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Mining Domain-Specific Dictionaries of Opinion Words

Lecture notes in computer sciencePublished 1 January 2014
Pantelis Agathangelou, Ioannis Katakis, Fotios Kokkoras, Konstantinos Ntonas
Citations11
SJR quartileQ2
SJR score0.35
SNIP0.55

TL;DR

This paper proposes an approach for domain-specific dictionary building, NiosTo, a software that enables dictionary extraction and sentiment analysis on a given corpus and evaluates the approach on a sentiment analysis task.

Abstract

The task of opinion mining has attracted interest during the last years. This is mainly due to the vast availability and value of opinions on-line and the easy access of data through conventional or intelligent crawlers. In order to utilize this information, algorithms make extensive use of word sets with known polarity. This approach is known as dictionary-based sentiment analysis. Such dictionaries are available for the English language. Unfortunately, this is not the case for other languages with smaller user bases. Moreover, such generic dictionaries are not suitable for specific domains. Domain-specific dictionaries are crucial for domain-specific sentiment analysis tasks. In this paper we alleviate the above issues by proposing an approach for domain-specific dictionary building. We evaluate our approach on a sentiment analysis task. Experiments on user reviews on digital devices demonstrate the utility of the proposed approach. In addition, we present NiosTo, a software that enables dictionary extraction and sentiment analysis on a given corpus.

Keywords

Computer Science