/j.ssci.2021.105602
Link DOI | Link Google Scholar
Stockdale, L.A., & Coyne, S.M. (2020). Bored and online: Reasons for using social media, problematic social networking site use, and behavioral outcomes across the transition from adolescence to emerging adulthood. Journal of Adolescence, 79, 173-183. https://doi.org/10.1016/j.adolescence.2020.01.010
Link DOI | Link Google Scholar
Throuvala, M.A., Griffiths, M.D., Rennoldson, M., & Kuss, D.J. (2019). Motivational processes and dysfunctional mechanisms of social media use among adolescents: A qualitative focus group study. Computers in Human Behavior, 93, 164-175. https://doi.org/10.1016/j.chb.2018.12.012
Link DOI | Link Google Scholar
Van-Reijmersdal, E.A., Rozendaal, E., Hudders, L., Vanwesenbeeck, I., Cauberghe, V., & van-Berlo, Z.M.C. (2020). Effects of disclosing influencer marketing in videos: An eye tracking study among children in early adolescence. Journal of Interactive Marketing, 49(1), 94-106. https://doi.org/10.1016/j.intmar.2019.09.001
Link DOI | Link Google Scholar
Vannucci, A., & McCauley-Ohannessian, C. (2019). Social media use subgroups differentially predict psychosocial well-being during early adolescence. Journal of Youth and Adolescence, 48, 1469-1493. https://doi.org/10.1007/s10964-019-01060-9
Link DOI | Link Google Scholar
Verrastro, V., Fontanesi, L., Liga, F., Cuzzocrea, F., & Gugliandolo, M.C. (2020). Fear the Instagram: Beauty stereotypes, body image and Instagram use in a sample of male and female adolescents. Qwerty, 15(1), 31-49. https://doi.org/10.30557/QW000021
Link DOI | Link Google Scholar
Vizcaíno-Verdú, A., & Aguaded, I. (2020). Análisis de sentimiento en Instagram: Polaridad y subjetividad de cuentas infantiles. ZER, 25(48), 213-229. https://doi.org/10.1387/zer.21454
Link DOI | Link Google Scholar
Weismueller, J., Harrigan, P., Wang, S., & Soutar, G.N. (2020). Influencer endorsements: How advertising disclosure and source credibility affect consumer purchase intention on social media. Australasian Marketing Journal, 28(4), 160-170. https://doi.org/10.1016/j.ausmj.2020.03.002
Link DOI | Link Google Scholar
Xu, Q.A., Chang, V., & Jayne, C. (2022). A systematic review of social media-based sentiment analysis: Emerging trends and challenges. Decision Analytics Journal, 3, 100073. https://doi.org/10.1016/j.dajour.2022.100073
Link DOI | Link Google Scholar
Yau, J.C., & Reich, S.M. (2019). “It’s just a lot of work”: Adolescents’ self-presentation norms and practices on Facebook and Instagram. Journal of Research on Adolescence, 29(1), 196-209. https://doi.org/10.1111/jora.12376
Link DOI | Link Google Scholar
Yu, Y., Duan, W., & Cao, Q. (2013). The impact of social and conventional media on firm equity value: A sentiment analysis approach. Decision Support Systems, 55(4), 919-926. https://doi.org/10.1016/j.dss.2012.12.028
Link DOI | Link Google Scholar
Technical information
Received: 02-05-2022
Revised: 13-06-2022
Accepted: 19-07-2022
OnlineFirst: 30-10-2022
Publication date: 01-01-2023
Article revision time: 42 days | Average time revision issue 74: 40 days
Article acceptance time: 78 days | Average time of acceptance issue 74: 69 days
Preprint editing time: 199 days | Average editing time preprint issue 74: 194 days
Article editing time: 244 days | Average editing time issue 74: 239 days
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Quilez-Robres, A; Acero-Ferrero, M; (...); Aiger-Valles, M. Social Networks in Military Powers: Network and Sentiment Analysis during the COVID-19 Pandemic COMPUTATION, 2023.
https://doi.org/10.3390/computation11060117
Feijoo, B; Sadaba, C and Zozaya, L. Distrust by default: analysis of parent and child reactions to health misinformation exposure on TikTok INTERNATIONAL JOURNAL OF ADOLESCENCE AND YOUTH, 2023.
https://doi.org/10.1080/02673843.2023.2244595
Pacheco, DAC; Briz, T and Urbano, B. The social side of business: content, traffic and visibility MANAGEMENT DECISION, 2023.
https://doi.org/10.1108/MD-09-2022-1319
Barroso-Moreno, C; Rayon-Rumayor, L; (...); Hernandez-Ortega, J. Polarization, virality and contrary sentiments for LGTB content on Instagram, TikTok, and Twitter Profesional de la Informacion, 2023.
https://doi.org/10.3145/epi.2023.mar.11
Cites in Scopus
Barroso-Moreno, C., Rayón-Rumayor, L., Bañares-Marivela, E., Hernández-Ortega, J.. Polarization, virality and contrary sentiments for LGTB content on Instagram, TikTok, and Twitter), Profesional de la Informacion , .
https://doi.org/10.3145/epi.2023.mar.11
Quilez-Robres, A., Acero-Ferrero, M., Delgado-Bujedo, D., Lozano-Blasco, R., Aiger-Valles, M.. Social Networks in Military Powers: Network and Sentiment Analysis during the COVID-19 Pandemic), Computation, .
https://doi.org/10.3390/computation11060117
Albadri, H.A. . The Role and Impact of Social Media Influencers), Information Sciences Letters, .
https://doi.org/10.18576/isl/120821
Feijoo, B., Sádaba, C., López-Martínez, A.. Spanish Minors’ Perception of their Parents’ Role in their Use of Social Media Networks), International and Multidisciplinary Journal of Social Sciences, .
https://doi.org/10.17583/rimcis.11017
Feijoo, B., Sádaba, C., Zozaya, L.. Distrust by default: analysis of parent and child reactions to health misinformation exposure on TikTok), International Journal of Adolescence and Youth, .
https://doi.org/10.1080/02673843.2023.2244595
Carpio Pacheco, D.A., Briz, T., Urbano, B.. The social side of business: content, traffic and visibility), Management Decision, .
https://doi.org/10.1108/MD-09-2022-1319
Notley, T., Dezuanni, M., Chambers, S., Park, S.. Using YouTube to seek answers and make decisions: Implications for Australian adult media and information literacy), Comunicar, .
https://doi.org/10.3916/C77-2023-06
