Sentimenduen analisia Instagramen: haurren kontuen polaritatea eta subjektibotasuna
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Argitaratua
29-05-2020
Arantxa Vizcaino-Verdu
Ignacio Aguaded
http://orcid.org/0000-0002-0229-1118
Laburpena
Instagram haur eta gazteen eguneroko bizitzaren parte bihurtu da, eta nolabaiteko familia albuma sortzen dute. Testuinguru horretan, plataforman gurasoek kudeatutako haurren kontuetako 772 testu sarreraren polaritatea eta subjektibotasuna aztertu ditugu, hizkuntza naturalaren prozesamenduaren bitartez, machine learning delakoaren eta eduki analisiaren bitartez. Emaitzek erakutsi zuten positibotasun eta subjektibotasun nabaria zegoela gaztelaniazko lau kontutako eta ingelesezko lau kontutako lexikoaren eremuan, eta behin eta berriz erabiltzen zituztela hainbat adjektibo, hala nola: zoriontsu, berria, superra... Laburbilduz, haurren kontuek heziera bukoliko eta alaien joera adierazten dute.
Nola aipatu
Vizcaino-Verdu, A., & Aguaded, I. (2020). Sentimenduen analisia Instagramen: haurren kontuen polaritatea eta subjektibotasuna. Zer - Komunikazio Ikasketen Aldizkaria, 25(48). https://doi.org/10.1387/zer.21454
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Keywords
Instagram, haurtzaroa, sentimenduen analisia, polaritatea, subjektibotasuna, zoriontasuna.
References
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Diyana-Abdullah, N.S., y Asnira-Zolkepli, I. (2017). Sentiment analysis of online crowd input towards brand provocation in Facebook, Twitter, and Instagram. En Proceedings of the International Conference on Big Data and Internet of Thing (pp. 67-74). New York: BDIOT. https://doi.org/10.1145/3175684.3175689
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Freitas, D. (2017). The happiness effect: How social media is driving a generation to appear perfect at any cost. Oxford: Oxford University Press.
Gómez-Espino, J.M., y Blanco-López, J. (2005). Los niños en la publicidad. Una propuesta de categorización de las representaciones sociales sobre la infancia en los anuncios televisivos. ZER Revista de Estudios de Comunicación, 10(19), 53-79. Recuperado de https://bit.ly/36iU2jM
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Hasan, A., Moin, S., Karim, A., y Shamshirband, S. (2018). Machine learning-based sentiment analysis for Twitter accounts. Mathematical and Computational Applications, 23(11), 1-15. https://doi.org/10.3390/mca23010011
Ho, H., Shin, W., y Lwin, M.O. (2017). Social networking site use and materialistic values among youth: The safeguarding role of the parent-child relationship and self-regulation. Communication Research, 46(8), 1119-1144. https://doi.org/10.1177/0093650216683775
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Ao, S. (2018). Sentiment analysis based on financial tweets and market information. En 2018 International Conference on Audio, Language and Image Processing (pp. 321-326). Shanghai: ICALIP. https://doi.org/10.1109/ICALIP.2018.8455771
Araque, O., Corcuera-Platas, I., Sánchez-Rada, F., y Iglesias, C.A. (2017). Enhancing deep learning sentiment analysis with ensemble techniques in social applications. Expert Systems with Applications, 77, 236-246. https://doi.org/10.1016/j.eswa.2017.02.002
Asch, S.E. (1946). Forming impressions of personality. The Journal of Abnormal and Social Psychology, 41(3), 258-290. https://doi.org/10.1037/h0055756
Ashok, M., Rajanna, S., y Joshi, P.V. (2016). A personalized recommender system using machine learning based sentiment analysis over social data. En 2016 IEEE Students' Conference on Electrical, Electronics and Computer Science (pp. 1-6). Bhopal, India: SCEECS. https://doi.org/10.1109/SCEECS.2016.7509354
Berezan, O., Krishen, A.S., Agarwal, S., y Kachroo, P. (2017). The pursuit of virtual happiness: Exploring the social media experience across generations. Journal of Business Research, 89, 455-461. https://doi.org/10.1016/j.jbusres.2017.11.038
Blum-Ross, A., y Livingstone, S. (2017). Sharenting, parent blogging, and the boundaries of the digital self. Popular Communication, 15(2), 110-125. https://doi.org/10.1080/15405702.2016.1223300
Bosangit, C., y Demangeot, C. (2016). Exploring reflective learning during the extended consumption of life experiences. Journal of Business Reserach, 69(1), 208-215. https://doi.org/10.1016/j.jbusres.2015.07.033
Bourdieu, P. (1990). Photography: A middlebrow art. Standford: Stanford University Press.
