Mining Domain-Specific Dictionaries of Opinion Words

Pantelis Agathangelou, Ioannis Katakis, Fotios Kokkoras, Konstantinos Ntonas

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)47-62
Number of pages16
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publication statusPublished - 1 Jan 2014


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