Big Data and Netnography Analysis of Mental Health on Twitter/X: Evidence From Indonesia

Authors

  • Tika Mutia Universitas Padjadjaran
  • Jenny Ratna Suminar Universitas Padjadjaran
  • Susanne Dida Universitas Padjadjaran
  • Herlina Agustin Universitas Padjadjaran

DOI:

https://doi.org/10.37385/jaets.v6i1.6226

Keywords:

Big Data, Mental Health, Netnography, Thread, X

Abstract

Digital traces of mental health conversations on social media X have become a new culture, especially for the young generation. This study aimed to explain the network, themes and comment of social media discussion posts about mental health in Indonesia. This study has focused on each conversation in the form of tweets using big data analysis from posts with containing keyword related and specific criteria on the theme of mental health. This research was collected 15,200 mental health-themed discussions on X. Further, the researcher conducted a selection based on engagement and specific criteria through the NoLimit tool in 2021. A total of 4969 threads were analyzed further. As a result, researchers found a network that formed 3 clusters, namely the Stress cluster, Depression cluster, and Bipolar cluster. Apart from that, three big themes were found that represent every conversation on social media X in Indonesia, namely, (1) The Story of Survivors, (2) Mental Health as a Trend and Fashion, (3) Stress, Anxiety, or just a Gerd? Through the study of netnography, it is revealed that social media serves as a community's backbone while also perpetuating stigma related to mental health issues. Mental health in Indonesia is still an issue that does not get serious attention, even though the number of cases of mental disorders continues to increase.

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Published

2024-12-15

How to Cite

Mutia, T., Suminar, J. R., Dida, S., & Agustin, H. (2024). Big Data and Netnography Analysis of Mental Health on Twitter/X: Evidence From Indonesia. Journal of Applied Engineering and Technological Science (JAETS), 6(1), 300–315. https://doi.org/10.37385/jaets.v6i1.6226