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.
|Number of pages||7|
|Journal||IJCAI International Joint Conference on Artificial Intelligence|
|Publication status||Published - 1 Jan 2016|
|Event||25th International Joint Conference on Artificial Intelligence, IJCAI 2016 - New York, United States|
Duration: 9 Jul 2016 → 15 Jul 2016
ASJC Scopus subject areas
- Artificial Intelligence