Main Article Content
Abstract
Miscommunication is common in text-based social media platforms like Twitter/X for a number of reasons. Misunderstandings may result from interactions that lack clear communication and tone of voice. As a result, tone indicators were created to represent the focus on tone in a text message. The aim of this research was to investigate the use of tone indicators and the effects they have on the audience. The analysis was conducted by investigating the audience's experience with tone indicators and the subsequent methods used to collect responses. The research employed a qualitative methodology. After using a purposive sampling strategy, seven informants were chosen. The study's findings demonstrated the value of tone indicators in social media communication on platforms like Twitter/X. When talking in a community, the audience or participants sense this tone indicator.
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References
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References
Alam, Md. K. (2020). A systematic qualitative case study: Questions, data collection, NVivo analysis and saturation. Qualitative Research in Organizations and Management: An International Journal, 16(1), 1–31. https://doi.org/10.1108/QROM-09-2019-1825
Boren, R. (2023). Tone indicators. Stimpunks Foundation. https://stimpunks.org/glossary/tone-indicators/
Cambridge Dictionary. (2024, May 10). Tone | English meaning—Definition of tone from the Cambridge academic content dictionary. Dictionary.Cambridge.Org. https://dictionary.cambridge.org/dictionary/english/tone
Carr, C. T. (2021). Computer-mediated communication: A theoretical and practical introduction to online human communication. Rowman & Littlefield.
Dellantonio, S., & Pastore, L. (2021). Ignorance, misconceptions and critical thinking. Synthese, 198(8), 7473–7501. https://doi.org/10.1007/s11229-019-02529-7
Diyora, N., & Mirzayev, A. (2023). The role of paralinguistic tools in the communication process. Zenodo. https://doi.org/10.5281/zenodo.7513328
Christanti, M. F., Mardani, P. B., & Fadhila, K. A. (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
Holtgraves, T. (2021). Understanding miscommunication: Speech act recognition in digital contexts. Cognitive Science, 45(10). https://doi.org/10.1111/cogs.13023
Hu, T., Xu, A., Liu, Z., You, Q., Guo, Y., Sinha, V., Luo, J., & Akkiraju, R. (2018). Touch your heart. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, 1–12. https://doi.org/10.1145/3173574.3173989
Juditha, C. (2018). Hoax communication interactivity in social media and anticipation (interaksi komunikasi hoax di media sosial serta antisipasinya). Journal Pekommas, 3(1), 31. https://doi.org/10.30818/jpkm.2018.2030104
Kang, I., Cui, H., & Son, J. (2019). Conformity consumption behavior and FoMO. Sustainability, 11(17), 4734. https://doi.org/10.3390/su11174734
Marcus, E., & O’Neill, S. (2020). Tone is hard to grasp online. Can tone indicators help? The New York Times. https://www.nytimes.com/2020/12/09/style/tone-indicators-online.html
Miles, M. B., Huberman, A. M., & Saldana, J. (2013). Qualitative data analysis: A methods sourcebook (3rd ed.). SAGE Publications.
Rahman, A. F. (2022). Sejarah emoji, ikon yang sering dipakai berkomunikasi seantero dunia. Detikinet. https://inet.detik.com/inetgrafis/d-5076548/sejarah-emoji-ikon-yang-sering-dipakai-berkomunikasi-seantero-dunia
Solomon, D., & Theiss, J. (2022). Interpersonal communication: Putting theory into practice (2nd ed.). Routledge.
Wang, N., Yin, J., Ma, Z., & Liao, M. (2022). The influence mechanism of rewards on knowledge sharing behaviors in virtual communities. Journal of Knowledge Management, 26(3), 485–505. https://doi.org/10.1108/JKM-07-2020-0530
Wijenayake, S., van Berkel, N., Kostakos, V., & Goncalves, J. (2020). Impact of contextual and personal determinants on online social conformity. Computers in Human Behavior, 108, 106302. https://doi.org/10.1016/j.chb.2020.106302
Winans, M. D. (2021). Grammarly’s tone detector: Helping students write pragmatically appropriate texts. RELC Journal, 52(2), 348–352. https://doi.org/10.1177/00336882211010506
Wu, R., Chen, J., Lu Wang, C., & Zhou, L. (2022). The influence of emoji meaning multipleness on perceived online review helpfulness: The mediating role of processing fluency. Journal of Business Research, 141, 299–307. https://doi.org/10.1016/j.jbusres.2021.12.037