Identification of Opinion Holders

Identifying Opinion Holders for Question Answering in Opinion Texts

Question answering in opinion texts has so far mostly concentrated on the identification of opinions and on analyzing the sentiment expressed in opinions. In this paper, we address another important part of Question Answering (QA) in opinion texts: finding opinion holders. Holder identification is a central part of full opinion identification and can be used independently to answer several opin...

Supervised Approaches and Dependency Parsing for Chinese Opinion Analysis at NTCIR-8

In this paper, we describe our participating system, which is based on supervised approaches and dependency parsing, for opinion analysis on traditional Chinese texts at NTCIR-8. For opinionated sentence recognition, the supervised lexicon-based approach, SVM and Maximum Entropy are combined together. For polarity classification, we use only the supervised lexicon-based approach. For opinion ho...

Joint Inference for Fine-grained Opinion Extraction

This paper addresses the task of finegrained opinion extraction – the identification of opinion-related entities: the opinion expressions, the opinion holders, and the targets of the opinions, and the relations between opinion expressions and their targets and holders. Most existing approaches tackle the extraction of opinion entities and opinion relations in a pipelined manner, where the inter...

意見持有者辨識之研究 (A Study on Identification of Opinion Holders) [In Chinese]

Identifying Opinion Holders and Targets with Dependency Parser in Chinese News Texts

In this paper, we propose to identify opinion holders and targets with dependency parser in Chinese news texts, i.e. to identify opinion holders by means of reporting verbs and to identify opinion targets by considering both opinion holders and opinion-bearing words. The experiments with NTCIR-7 MOAT’s Chinese test data show that our approach provides better performance than the baselines and m...