Buijzen, M., y Valkenburg, P.M. (2005). Parental mediation of undesired advertising effects. Journal of Broadcasting & Electronic Media, 49, 153-165. https://doi.org/10.1207/s15506878jobem4902_1
Buijzen, M., Schuurman, J., y Bomhof, E. (2008). Associations between children's television advertising exposure and their food consumption patterns: A household diary-survey study. Appetite, 50, 231-239. https://doi.org/10.1016/j.appet.2007.07.006
Calvo-González, S., y San-Fabián-Maroto, J.L. (2018). Selfies, jóvenes y sexualidad en Instagram: Representaciones del yo en formato imagen. Pixel-Bit, 52, 167-181. https://doi.org/10.12795/pixelbit.2018.i52.12
Casado-Riera, C., y Carbonell, X. (2018). La influencia de la personalidad en el uso de Instagram. Aloma, 36(2), 23-31. Recuperado de https://bit.ly/37dFP9b
Chacón-López, H., Romero-Barriga, J.F., Aragón-Carretero, Y., y Caurcel-Cara, M.J. (2016). Construcción y validación de la escala de conductas sobre sexting (ECS). Revista Española de Orientación y Psicopedagogía, 27(2), 99-115. https://doi.org/10.5944/reop.vol.27.num.2.2016.17116
Chae, J. (2018). Reexamining the relationship between social media and happiness: The effects of various social media platforms on reconceptualized happiness. Telematics and Informatics, 35(6), 1656-1664. https://doi.org/10.1016/j.tele.2018.04.011
Choi, G.Y., y Lewallen, J. (2017). Say Instagram, kids!: Examining sharenting and children's digital representations on Instagram. Howard Journal of Communication, 29(2), 144-164. https://doi.org/10.1080/10646175.2017.1327380
Dale, K.R., Raney, A.A., Ji, Q., Janicke-Bowles, S.H., Baldwin, J., Rowlett, J.T., … Oliver, M.B. (2019). Self-transcendent emotions and social media: Exploring the content and consumers of inspirational Facebook posts. New Media & Society, 1-21. https://doi.org/10.1177%2F1461444819865720
De-Casas-Moreno, P., Tejedor-Calvo, S., y Romero-Rodríguez, L.M. (2018). Micronarrativas en Instagram: Análisis del storytelling autobiográfico y de la proyección de identidades de los universitarios del ámbito de la comunicación. Prisma Social, 20, 41-57. Recuperado de https://bit.ly/30EDEsT
Díaz-Bustamante, M., y Llovet-Rodriguez, C. (2017). Empowerment or impoverishment of children from social networks? Perceptions of sexualized images of girls in Instagram. El Profesional de la Información, 26(1), 77-87. https://doi.org/10.3145/epi.2017.ene.08
Diener, E. (2009). Happiness. En M.R., Leary y R.H. Hoyle (Eds.), Handbook of individual differences in social behavior (pp. 147-160). New York: Guilford. Recuperado de https://bit.ly/2sK57gh
Diessner, R., Solom, R.C., Frost, N.K., Parsons, L., y Davidson, J. (2008). Engagement with beauty: Appreciating natural, artistic, and moral beauty. The Journal of Psychology, 142(3), 303-332. https://doi.org/10.3200/JRLP.142.3.303-332
Diyana-Abdullah, N.S., y Asnira-Zolkepli, I. (2017). Sentiment analysis of online crowd input towards brand provocation in Facebook, Twitter, and Instagram. En Proceedings of the International Conference on Big Data and Internet of Thing (pp. 67-74). New York: BDIOT. https://doi.org/10.1145/3175684.3175689
Domingo, M., Jewitt, C., y Kress, G. (2015). Multimodal social semiotics: Writing in online contexts. En J. Rowsell & K. Pahl (Eds.), The Routledge Handbook of Literacy Studies (pp. 251-266). London: Routledge. Recuperado de https://bit.ly/2sMlbOE
Dresner, E., y Herring, S.C. (2010). Functions of the nonverbal in CMC: Emoticons and 833 illocutionary force. Communication Theory, 20(3), 249-268. https://doi.org/10.1111/j.1468-2885.2010.01362.x
Freitas, D. (2017). The happiness effect: How social media is driving a generation to appear perfect at any cost. Oxford: Oxford University Press.
