{"type":"ScholarlyArticle","title":"Intersubjectivity and Sentiment: From Language to Knowledge","authors":[{"name":"Lin Gui","slug":"lin-gui","given":"Lin","family":"Gui","affiliation":"Laboratory of Network Oriented Intelligent Computation , Shenzhen Graduate School , Harbin Institute of Technology , Shenzhen , China"},{"name":"Ruifeng Xu","slug":"ruifeng-xu","given":"Ruifeng","family":"Xu","affiliation":"Laboratory of Network Oriented Intelligent Computation , Shenzhen Graduate School , Harbin Institute of Technology , Shenzhen , China"},{"name":"Yulan He","slug":"yulan-he","given":"Yulan","family":"He","affiliation":"School of Engineering and Applied Science , Aston University , United Kingdom"},{"name":"Qin Lu","slug":"qin-lu","given":"Qin","family":"Lu","affiliation":"Department of Computing , the Hong Kong Polytechnic University , Hong Kong"},{"name":"Zhongyu Wei","slug":"zhongyu-wei","given":"Zhongyu","family":"Wei","affiliation":"Computer Science Department , The University of Texas at Dallas , Texas 75080 , USA"}],"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.","doi":null,"url":"https://ijcai.org/proceedings/2016/396","pdf":"https://ijcai.org/proceedings/2016/0396.pdf","markdown":"https://ijcai.org/proceedings/2016/396.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/396","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":396,"pages":{"first":2789,"last":2794},"keywords":[],"videos":[],"references":[{"position":1,"raw":"[Abbasi et al., 2011] Ahmed Abbasi, Stephen France, Zhu Zhang, and et al. 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