Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 2022 · 12 citations · 41 references
ComputingComputer SciencePredictive AnalyticsRecommender SystemsSocial Media AnalyticsAffective ComputingEmotion RecognitionOnline RecommendationRecommendation EvaluationRecommendation SystemsSocial MediaActive RecommendationAffect PredictionAffective Data MiningAffective PersonalizationAffective User ExperienceEmotion PredictionPersonalized RecommendationSignals
People come to social media to satisfy a variety of needs, such as being informed, entertained and inspired, or connected to their friends and community. Hence, to design a ranking function that gives useful and personalized post recommendations, it would be helpful to be able to predict the affective response a user may have to a post (e.g., entertained, informed, angered). This paper describes the challenges and solutions we developed to apply Affective Computing to social media recommendation systems.
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