Intersubjectivity and sentiment: From language to knowledge

Lin Gui, Ruifeng Xu, Yulan He, Qin Lu, Zhongyu Wei

Research output: Journal article publicationConference articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

Intersubjectivity is an important concept in psychology and sociology. It refers to sharing conceptualizations through social interactions in a community and using such shared conceptualization as a resource to interpret things that happen in everyday life. In this work, we make use of intersubjectivity as the basis to model shared stance and subjectivity for sentiment analysis. We construct an intersubjectivity network which links review writers, terms they used, as well as the polarities of the terms. Based on this network model, we propose a method to learn writer embeddings which are subsequently incorporated into a convolutional neural network for sentiment analysis. Evaluations on the IMDB, Yelp 2013 and Yelp 2014 datasets show that the proposed approach has achieved the state-of-the-art performance.
Original languageEnglish
Pages (from-to)2789-2795
Number of pages7
JournalIJCAI International Joint Conference on Artificial Intelligence
Volume2016-January
Publication statusPublished - 1 Jan 2016
Event25th International Joint Conference on Artificial Intelligence, IJCAI 2016 - New York, United States
Duration: 9 Jul 201615 Jul 2016

ASJC Scopus subject areas

  • Artificial Intelligence

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