Gómez-Espino, J.M., y Blanco-López, J. (2005). Los niños en la publicidad. Una propuesta de categorización de las representaciones sociales sobre la infancia en los anuncios televisivos. ZER Revista de Estudios de Comunicación, 10(19), 53-79. Recuperado de https://bit.ly/36iU2jM
Gorton, K., y Garde-Hansen, J. (2013). Social media, happiness, and virtual communities. En Emotion online (pp. 103-125). London: Palgrave Macmillan. https://doi.org/10.1057/9781137312877_5
Hadjipanayis, A., Efstathiou, E., Altorjai, P., Stiris, T., Valiulis, A., Koletzko, B., y Fonseca, H. (2019). Social media and children: What is the paediatrician's role? European Journal of Pediatrics, 178(10), 1605-1612. https://doi.org/10.1007/s00431-019-03458-w
Hasan, A., Moin, S., Karim, A., y Shamshirband, S. (2018). Machine learning-based sentiment analysis for Twitter accounts. Mathematical and Computational Applications, 23(11), 1-15. https://doi.org/10.3390/mca23010011
Ho, H., Shin, W., y Lwin, M.O. (2017). Social networking site use and materialistic values among youth: The safeguarding role of the parent-child relationship and self-regulation. Communication Research, 46(8), 1119-1144. https://doi.org/10.1177/0093650216683775
Huffaker, D. (2010). Dimensions of leadership and social influence in online 853 communities. Human Communication Research, 36(4), 593-617. https://doi.org/10.1111/j.1468-2958.2010.01390.x
Hummel-O'Donnell, N. (2018). Storied lives on Instagram: Factors associated with the need for personal-visual identity. Visual Communication Quarterly, 25(3), 131-142. https://doi.org/10.1080/15551393.2018.1490186
Instagram (2020). About us. Recuperado de https://bit.ly/38n6mBa
Izquierdo-Iranzo, P., y Gallardo-Echenique, E. (2020). Estudigramers: Influencers del aprendizaje. [Studygrammers: Learning influencers]. Comunicar, 62, 115-125. https://doi.org/10.3916/C62-2020-10
Kim, Y., y Kim, J.H. (2018). Using computer vision techniques on Instagram to link users' personalities and genders to the features of their photos: An exploratory study. Information Processing and Management, 54, 1101-1114. https://doi.org/10.1016/j.ipm.2018.07.005
Krippendorff, K. (1980). Metodología de análisis de contenido. Teoría y práctica. Barcelona: Paidós.
Larrañaga, E., Navarro, R., y Yubero, S. (2018). Socio-cognitive and emotional factors on perpetration of cyberbullying. [Factores socio-cognitivos y emocionales en la agresión del ciberacoso]. Comunicar, 56, 19-28. https://doi.org/10.3916/C56-2018-02
Lee, E., Lee, J.A., Moon, J.H., y Sung, Y. (2015). Pictures speak louder than words: Motivations for using Instagram. Cyberpsychology, Behavior and Social Networking, 18(9), 552-556. https://doi.org/10.1089/cyber.2015.015
Le-Moignan, E., Lawson, S., Rowland, D.A., Mahoney, J., y Briggs, P. (2017). Has Instagram fundamentally altered the 'family snapshot'? Technology in Households, 6(11), 4935-4947. https://doi.org/10.1145/3025453.3025928
Liu, B. (2015). Sentiment analysis: Mining opinions, sentiments, and emotions. Cambridge: Cambridge University Press.
Livingstone, S., Mascheroni, G., Ólafsson, K., y Haddon, L. (2014). Children's online risks and opportunities: Comparative findings from EU Kids online and Net Children Go Mobile. London: EU Kids Online. Recuperado de https://bit.ly/37fJDXo
Lup, K., Trub, L., y Rosenthal, L. (2015). Instagram #instasad?: Exploring associations among Instagram use, depressive symptoms, negative social comparison, and strangers followed. Cyberpsychology, Behavior and Social Networking, 18(5), 247-252. https://doi.org/10.1089/cyber.2014.0560
Marinas, L. (2019). Instagram: Donde Millenialls, Generación Z, McLuhan y Bolter se cruzan. Cuadernos de Información y Comunicación, 24, 187-201. https://doi.org/10.5209/ciyc.64641
Micu, A., Micu, A.E., Geru, M., y Lixandroiu, R.C. (2017). Analyzing user sentiment in social media: Implications for online marketing strategy. Psychology & Marketing, 34(12), 1094-1100. https://doi.org/10.1002/mar.21049
Nathanson, A.I. (2004). Factual and evaluative approaches to modifying children's responses to violent television. Journal of Communication, 54, 321-336. https://doi.org/10.1111/j.1460-2466.2004.tb02631.x
Pang, B., Lee, L., y Viathyanathan, S. (2002). Thumbs up?: Sentiment classification using machine learning techniques. En Proceedings of the ACL-02 conference on empirical methods in natural language processing (pp. 79-86). Stroudsburg: Association for Computational Linguistics.
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