SICLDec 14, 2024

Quantifying Extreme Opinions on Reddit Amidst the 2023 Israeli-Palestinian Conflict

arXiv:2412.10913v12 citationsh-index: 9Nat Lang Process J
Originality Synthesis-oriented
AI Analysis

It addresses the problem of understanding polarized online discourse for researchers and policymakers, but is incremental as it applies an unsupervised lexicon-based method to a new dataset.

This study tackled the problem of quantifying extreme opinions on Reddit during the 2023 Israeli-Palestinian conflict by analyzing over 450,000 posts, finding significant peaks in extremism scores that correlated with key real-life events like bombings and ceasefire ends.

This study investigates the dynamics of extreme opinions on social media during the 2023 Israeli-Palestinian conflict, utilising a comprehensive dataset of over 450,000 posts from four Reddit subreddits (r/Palestine, r/Judaism, r/IsraelPalestine, and r/worldnews). A lexicon-based, unsupervised methodology was developed to measure "extreme opinions" by considering factors such as anger, polarity, and subjectivity. The analysis identifies significant peaks in extremism scores that correspond to pivotal real-life events, such as the IDF's bombings of Al Quds Hospital and the Jabalia Refugee Camp, and the end of a ceasefire following a terrorist attack. Additionally, this study explores the distribution and correlation of these scores across different subreddits and over time, providing insights into the propagation of polarised sentiments in response to conflict events. By examining the quantitative effects of each score on extremism and analysing word cloud similarities through Jaccard indices, the research offers a nuanced understanding of the factors driving extreme online opinions. This approach underscores the potential of social media analytics in capturing the complex interplay between real-world events and online discourse, while also highlighting the limitations and challenges of measuring extremism in social media contexts.

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