Community Detection, Topic, and Sentiment Analysis of the Palestine-Israel Issue on Social Media X

Fathnin Nur Azmina; Muhaza Liebenlito; Dhea Urfina Zulkifli

doi:10.20956/j.v21i2.41308

Authors

Fathnin Nur Azmina Department of Mathematics, Faculty of Science and Technology, Syarif Hidayatullah State Islamic University Jakarta
Muhaza Liebenlito Department of Mathematics, Faculty of Science and Technology, Syarif Hidayatullah State Islamic University Jakarta
Dhea Urfina Zulkifli Department of Mathematics, Faculty of Science and Technology, Syarif Hidayatullah State Islamic University Jakarta

DOI:

https://doi.org/10.20956/j.v21i2.41308

Keywords:

Community Detection, Leiden, LDA, IndoBERT, Palestine-Israel

Abstract

The combination of community detection, topic modeling, and sentiment analysis provides deep insights into conversation data on the social media platform X (formerly Twitter) regarding the Palestine-Israel issue. The data, collected in Indonesian using several keywords, resulted in 108,969 tweets. The analysis process began with community detection using the Leiden algorithm, which identified five communities. The three dominant communities identified are Community 1 comprising 37.13% of users, Community 2 with 26.95%, and Community 3 with 19.76%. Topic modeling using LDA revealed that these communities focused on various aspects of the conflict. Sentiment analysis using the IndoBERT model uncovered that the majority of users expressed negative attitudes such as disappointment and anger. This study provides insights into public opinions and social dynamics surrounding the conflict.

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