The Journal of Machine Learning Research
We feel fine and searching the emotional web
Proceedings of the fourth ACM international conference on Web search and data mining
Aspect and sentiment unification model for online review analysis
Proceedings of the fourth ACM international conference on Web search and data mining
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Conversational partners influence each others' emotions and topics. Using a large dataset of Twitter conversations and an unsupervised machine learning technique, we discover patterns of emotion influence in naturally occurring conversations. We describe our computational framework for automatically classifying emotions, analyzing the emotional transitions, and discovering emotion influence patterns. We found that conversational partners usually express the same emotion (emotion contagion), but when they do not, one of the conversational partners tends to respond with a positive emotion. Also, tweets containing sympathy, apology, and complaint are significant emotion influencers. One of the interesting findings is that expressing a desired emotion is the best strategy to alter partner's emotion.