ac

Text as a Social Network Analysis Topography And Political Communication In Indonesia

Penulis

  • Heri Heryono Heryono Universitas Widyatama, Indonesia
  • Dani Hamdani Universitas Widyatama, Indonesia
  • Ari Purno Wahyu Universitas Widyatama, Indonesia

DOI:

10.47709/brilliance.v4i1.3645

Kata Kunci:

texts, social network analysis, political communication

Dimension Badge Record



Abstrak

Political communication has a central role in shaping public opinion and political dynamics in Indonesia. This research aims to investigate the role of text in the context of Social Network Analysis (SNA) and political communication in Indonesia. This research combines NLP (Natural Language Processing) text analysis with SNA to understand how texts related to politics can provide insight into the relationship between political figures, political issues, and society. The research methodology involves collecting text data from various sources, such as social media, online news, blogs, and political discussion forums. The text data is then processed, analyzed and modeled with SNA analysis tools and NLP algorithms to identify relationships and communication patterns in a political context. In addition, this research also considers how the sentiments in these texts can influence the dynamics of sociopolitical networks. It is hoped that the results of this research will provide a deeper understanding of how political texts can be used as a tool for SNA analysis, with a focus on the Indonesian context. The findings of this research can be useful for political researchers, communication practitioners, and political decision makers to understand the political dynamics that are developing in the digital era. Apart from that, this research also has implications in understanding how political issues and political figures are understood and perceived by the public in political communication in Indonesia.

Google Scholar Cite Analysis
Abstrak viewed = 94 times

Referensi

A. F. Hidayatullah, et al. (2014). Analisis sentimen dan klasifikasi kategori terhadap tokoh publik pada twitter. vol. 2014, no. semnasIF, pp. 115–122, 2014.

Bach, R.L. & Wenz, A. (2020) Studying health-related internet and mobile device use using web logs and smartphone records. PloS ONE, 15(6), e0234663.

Bosch, O.J. & Revilla, M. (2021) When survey science met online tracking: presenting an error framework for metered data. RECSM Working Paper Number 62. Available from: https://repositori.upf.edu/bitstream/ handle/10230/46482/RECSMwp62.pdf?sequence=1&isAllowed=y

D. Ayu, P. Wulandari, M. Sudarma, dan N. Pramaita. (2019). Pemanfaatan Big Data Media Sosial Dalam Menganalisa Kemenangan Pilkada. Majalah Ilmiah Teknologi Elektro, Vol. 18, No. 1, Januari - April 2019 DOI: https://doi.org/10.24843/MITE.2019.v18i01.P15

DiGrazia, J., McKelvey, K., Bollen, J. & Rojas, F. (2013). More tweets, more votes: Social media as a quantitative indicator of political behavior. PLoS ONE 8, e79449 (2013).

Gentzkow, M. & Shapiro, J.M. (2011) Ideological segregation online and offline. The Quarterly Journal of Economics, 126(4), 1799–1839.

Garimella, K., De Francisci Morales, G., Gionis, A. & Mathioudakis, M. (2018). Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship. In: Te Web Conference 2018—Proceedings of the World Wide Web Conference, WWW 2018 913–922 (Association for Computing Machinery, Inc, 2018). https://doi.org/10.1145/3178876.3186139.

Gruzd, Anatoliy, and Jeffrey Roy (2014). Investigating Political Polarization on Twitter: A Canadian Perspective. Policy Internet 6(2)

Guess, A.M., Nyhan, B., O’Keeffe, Z. & Reifler, J. (2020) The sources and correlates of exposure to vaccine-related (mis) information online. Vaccine, 38(49), 7799–7805.

Hao Wang, Dogan Can, Abe Kazemzadeh, Franc ?ois Bar, and Shrikanth Narayanan. (2012). A system for real-time Twitter sentiment analysis of the 2012 U.S. presidential election cycle. In ACL (System Demonstrations).

Ibrahim, V., Bakar, J. A., Harun, N. H., & Abdulateef, A. F. (2021). A word cloud model based on hate speech in an online social media environment. Baghdad Science Journal, 18, 937–946. https://doi.org/10.21123/bsj.2021.18.2(Suppl.).0937

J. Han, M. Kamber and J. Pei. (2012). Rule-Based Classification in Data Mining : Concepts and Techniques. Morgan Kaufmann, 2012, pp. 355-357.

Konstantinas, Paulius dan Gintautas. (2017). SVM and Na?ve Bayes Classification Ensemble Method for Sentiment Analysis. Baltic J. Modern Computing, vol.5. no.4, pp. 398–409, 2017

Liu, Bing. (Ed.). (2012). Sentiment Analysis and Opinion Mining. Graeme Hirst, University of Toronto

Murphy Choy, Michelle L. F. Cheong, Ma Nang Laik, and Koo Ping Shung. (2011). A sentiment analysis of Singapore Presidential Election 2011 using Twitter data with census correction. CoRR, abs/1108.5520.

Pak, Alexander and Paroubek, Patrick. (2010). Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10).

Qiu, L., Lin, H., Ramsay, J., dan Yang, F. (2012). You are what you tweet: Personality expression and perception on Twitter. Division of Psychology, Singapore. Science Direct. Pp.710-718.

Rudat, A. & Buder, J. (2015). Making retweeting social: The influence of content and context information on sharing news on Twitter. Comput. Hum. Behav. 46, 75–84 (2015).

S. Vijayarani, J. Ilamathi and Nithya. (2015). Preprocessing Techniques for Text Mining - An Overview. International Journal of Computer Science & Communication Networks, vol. V, no. 1, pp. 7-16, 2015.

Snow, R., O’Connor, B., Jurafsky, D., Ng, A.Y. (2008). Cheap and fast—but is it good? Evaluating non-expert annotations for natural language tasks. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2008), Honolulu, Hawaii, 25–27 October, pp. 254–263 (2008)

Stier, S., Kirkizh, N., Froio, C. & Schroeder, R. (2020) Populist attitudes and selective exposure to online news: a cross-country analysis combining web tracking and surveys. The International Journal of Press/Politics, 25(3), 426–446.

Werayawarangura, N., Pungchaichan, T., & Vateekul, P. (2016). Social network analysis of calling data records for identifying influencers and communities. 2016 13th International Joint Conference on Computer Science and Software Engineering, JCSSE 2016. https://doi.org/10.1109/JCSSE.2016.77 48864

##submission.downloads##

ARTICLE Diterbitkan HISTORY

Submitted Date: 2024-02-23
Accepted Date: 2024-02-24
Published Date: 2024-03-08

Cara Mengutip

Heryono, H. H., Hamdani, D., & Purno Wahyu, A. (2024). Text as a Social Network Analysis Topography And Political Communication In Indonesia. Brilliance: Research of Artificial Intelligence, 4(1), 19-24. https://doi.org/10.47709/brilliance.v4i1.3645