Neural-based RST Parsing And Analysis In Persuasive Discourse

Jinfen Li, Lu Xiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Most of the existing studies of language use in social media content have focused on the surface-level linguistic features (e.g., function words and punctuation marks) and the semantic level aspects (e.g., the topics, sentiment, and emotions) of the comments. The writer’s strategies of constructing and connecting text segments have not been widely explored even though this knowledge is expected to shed light on how people reason in online environments. Contributing to this analysis direction for social media studies, we build an openly accessible neural RST parsing system that analyzes discourse relations in an online comment. Our experiments demonstrate that this system achieves comparable performance among all the neural RST parsing systems. To demonstrate the use of this tool in social media analysis, we apply it to identify the discourse relations in persuasive and non-persuasive comments and examine the relationships among the binary discourse tree depth, discourse relations, and the perceived persuasiveness of online comments. Our work demonstrates the potential of analyzing discourse structures of online comments with our system and the implications of these structures for understanding online communications.

Original languageEnglish (US)
Title of host publicationW-NUT 2021 - 7th Workshop on Noisy User-Generated Text, Proceedings of the Conference
EditorsWei Xu, Alan Ritter, Tim Baldwin, Afshin Rahimi
PublisherAssociation for Computational Linguistics (ACL)
Pages274-283
Number of pages10
ISBN (Electronic)9781954085909
StatePublished - 2021
Event7th Workshop on Noisy User-Generated Text, W-NUT 2021 - Virtual, Online
Duration: Nov 11 2021 → …

Publication series

NameW-NUT 2021 - 7th Workshop on Noisy User-Generated Text, Proceedings of the Conference

Conference

Conference7th Workshop on Noisy User-Generated Text, W-NUT 2021
CityVirtual, Online
Period11/11/21 → …

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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