Summarizing Dialogic Arguments from Social Media

Amita Misra, Shereen Oraby, Shubhangi Tandon, Sharath Ts, Pranav Anand, Marilyn Walker

Online argumentative dialogue is a rich source of information on popular beliefs and opinions that could be useful to companies as well as governmental or public policy agencies. Compact, easy to read, summaries of these dialogues would thus be highly valuable. A priori, it is not even clear what form such a summary should take. Previous work on summarization has primarily focused on summarizing written texts, where the notion of an abstract of the text is well defined. We collect gold standard training data consisting of five human summaries for each of 161 dialogues on the topics of Gay Marriage, Gun Control and Abortion. We present several different computational models aimed at identifying segments of the dialogues whose content should be used for the summary, using linguistic features and Word2vec features with both SVMs and Bidirectional LSTMs. We show that we can identify the most important arguments by using the dialogue context with a best F-measure of 0.74 for gun control, 0.71 for gay marriage, and 0.67 for abortion.

 DOI: 10.21437/SemDial.2017-14

Cite as: Misra, A., Oraby, S., Tandon, S., Ts, S., Anand, P., Walker, M. (2017) Summarizing Dialogic Arguments from Social Media. Proc. SEMDIAL 2017 (SaarDial) Workshop on the Semantics and Pragmatics of Dialogue, 126-136, DOI: 10.21437/SemDial.2017-14.

  author={Amita Misra and Shereen Oraby and Shubhangi Tandon and Sharath Ts and Pranav Anand and Marilyn Walker},
  title={Summarizing Dialogic Arguments from Social Media},
  booktitle={Proc. SEMDIAL 2017 (SaarDial) Workshop on the Semantics and Pragmatics of Dialogue},