Main Article Content

Abstract

This study examines how public perceptions of Anies Baswedan are shaped through YouTube, Twitter, and Google, employing text, network, and sentiment analysis with InfraNodus. Data was collected through each platform's official API with a focus on the keyword "Anies Baswedan." The findings reveal that informative narratives dominate YouTube, while Twitter serves as a space for emotional expression, characterized by a high level of positive sentiment. At the same time, Google reflects information-seeking behavior with a more balanced sentiment distribution. These findings reveal that each platform plays a unique role in shaping political perceptions: YouTube archives and disseminates documentation, and Twitter serves as a forum for debate and support. At the same time, Google functions as an aggregator of opinions from various sources. This study offers new insights into how cross-platform interactions are influenced not only by the content of messages but also by communication patterns and the digital ecosystem in which conversations occur, thereby strengthening our understanding of how political narratives evolve in the digital age.

Keywords

anies baswedan jakarta politics sentiment analysis social networks digital media

Article Details

Author Biographies

Herman Lawelai, Department of Government Studies, Faculty of Political and Social Sciences, Universitas Muhammadiyah Buton, Baubau, Indonesia.

Department of Government Studies

Achmad Nurmandi, Department of Government Affairs and Administration, Jusuf Kalla School of Government, Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia.

Department of Government Affairs and Administration, Jusuf Kalla School of Government

Harry Fajar Maulana, Department of Communication Science, Faculty of Political and Social Sciences, Universitas Muhammadiyah Buton, Baubau, Indonesia.

Department of Communication Science

Hasse Jubba, Department of Political Islam-Political Science, Graduate School, Universitas Muhammadiyah Yogyakarta, Yogyakarta, Indonesia

Department of Political Islam-Political Science

How to Cite
Lawelai, H., Nurmandi, A., Maulana, H. F., & Jubba, H. (2025). InfraNodus analysis of text, networks, and sentiment on a political actor across media platforms. Jurnal Komunikasi, 19(3), 491–516. https://doi.org/10.20885/komunikasi.vol19.iss3.art5

