@InProceedings{cummings-wilson:2019:S19-2,
  author    = {Cummings, Joseph  and  Wilson, Jason},
  title     = {CLARK at SemEval-2019 Task 3: Exploring the Role of Context to Identify Emotion in a Short Conversation},
  booktitle = {Proceedings of the 13th International Workshop on Semantic Evaluation},
  month     = {June},
  year      = {2019},
  address   = {Minneapolis, Minnesota, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {159--163},
  abstract  = {With text lacking valuable information avail-able 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 Naive 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 train-ing the model significantly decreases performance. Our approach has the additional bene-fit that its performance rivals a baseline LSTM model while requiring fewer resources.},
  url       = {http://www.aclweb.org/anthology/S19-2024}
}