Opinion Distribution
Opinion distribution research focuses on understanding and modeling how opinions are formed, spread, and evolve within populations, aiming to quantify and predict sentiment across diverse contexts. Current research employs various techniques, including sentiment analysis of social media data, large language models for opinion annotation and aggregation, and computational models simulating opinion dynamics based on factors like bounded confidence and argumentation. These advancements have implications for improving online content moderation, enhancing recommendation systems, and providing insights into social phenomena like polarization and the spread of misinformation.
Papers
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