TY - GEN
T1 - Mining domain-specific dictionaries of opinion words
AU - Agathangelou, Pantelis
AU - Katakis, Ioannis
AU - Kokkoras, Fotios
AU - Ntonas, Konstantinos
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2014.
PY - 2014
Y1 - 2014
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=84945352376&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-11749-2_4
DO - 10.1007/978-3-319-11749-2_4
M3 - Conference contribution
AN - SCOPUS:84945352376
SN - 9783319117485
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 47
EP - 62
BT - Web Information Systems Engineering – WISE 2014 - 15th International Conference, Proceedings
A2 - Benatallah, Boualem
A2 - Bestavros, Azer
A2 - Manolopoulos, Yannis
A2 - Vakali, Athena
A2 - Zhang, Yanchun
PB - Springer Verlag
T2 - 15th International Conference on Web Information Systems Engineering, WISE 2014
Y2 - 12 October 2014 through 14 October 2014
ER -