References

  1. Alim, A. S., & Rahmawati, D. E. (2021). Komunikasi Politik Anies Baswedan Melalui Sosial Media Twitter. Jurnal Academia Praja, 4(2), 441–453. https://doi.org/10.36859/jap.v4i2.334
  2. Alsinet, T., Argelich, J., Béjar, R., & Cemeli, J. (2019). A distributed argumentation algorithm for mining consistent opinions in weighted Twitter discussions. Soft Computing, 23(7), 2147–2166. https://doi.org/10.1007/s00500-018-3380-x
  3. Angus, D., & Wiles, J. (2018). Social semantic networks: Measuring topic management in discourse using a pyramid of conceptual recurrence metrics. Chaos, 28(8). https://doi.org/10.1063/1.5024809
  4. Anom, E., Vina, E., & Samani, M. C. (2024). Political Communication Strategy in the 2024 Indonesia’s Presidential Election. Jurnal Komunikasi: Malaysian Journal of Communication, 40(2), 296–309. https://doi.org/10.17576/JKMJC-2024-4002-17
  5. Arman, Z. R., & McClurg, S. (2024). Exploring the Relationship Between Televised Presidential Debate and Twitter: A Network Analysis of Intermedia Agenda Setting. Communication Studies, 75(6), 861–879. https://doi.org/10.1080/10510974.2024.2342062
  6. Bajari, A., Koswara, I., Istiqomah, R. N., & Erlandia, D. R. (2021). Hatenography On Twitter During the Covid-19 Pandemic in Indonesia: Hate Speech Case Against Anies Baswedan. Review of International Geographical Education Online, 11(5), 68–78. https://doi.org/10.48047/rigeo.11.05.07
  7. Blondel, V. D., Guillaume, J.-L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008. https://doi.org/10.1088/1742-5468/2008/10/P10008
  8. Bruns, A., & Stieglitz, S. (2012). Quantitative Approaches to Comparing Communication Patterns on Twitter. Journal of Technology in Human Services, 30(3–4), 160–185. https://doi.org/10.1080/15228835.2012.744249
  9. Budi, A., & Pamungkas, W. A. (2020). Partisanship in crisis: Public response to covid-19 pandemic in Indonesia. Jurnal Ilmu Sosial Dan Ilmu Politik, 24(1), 15–32. https://doi.org/10.22146/JSP.56443
  10. Capano, G., Galanti, M. T., & Barbato, G. (2023). When the political leader is the narrator: the political and policy dimensions of narratives. Policy Sciences, 56(2), 233–265. https://doi.org/10.1007/s11077-023-09505-6
  11. Chandrasekar, A., Clark, S. E., Martin, S., Vanderslott, S., Flores, E. C., Aceituno, D., Barnett, P., Vindrola-Padros, C., & Vera San Juan, N. (2024). Making the most of big qualitative datasets: a living systematic review of analysis methods. Frontiers in Big Data, 7, 1455399. https://doi.org/10.3389/fdata.2024.1455399
  12. Dayter, D. (2015). Small stories and extended narratives on Twitter. Discourse, Context and Media, 10, 19–26. https://doi.org/10.1016/j.dcm.2015.05.003
  13. Dongo, I., Cardinale, Y., Aguilera, A., Martinez, F., Quintero, Y., Robayo, G., & Cabeza, D. (2021). A qualitative and quantitative comparison between Web scraping and API methods for Twitter credibility analysis. International Journal of Web Information Systems, 17(6), 580–606. https://doi.org/10.1108/IJWIS-03-2021-0037
  14. Gamal, D., Alfonse, M., El-Horbaty, E.-S. M., & Salem, A.-B. M. (2019). Implementation of Machine Learning Algorithms in Arabic Sentiment Analysis Using N-Gram Features. Procedia Computer Science, 154, 332–340. https://doi.org/10.1016/j.procs.2019.06.048
  15. Gerber, A. (2022). The Detection of Conversation Patterns in South African Political Tweets Through Social Network Analysis. In J. E., G. A.J., V. S., & P. A. (Eds.), Communications in Computer and Information Science: Vol. 1551 CCIS (pp. 15–31). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-95070-5_2
  16. Gil-Ramírez, M., Gómez-De-travesedo-rojas, R., & Almansa-Martínez, A. (2020). Political debate on youtube: Revitalization or deterioration of democratic deliberation? Profesional de la Informacion, 29(6), 1–19. https://doi.org/10.3145/epi.2020.nov.38
  17. Gooch, A. (2018). Ripping Yarn: Experiments on Storytelling by Partisan Elites. Political Communication, 35(2), 220–238. https://doi.org/10.1080/10584609.2017.1336502
  18. Hall, M., Mazarakis, A., Peters, I., Chorley, M., Caton, S., Mai, J. E., & Strohmaier, M. (2016). Following user pathways: Cross platform and mixed methods analysis in social media studies. Conference on Human Factors in Computing Systems - Proceedings, 07-12-May-2016, 3400–3407. https://doi.org/10.1145/2851581.2856500
  19. Haris, A., Amalia, A., & Hanafi, K. (2022). Citra Politik Anies Baswedan Di Media Massa. Ilmu Komunikasi, 7 No.2(2), 1–10. http://jurnal.univrab.ac.id/index.php/cmv/article/view/2631
  20. Hewage, T. N., Halgamuge, M. N., Syed, A., & Ekici, G. (2018). Review: Big data techniques of google, Amazon, Facebook and Twitter. Journal of Communications, 13(2), 94–100. https://doi.org/10.12720/jcm.13.2.94-100
  21. Jacomy, M., Venturini, T., Heymann, S., & Bastian, M. (2014). ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software. PLoS ONE, 9(6), e98679. https://doi.org/10.1371/journal.pone.0098679
  22. Jaidka, K., Eichstaedt, J., Giorgi, S., Schwartz, H. A., & Ungar, L. H. (2021). Information-seeking vs. sharing: Which explains regional health? An analysis of Google Search and Twitter trends. Telematics and Informatics, 59, 101540. https://doi.org/10.1016/j.tele.2020.101540
