Abstract
ABSTRACT This research employs a comprehensive methodology to delve into public sentiments surrounding the Israeli–Palestinian conflict, incorporating unconventional data sources—YouTube comments and Mastodon. Departing from the traditional reliance on Twitter, our systematic approach involves keyword-driven content identification, leveraging Google Trends to establish five pivotal keywords. Mastodon searches employed straightforward hashtag strategies, while the intricacies of YouTube required an exclusive focus on official newspaper channels to mitigate polarization risks. Rigorous data cleaning ensued, retaining only English-language texts and eliminating extraneous elements. The resulting dataset was subjected to Sentiment Analysis and Emotion Detection, providing a nuanced understanding of public sentiments across platforms, totaling 253.3 K texts.
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