Wang, Bo, Liakata, Maria, Zubiaga, Arkaitz and Procter, Rob (2016) TDParse - multi-target-specific sentiment recognition on Twitter. In: The 15th Conference of the European Chapter of the Association for Computational Linguistics, Valencia, Spain, 3-7 April 2017

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Abstract

Existing target-specific sentiment recognition methods consider only a single target per tweet, and have been shown to miss nearly half of the actual targets mentioned. We present a corpus of UK election tweets, with an average of 3.09 entities per tweet and more than one type of sentiment in half of the tweets. This requires a method for multi-target specific sentiment recognition, which we develop by using the context around a target as well as syntactic dependencies involving the target. We present results of our method on both a benchmark corpus of single targets and the multi-target election corpus, showing state-of-the art performance in both corpora and outperforming previous approaches to multi-target sentiment task as well as deep learning models for single-target sentiment.

Item Type:	Conference Item (Paper)
Subjects:	Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software
Divisions:	Faculty of Science, Engineering and Medicine > Science > Computer Science
Official Date:	9 December 2016
Dates:	Date Event 9 December 2016 Accepted
Status:	Peer Reviewed
Publication Status:	Published
Date of first compliant deposit:	13 January 2017
Date of first compliant Open Access:	16 January 2017
Conference Paper Type:	Paper
Title of Event:	The 15th Conference of the European Chapter of the Association for Computational Linguistics
Type of Event:	Conference
Location of Event:	Valencia, Spain
Date(s) of Event:	3-7 April 2017
Related URLs:	Organisation

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