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.

View infography

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

Crossmark

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

Metrics

Metrics of this article

Views: 41688

Abstract readings: 36661

PDF downloads: 5027

Full metrics of Comunicar 74

Views: 357459

Abstract readings: 327264

PDF downloads: 30195

Cited by

Cites in Web of Science

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

Cites in Google Scholar

Mendoza Rosas, D. S. (2022). El cambio de la forma de consumo de contenidos en redes sociales a partir del Tik Tok.

https://repositorio.uns.edu.pe/handle/20.500.14278/4066

Polarization, virality and contrary sentiments for LGTB content on Instagram, TikTok, and Twitter C Barroso-Moreno… - Profesional de …, 2023 - revista.profesionaldelainformacion …

https://revista.profesionaldelainformacion.com/index.php/EPI/article/view/87253

The effectiveness of Facebook advertising in a sports club. P Zach - Journal of Sports Marketing & Sponsorship, 2023 - theses.cz

https://theses.cz/id/yqi7ge/BP-MarketingEfektivita_facebook_reklamy_ve_sportovnim_kkudocx.pdf

Análisis comparativo de la interacción discursiva de dos 'edutubers' de matemáticas J Anzola, D River-Rogel - 2023 - burjcdigital.urjc.es

https://burjcdigital.urjc.es/handle/10115/22943

Percepción de los menores sobre el papel de sus padres en su uso de redes sociales B Feijoo, C Sádaba… - … Multidisciplinary Journal of …, 2023 - hipatiapress.com

https://hipatiapress.com/hpjournals/index.php/rimcis/article/view/11017

Download

Alternative metrics

How to cite

Lozano-Blasco, R., Mira-Aladrén, M., & Gil-Lamata, M. (2023). Social media influence on young people and children: Analysis on Instagram, Twitter and YouTube. [Redes sociales y su influencia en los jóvenes y niños: Análisis en Instagram, Twitter y YouTube]. Comunicar, 74, 125-137. https://doi.org/10.3916/C74-2023-10

Share

           

Oxbridge Publishing House

4 White House Way

B91 1SE Sollihul United Kingdom

Administration

Editorial office

Creative Commons

This website uses cookies to obtain statistical data on the navigation of its users. If you continue to browse we consider that you accept its use. +info X