TY - GEN
T1 - A comparative study on twitter sentiment analysis
T2 - 20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015
AU - Koto, Fajri
AU - Adriani, Mirna
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - In this paper, investigations of Sentiment Analysis over a well-known Social Media Twitter were done. As literatures show that some works related to Twitter Sentiment Analysis have been done and delivered interesting idea of features, but there is no a comparative study that shows the best features in performing Sentiment Analysis. In total we used 9 feature sets (41 attributes) that comprise punctuation, lexical, part of speech, emoticon, SentiWord lexicon, AFINN-lexicon, Opinion lexicon, Senti-Strength method, and Emotion lexicon. Feature analysis was done by conducting supervised classification for each feature sets and continued with feature selection in subjectivity and polarity domain. By using four different datasets, the results reveal that AFINN lexicon and Senti-Strength method are the best current approaches to perform Twitter Sentiment Analysis.
AB - In this paper, investigations of Sentiment Analysis over a well-known Social Media Twitter were done. As literatures show that some works related to Twitter Sentiment Analysis have been done and delivered interesting idea of features, but there is no a comparative study that shows the best features in performing Sentiment Analysis. In total we used 9 feature sets (41 attributes) that comprise punctuation, lexical, part of speech, emoticon, SentiWord lexicon, AFINN-lexicon, Opinion lexicon, Senti-Strength method, and Emotion lexicon. Feature analysis was done by conducting supervised classification for each feature sets and continued with feature selection in subjectivity and polarity domain. By using four different datasets, the results reveal that AFINN lexicon and Senti-Strength method are the best current approaches to perform Twitter Sentiment Analysis.
KW - Comparative study
KW - Polarity
KW - Sentiment Analysis
KW - Subjectivity
KW - Twitter
UR - http://www.scopus.com/inward/record.url?scp=84948845333&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-19581-0_46
DO - 10.1007/978-3-319-19581-0_46
M3 - Conference contribution
AN - SCOPUS:84948845333
SN - 9783319195803
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 453
EP - 457
BT - Natural Language Processing and Information Systems - 20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015, Proceedings
A2 - Handschuh, Siegfried
A2 - Freitas, André
A2 - Métais, Elisabeth
A2 - Biemann, Chris
A2 - Meziane, Farid
PB - Springer Verlag
Y2 - 17 June 2015 through 19 June 2015
ER -