POLA BAHASA PADA INDIVIDU DENGAN KECENDERUNGAN DEPRESI DI MEDIA SOSIAL: SEBUAH KAJIAN PSIKOLINGUISTIK

Firdhaniaty Rachmania

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


Full Text:

PDF

References


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

Copyright (c) 2025 Firdhaniaty Rachmania

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Editorial address:

Fakultas Ilmu Budaya, Universitas Mulawarman
Address: Jl. Ki Hajar Dewantara, Gunung Kelua, Kec. Samarinda Ulu, Kota Samarinda, Kalimantan Timur, Indonesia 75123
Email: jurnalcalls@fib.unmul.ac.id
Website: http://e-journals.unmul.ac.id/index.php/CALLS

 

Creative Commons License  
CaLLs: Journal of Culture, Arts, Literature, and Linguistics site is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License


CaLLs: Journal of Culture, Arts, Literature, and Linguistics indexing by:

Sinta Crossref Garuda Google Scholar Neliti Base Dimensions Portal ISSN DOAJ