Analysing The Meaning Of Tone Indicators By Neurodivergent Community in Twitter

  • Maria Febiana Christanti Lecturer, Faculty of Communication and Political Science, UPNVJ University, Indonesia
  • Puri Bestari Mardani Lecturer, Faculty of Communication and Political Science, UPNVJ University, Indonesia
  • Khansa Ayu Fadhila Student, Faculty of Communication and Political Science, UPNVJ University, Indonesia
Keywords: Tone Indicators, Neurodivergent Community, Twitter

Abstract

Miscommunication happens often in social media, especially in text-based environment where tone can be non-existent for the readers. Tone indicators are introduced to help ease the process of message interpretation by indicating the tone or context delivered in text. The neurodivergent community has found this tool to be beneficial and utilise it in their day-to-day communication in social media, especially Twitter where the majority of content comes in text. This study presents a qualitative analysis of how the community the define tone indicators through interaction symbolic theory. The result indicated that tone indicators not only helped clarify the tone or context in text, but also emphasized the expression or emotion conveyed as well as minimizing the misinterpretation of messages. Tone indicators had also shaped the behaviour taken during communication online and provide an inclusive digital space. Result has provided insights on the community and tone indicators in social media.

References

Bandur, A. (2019). Penelitian Kualitatif: Studi Multi-Disiplin Keilmuan dengan NVivo 12 Plus. Bogor: Mitra Wacana Media.

Borst, G., & Kosslyn, S. M. (2010). Fear Selectively Modulates Visual Memory, Mental Imagery, and Visual Perception. The Quarterly Hournal of Experimental Psychology, 833-839.

Crystal, D. (2001). Language and The Internet. New York: Cambridge University Press.

Davidov, D., Tsur, O., & Rappoport, A. (2010). Semi-Supervised Recognition of Sarcastic Sentences in Twitter and Amazon. Dmitry Proceeding of Computitational Natural Language Learning (ACL-CoNLL).

Department, S. R. (2021, June 30). Distribution of Twitter Users Worldwide as of April 2021, by Age Group. Retrieved July 21, 2021, from Statista: https://www.statista.com/statistics/283119/age-distribution-of-global-twitter-users/

Derks, D., Bos, A. R., & Grumbkow, J. v. (2008). Emoticons and Online Message Interpretation. Social Science Computer Review, 379-388.

Edwards, R., Bybee, B. T., Frost, J. K., Harvey, A. J., & Navarro, M. (2016). That's Not What I Meant: How Misunderstanding Is Related to Channel and Perspective-Taking. Journal of Language ad Social Psychology, 188-210.

Ellis, K., & Kent, M. (2017). Disability and Social Media: Global Perspective. Nem York: Taylor & Francis Group.

Emojipedia. (n.d.). Slightly Smiling Face. Retrieved September 27, 2021, from Emojipedia: https://emojipedia.org/slightly-smiling-face/

Fuchs, C. (2017). Fascism 2.0: Twitter User' Social Media Memories of Hitler on his 127th Birthday. Fascism, 6(2), 228-263.

Gillespie, A., & Cornish, F. (2010). Intersubjectivity: Towards A Dialogical Analysis. Journal For The Theory of Social Behaviour, 19-46.

Gillespie, A., & Zittoun, T. (2010). Conceptualizing The Mediation and Reflective Use Of Tools and Signs. Culture & Psychology, 37-62.

Gillespie, A., & Zittoun, T. (2010). Using Resources: Conceptualizing The Mediation and Reflective Use Of Tools and Signs. Culture & Psychology, 37-62.

Grundy, P. (2000). Doing Pragmatics. New York: Oxford University Press.

Heasman, B., & Gillespie, A. (2019). Neurodivergent Intersubjectivity: Distinctive Features of How Autistic People Create Shared Understanding. Autism, 910-921.

Herring, S. (1996). Computer-mediated Communication: Linguistic, social and cross-cultural perspectives. Amsterdam: Benjamins.

Kiesler, S., & Sproull, L. (1992). Group decision-making and communication technology. Organization Behavior and Human Decision Processes, 96-123.

Kozinets, R. V. (2015). Netnography: Redefined. London: SAGE.

Lea, M., & Spears, R. (1992). Paralanguage and Social Perception in Computer Mediated Communication. Journal of Organizational Computing, 321-341.

Luangrath, A. W., Peck, J., & Barger, V. A. (2016). Textual Paralanguage and Its Implications for Marketing Communication. Journal of Consumer Psychology, 98-107.

Marcus, E. (2020, December 9). Tone Is Hard To Grasp Online. Can Tone Indicators Help? Retrieved May 15, 2021, from The New York Times: https://www.nytimes.com/2020/12/09/style/tone-indicators-online.html

Negrete, G., & McManus, T. G. (2021). "Okay Twitter... trend this, sucka! #Supernatural": A Content Analysis of the Supernatural Fandom's Use of Live-Tweeting. The Journal of Social Media in Society, 10 (1), 162-181.

NIDCD. (2020, April 13). Autism Spectrum Disorder: Communication Problems in Children. Retrieved July 22, 2021, from National Institute on Deafness and Other Communication Disorders: https://www.nidcd.nih.gov/health/autism-spectrum-disorder-communication-problems-children

Poster, M. (2018). The Second Media Age. John Wiley & Sons.

Rainey, V. P. (2000). The Potential for Miscommunication Using E-mail as a Source of Communication. Journal of Integrated Design and Process Science, 21-43.

Soliha, S. F. (2015). Tingkat Ketergantungan Pengguna Media Sosial dan Kecemasan Sosial. Interaksi: Jurnal Ilmu Komunikasi, 4 (1), 1-10.

Statista. (2021, September 7). Countries with the most Twitter users 2021. Retrieved September 27, 2021, from Statista Research Department: https://www.statista.com/statistics/242606/number-of-active-twitter-users-in-selected-countries/

Sugiyono. (2017). Metode Penelitian Pendidikan Pendekatan Kuantitatif, Kualitatif, dan R&D. Bandung: Alfabeta.

Team, E. R. (2016, November 16). Emoji Report. Retrieved July 21, 2021, from Emogi: http://cdn.emogi.com/docs/reports/2016_emoji_report.pdf

Thurlow, C., Lengel, L., & Tomic, A. (2004). Computer Mediated Communication: Social Interaction and The Internet. London: SAGE Publications Ltd.

Tungthamthiti, P., Shirai, K., & Mohd, M. (2016). Recognition of Sarcasm in Microblogging Based on Sentiment Analysis and Coherence Identification. Journal of Natural Language Processing 23(5), 383-405.

Walther, J. (2011). Theories of Computer-Mediated Communication and Interpersonal Communication. The SAGE Handbook of Interpersonal Communication, 443-479.

Walther, J., & Parks, M. (2002). Cues filtered out, cues filtered in: computer-mediated communication in relationships. In M. Knapp, & J. Daly, Handbook of interpersonal communication (p. 529). Thousand Oaks, CA: Sage.

Published
2022-01-03
How to Cite
Febiana Christanti, M., Bestari Mardani, P., & Fadhila, K. (2022). Analysing The Meaning Of Tone Indicators By Neurodivergent Community in Twitter. International Journal of Social Science Research and Review, 5(1), 5-15. https://doi.org/10.47814/ijssrr.v5i1.118