  23. Jayasudha, J., & Thilagu, M. (2022). A Survey on Sentimental Analysis of Student Reviews Using Natural Language Processing (NLP) and Text Mining. In P. M., D. S., P. M.R., B. P.K., T. G.A., C. S., & C. C. C.A. (Eds.), Communications in Computer and Information Science: Vol. 1737 CCIS (pp. 365–378). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-23233-6_27
  24. Lawelai, H., Sadat, A., & Suherman, A. (2022). Democracy and Freedom of Opinion in Social Media: Sentiment Analysis on Twitter. PRAJA: Jurnal Ilmiah Pemerintahan, 10(1), 40–48. http://jurnal.umsrappang.ac.id/praja/article/view/585
  25. Lestanata, Y. (2023). Anies Rasyid Baswedan’S Political Communication in Facing the 2024 Election. Jurnal Ilmiah Peuradeun, 11(3), 1155–1172. https://doi.org/10.26811/peuradeun.v11i3.952
  26. Luth, Maswati, R., & Baharuddin, T. (2023). Online political trust in Anies Baswedan as a candidate for the President of Indonesia 2024. In Environmental Issues and Social Inclusion in a Sustainable Era (pp. 317–322). Routledge. https://doi.org/10.1201/9781003360483-36
  27. Lybecker, D. L., McBeth, M. K., Husmann, M. A., & Pelikan, N. (2015). Do New Media Support New Policy Narratives? the Social Construction of the U.S.-Mexico Border on YouTube. Policy and Internet, 7(4), 497–525. https://doi.org/10.1002/poi3.94
  28. Moya Sánchez, M., & Herrera Damas, S. (2015). How can twitter contribute to more advanced political communication? Arbor, 191(774). https://doi.org/10.3989/arbor.2015.774n4012
  29. Naskar, D., Singh, S. R., Kumar, D., Nandi, S., & De La Rivaherrera, E. O. (2020). Emotion Dynamics of Public Opinions on Twitter. ACM Transactions on Information Systems, 38(2), 1–24. https://doi.org/10.1145/3379340
  30. Nasution, F. A., Saraan, M. I. K., & Ramadhan, A. (2024). Political artifacts from the Jakarta International Stadium as local leadership impression management. Research Journal in Advanced Humanities, 5(3), 49–66. https://doi.org/10.58256/qzk7gk14
  31. Nuraniyah, N. N. (2024). Indonesia’s 2024 Presidential Election: Sectarianism Out, Dynasty In, Democracy Tethered. Asia Policy, 19(4), 96–107. https://doi.org/10.1353/asp.2024.a942836
  32. Paranyushkin, D. (2019). InfraNodus: Generating insight using text network analysis. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019, 3584–3589. https://doi.org/10.1145/3308558.3314123
  33. Persson, G. (2017). Love, Affiliation, and Emotional Recognition in #kämpamalmö:— The Social Role of Emotional Language in Twitter Discourse. Social Media and Society, 3(1). https://doi.org/10.1177/2056305117696522
  34. Puschmann, C. (2019). Beyond the Bubble: Assessing the Diversity of Political Search Results. Digital Journalism, 7(6), 824–843. https://doi.org/10.1080/21670811.2018.1539626
  35. Rasyid, S. B. A., Nurmandi, A., Suswanta, Mutiarin, D., & Salahudin. (2021). Public Communication of Local Government Leaders: A Case Study of Three Major Governors in Indonesia. In A. T. (Ed.), Advances in Intelligent Systems and Computing (Vol. 1352, pp. 487–497). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-71782-7_43
  36. Richey, S., & Taylor, J. B. (2017). Google and democracy: Politics and the power of the internet. In Google and Democracy: Politics and the Power of the Internet. Routledge. https://doi.org/10.4324/9781315159157
  37. Sheafer, T., Shenhav, S. R., & Balmas, M. (2014). Political actors as communicators. In Political Communication (pp. 211–229). DE GRUYTER. https://doi.org/10.1515/9783110238174.211
  38. Shevtsov, A., Oikonomidou, M., Antonakaki, D., Pratikakis, P., & Ioannidis, S. (2023). What Tweets and YouTube comments have in common? Sentiment and graph analysis on data related to US elections 2020. PLoS ONE, 18(1 January), e0270542. https://doi.org/10.1371/journal.pone.0270542
  39. Sujoko, A., Haboddin, M., & Afala, L. O. M. (2022). Anies Baswedan’s Rhetoric amid Political Polarization for COVID-19 Handling in Jakarta, Indonesia. Jurnal Komunikasi: Malaysian Journal of Communication, 38(3), 54–69. https://doi.org/10.17576/JKMJC-2022-3803-04
  40. Tursunkulova, I., de Castell, S., & Jenson, J. (2023). Exploring Infranodus: a Text Analysis Tool. 20th International Conference on Cognition and Exploratory Learning in Digital Age, CELDA 2023, 34–42. https://eric.ed.gov/?id=ED636402
  41. Ul Haq, F. R., Hadna, A. H., Darwin, M., & Ikhwan, H. (2024). Dynamics of Covid-19 policy implementation in DKI Jakarta: study of the responses of Muhammadiyah members. Indonesian Journal of Islam and Muslim Societies, 14(1), 63–89. https://doi.org/10.18326/ijims.v14i1.63-89
  42. Yandra, A., Safitri, D., Herdi, Kurniawan, & Hamuddin, B. (2018). Exploring Discourse of Illocutionary Act: The Controversial Pribumi Anies Baswedan’s Speech. IOP Conference Series: Earth and Environmental Science, 175(1), 012230. https://doi.org/10.1088/1755-1315/175/1/012230
  43. Ye, Y., Zhang, R., Zhao, Y., Yu, Y., Du, W., & Chen, T. (2022). A Novel Public Opinion Polarization Model Based on BA Network. Systems, 10(2), 46. https://doi.org/10.3390/systems10020046
  44. Zumofen, G. (2023). What Drives the Selection of Political Information on Google? Tension Between Ideal Democracy and the Influence of Ranking. Swiss Political Science Review, 29(1), 120–138. https://doi.org/10.1111/spsr.12545