TY - JOUR
T1 - Mining Domain-Specific Dictionaries of Opinion Words
AU - Agathangelou, Pantelis
AU - Katakis, Ioannis
AU - Kokkoras, Fotios
AU - Ntonas, Konstantinos
PY - 2014/1/1
Y1 - 2014/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84921684214&partnerID=8YFLogxK
M3 - Article
AN - SCOPUS:84921684214
SN - 0302-9743
VL - 8786
SP - 47
EP - 62
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -