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With text lacking valuable information available in other modalities, context may provide useful information to better detect emotions. In this paper, we do a systematic exploration of the role of context in recognizing emotion in a conversation. We use a Naïve Bayes model to show that inferring the mood of the conversation before classifying individual utterances leads to better performance. Additionally, we find that using context while training the model significantly decreases performance.doi:10.18653/v1/s19-2024 dblp:conf/semeval/CummingsW19 fatcat:6bavg4q66ba6jikrotclhykt7e