Social Data Analytics sebagai Metode Alternatif dalam Riset Psikologi

Cleoputri Yusainy(1*), Anif Fatma Chawa(2), Siti Kholifah(3)

(1) Universitas Brawijaya
(2) Jurusan Psikologi FISIP Universitas Brawijaya
(3) Jurusan Psikologi FISIP Universitas Brawijaya
(*) Corresponding Author


The usage of technological based utilities has been increasing rapidly in our daily life. This phenomenon breeds two fundamental changes: Data explosion and social structures. It takes a different approach to gain insights and benefits from the phenomenon. In psychological science, the acquintance of alternative methods to keep up with the problems should be a necessity. This article introduces two social media data analytical techniques, namely (i) sentiment analysis as the process of computationally identifying, extracting, and quantifying the affective condition towards a particular target, and (ii) social network analysis (SNA) as the process of investigating social structures through the use of Graph Theory dan Network Science. Overviews are presented in general terms with expectation to bring quality of research in Psychology to the next level.


social network analysis (SNA); analisis sentimen; Psikologi


Barabási, A-L. (2016). Network Science. Cambridge: Cambridge University Press.

Bollen, J., Mao, H., & Zeng, X. (2011) Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8.

Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing Social Networks. Los Angeles: Sage Publications.

Easley, D., & Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. New York: Cambridge University Press.

Grimm, K., Jacobucci, R., McArdle, J. J. (Januari 2017). Big data methods and psychological science: Finding meaning in large (and small) sets of psychological data. Psychological Science Agenda, American Psychological Science. Diunduh dari EMC

Education Services. (2015). Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data. Indianapolis, Indiana:

Wiley Kadushin, C. (2012). Understanding Social Networks. New York: Oxford University Press.

Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6, 70-73.

Lerman, K., Yan, X., Wu, X-Z (2016). The "majority illusion" in social networks. PLoS ONE 11(2): e0147617.

Liu, B. (2015). Sentiment Analysis: Mining Opinions, Sentiments, and Emotions. New York: Cambridge University Press.

Magdy, W., Darwish, K., & Weber, I. (2015). #FailedRevolutions: Using Twitter to study the antecedents of ISIS support. Cornell University Library.

Ruths, D., & Pfeffer, J. (2014). Supplemental material for Social media for large studies of behavior. Science, 346(6213), 1063-1064.

Scott, J. (2013). Social Network Analysis, 3rd ed. London: Sage.

Simonton, D. K. (2015). Psychology as a science within Comte's hypothesized hierarchy: Empirical investigations and conceptual implications. Review of General Psychology, 19, 334-344.

We Are Social. (Januari 2017). Digital in 2017: Southeast Asia Regional Overview. Diunduh dari

Yusainy, C. (2015). Quo vadis Psikologi sebagai sebuah kajian ilmiah? Buletin Psikologi, 23(1), 51-56.

Yusainy, C., Chawa, A. F., & Kholifah, S. (2017). Reduksi stigma-publik kepada penyandang disabilitas fisik dan mental: social listening dan pemberdayaan komunitas. Laporan Penelitian Berbasis Kompetensi. Kementerian Riset, Teknologi, dan Pendidikan Tinggi.


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