POLA BAHASA PADA INDIVIDU DENGAN KECENDERUNGAN DEPRESI DI MEDIA SOSIAL: SEBUAH KAJIAN PSIKOLINGUISTIK
Abstract
Depresi menduduki posisi sebagai salah satu gangguan mental yang paling umum di dunia. Perkembangan teknologi mendukung upaya pendeteksian kecenderungan depresi melalui bahasa yang termuat dalam konten media sosial. Penelitian kualitatif ini menggunakan studi literatur untuk menghimpun informasi dari penelitian-penelitian yang dominan dilakukan di luar negeri tentang pola-pola bahasa pada individu dengan kecenderungan depresi di media sosial. Hasil penelitian menunjukkan adanya pola-pola bahasa berupa: (1) postingan dikategorikan bermuatan ekspresi emosional, dukungan dan informasi, atau ekspresi kontekstual; (2) penggunaan kata-kata absolut; (3) gaya linguistik berupa pemilihan kata yang memuat emosi negatif, kata yang berfokus pada masa lalu, dan urutan kata yang tidak biasa; (4) penggunaan kata ganti orang pertama tunggal; dan (5) narasi konten yang sangat panjang atau sangat pendek.
Kata kunci: pola bahasa, depresi, media sosial, psikolinguistik
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Ahmad, A. (2020). Media sosial dan tantangan masa depan generasi milenial. Avant Garde, 8(2), 134. https://doi.org/10.36080/ag.v8i2.1158
Al-Mosaiwi, M. (2018). The impact of absolute thinking on wellbeing (University of Reading). University of Reading. Retrieved from https://core.ac.uk/reader/275551790
Al-Mosaiwi, M., & Johnstone, T. (2018). In an absolute state: Elevated use of absolutist words as a marker specific to anxiety, depression, and suicidal ideation. Clinical Psychological Science, 6(4), 529–542. https://doi.org/10.1177/2167702617747074
Aldarwish, M. M., & Ahmad, H. F. (2017). Predicting depression levels using social media posts. 2017 IEEE 13th International Symposium on Autonomous Decentralized System (ISADS), 277–280. IEEE. https://doi.org/10.1109/ISADS.2017.41
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-V) (5th ed.). Arlington: American Psychiatric Association Publishing.
Andalibi, N., Ozturk, P., & Forte, A. (2017). Sensitive self-disclosures, responses, and social support on instagram: The case of #depression. Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW), 1485–1500. https://doi.org/10.1145/2998181.2998243
Bembnowska, M., & Jośko-Ochojska, J. (2015). What causes depression in adults? Polish Journal of Public Health, 125(2), 116–120. https://doi.org/10.1515/pjph-2015-0037
Carroll, D. W. (2008). Psychology of language (5th ed.). Belmont: Thomson Wadsworth.
Chung, C., & Pennebaker, J. (2007). The psychological functions of function words. In K. Fiedler (Ed.), Social communication (pp. 343–359). New York: Psychology Press. https://doi.org/10.4324/9780203837702
Coppersmith, G., Ngo, K., Leary, R., & Wood, A. (2016). Exploratory analysis of social media prior to a suicide attempt. Proceedings of the 3rd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, CLPsych 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Lan, 106–117. https://doi.org/10.18653/v1/w16-0311
De Choudhury, M., & De, S. (2014). Mental health discourse on reddit: Self-disclosure, social support, and anonymity. Proceedings of the 8th International Conference on Weblogs and Social Media, ICWSM 2014, 71–80. https://doi.org/10.1609/icwsm.v8i1.14526
De Choudhury, M., Gamon, M., Counts, S., & Horvitz, E. (2022). Predicting depression through social media. Lecture Notes on Data Engineering and Communications Technologies, 128, 109–127. https://doi.org/10.1007/978-981-19-1724-0_6
Dewing, M. (2012). Social Media: An Introduction. Library of Parliament, 1–5.
Dirgayunita, A. (2016). Depresi: Ciri, penyebab dan penangannya. Journal An-Nafs: Kajian Penelitian Psikologi, 1(1), 1–14. https://doi.org/10.33367/psi.v1i1.235
Edwards, T., & Holtzman, N. S. (2017). A meta-analysis of correlations between depression and first person singular pronoun use. Journal of Research in Personality, 68, 63–68.
Fatima, I., Abbasi, B. U. D., Khan, S., Al-Saeed, M., Ahmad, H. F., & Mumtaz, R. (2019). Prediction of postpartum depression using machine learning techniques from social media text. Expert Systems, 36(4), 1–13. https://doi.org/10.1111/exsy.12409
Field, J. (2004). Psycholinguistics: The key concepts. London: Routledge. https://doi.org/10.1016/j.system.2004.12.005
Howitt, D. (2010). Introduction to qualitative methods in psychology. Harlow: Pearson Education Limited.
