A Computational Analysis of Polarization on Indian and Pakistani Social Media
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Abstract (arXiv)
Between February 14, 2019 and March 4, 2019, a terrorist attack in Pulwama, Kashmir followed by retaliatory airstrikes led to rising tensions between India and Pakistan, two nuclear-armed countries. In this work, we examine polarizing messaging on Twitter during these events, particularly focusing on the positions of Indian and Pakistani politicians. We use a label propagation technique focused on hashtag co-occurrences to find polarizing tweets and users. Our analysis reveals that politicians in the ruling political party in India (BJP) used polarized hashtags and called for escalation of conflict more so than politicians from other parties. Our work offers the first analysis of how escalating tensions between India and Pakistan manifest on Twitter and provides a framework for studying polarizing messages.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 May 2020.
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Citing papers per year: 2021: 2; 2022: 2.
4 papers.
- 2022A Multi-task Model for Sentiment Aided Stance Detection of Climate Change Tweetscited by 11
- 2021ENTRUST: Argument Reframing with Language Models and Entailmentcited by 10
- 2021Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsitycited by 9
- 2022Unsupervised Detection of Contextualized Embedding Bias with Application to Ideologycited by 1
- 2022Unsupervised Detection of Contextualized Embedding Bias with Application to Ideology14 Dec 2022
- 2022A Multi-task Model for Sentiment Aided Stance Detection of Climate Change Tweets7 Nov 2022
- 2021Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsity18 Apr 2021
- 2021ENTRUST: Argument Reframing with Language Models and Entailment11 Mar 2021