@inproceedings{flor-somasundaran-2017-sentiment,
    title = "Sentiment Analysis and Lexical Cohesion for the Story Cloze Task",
    author = "Flor, Michael  and
      Somasundaran, Swapna",
    editor = "Roth, Michael  and
      Mostafazadeh, Nasrin  and
      Chambers, Nathanael  and
      Louis, Annie",
    booktitle = "Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics",
    month = apr,
    year = "2017",
    address = "Valencia, Spain",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W17-0909/",
    doi = "10.18653/v1/W17-0909",
    pages = "62--67",
    abstract = "We present two NLP components for the Story Cloze Task {--} dictionary-based sentiment analysis and lexical cohesion. While previous research found no contribution from sentiment analysis to the accuracy on this task, we demonstrate that sentiment is an important aspect. We describe a new approach, using a rule that estimates sentiment congruence in a story. Our sentiment-based system achieves strong results on this task. Our lexical cohesion system achieves accuracy comparable to previously published baseline results. A combination of the two systems achieves better accuracy than published baselines. We argue that sentiment analysis should be considered an integral part of narrative comprehension."
}