Hussain, J., Satti, F. A., Afzal, M., Khan, W. A., Bilal, H. S. M., Ansaar, M. Z., … Lee, S. (2020). Exploring the dominant features of social media for depression detection. Journal of Information Science, 46(6), 739–759. https://doi.org/10.1177/0165551519860469
Islam, M. R., Kabir, M. A., Ahmed, A., Kamal, A. R. M., Wang, H., & Ulhaq, A. (2018). Depression detection from social network data using machine learning techniques. Health Information Science and Systems, 6(1), 1–12. https://doi.org/10.1007/s13755-018-0046-0
KBBI Daring. (2016). Media Sosial. Retrieved March 27, 2021, from https://kbbi.kemdikbud.go.id/entri/media sosial
Kemenkes RI. (2018). Laporan Nasional Riskesdas. Jakarta. Retrieved from http://www.yankes.kemkes.go.id/assets/downloads/PMK No. 57 Tahun 2013 tentang PTRM.pdf
Menn, L. (2017). Psycholinguistics: Introduction and applications (2nd ed.). San Diego: Plural Publishing. Retrieved from https://search.proquest.com/docview/2131108059?accountid=8630 https://birmingham-primo.hosted.exlibrisgroup.com/openurl/44BIR/44BIR_Services?genre=book&issn=&title=Psycholinguistics%3A+Introduction+and+Applications%2C+Second+Edition&volume=&issue=&date=20
Miller, D., Costa, E., Haynes, N., McDonald, T., Nicolescu, R., Sinanan, J., … Wang, X. (2018). How the World Changed Social Media. London: UCL Press. https://doi.org/10.2307/j.ctt1g69z35
Narynov, S., Mukhtarkhanuly, D., & Omarov, B. (2020). Dataset of depressive posts in Russian language collected from social media. Data in Brief, 29, 105195. https://doi.org/10.1016/j.dib.2020.105195
Nguyen, T., Phung, D., Dao, B., Venkatesh, S., & Berk, M. (2014). Affective and content analysis of online depression communities. IEEE Transactions on Affective Computing, 5(3), 217–226. https://doi.org/10.1109/TAFFC.2014.2315623
Pamungkas, G. A. (2019). Gangguan produksi dan komprehensif ujaran pada penderita depresi. SENASBASA (Seminar Nasional Bahasa Dan Sastra, 3(2), 381–389. Retrieved from http://research-report.umm.ac.id/index.php/
Park, M., Cha, C., & Cha, M. (2012). Depressive moods of users portrayed in Twitter. Proceedings of the ACM SIGKDD Workshop on Healthcare Informatics (HI-KDD), 2012, 1–8.
Pennebaker, J.W., Francis, M. E., & Booth, R. J. (2007). Linguistic Inquiry and Word Count [Computer software]. LIWC Inc
Sagiyanto, A., & Ardiyanti, N. (2018). Self disclosure melalui media sosial Instagram (Studi kasus pada anggota Galeri Quote). Nyimak (Journal of Communication), 2(1), 81–94. https://doi.org/10.31000/nyimak.v2i1.687
Schlosser, A. E. (2020). Self-disclosure versus self-presentation on social media. Current Opinion in Psychology, 31, 1–6. https://doi.org/10.1016/j.copsyc.2019.06.025
Shrestha, A., Serra, E., & Spezzano, F. (2020). Multi-modal social and psycho-linguistic embedding via recurrent neural networks to identify depressed users in online forums. Network Modeling Analysis in Health Informatics and Bioinformatics, 9(22), 1–11. https://doi.org/10.1007/s13721-020-0226-0
Smirnova, D., Cumming, P., Sloeva, E., Kuvshinova, N., Romanov, D., & Nosachev, G. (2018). Language patterns discriminate mild depression from normal sadness and euthymic state. Frontiers in Psychiatry, 9(105), 1–11. https://doi.org/10.3389/fpsyt.2018.00105
Snyder, H. (2019). Literature review as a research methodology: An overview and guidelines. Journal of Business Research, 104, 333–339. https://doi.org/10.1016/j.jbusres.2019.07.039
Suharti, S., Khusnah, W. D., Ningsih, S., Shiddiq, J., Saputra, N., Kuswoyo, H., … Purba, J. H. (2021). Kajian psikolinguistik. Pidie: Yayasan Penerbit Muhammad Zaini.
Tadesse, M. M., Lin, H., Xu, B., & Yang, L. (2019). Detection of depression-related posts in reddit social media forum. IEEE Access, 7, 44883–44893. https://doi.org/10.1109/ACCESS.2019.2909180
Trifan, A., Antunes, R., Matos, S., & Oliveira, J. L. (2020). Understanding depression from psycholinguistic patterns in social media texts. In J. M. Jose, E. Yilmaz, J. Magalhães, P. Castells, N. Ferro, M. J. Silva, & F. Martins (Eds.), Advances in Information Retrieval (pp. 402–409). Springer Cham. https://doi.org/10.1007/978-3-030-45442-5
Vanlalawmpuia, R., & Lalhmingliana, M. (2020). Prediction of depression in social network sites using data mining. Proceedings of the International Conference on Intelligent Computing and Control Systems, ICICCS 2020, 489–495. https://doi.org/10.1109/ICICCS48265.2020.9120899
WHO. (2017). Depression and Other Common ental Disorders: Global Health Estimates. Geneva. Retrieved from http://apps.who.int/iris
Zafarani, R., Abbasi, M. A., & Liu, H. (2014). Social media mining: An introduction. Cambridge University Press. https://doi.org/10.1017/CBO9781139088510
Zimmermann, J., Brockmeyer, T., Hunn, M., Schauenburg, H., & Wolf, M. (2017). First-person pronoun use in spoken language as a predictor of future depressive symptoms: Preliminary evidence from a clinical sample of depressed patients. Clinical Psychology and Psychotherapy, 24(2), 384–391. https://doi.org/10.1002/cpp.2006
DOI: http://dx.doi.org/10.30872/calls.v11i2.15000
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