A comparative study on twitter sentiment analysis: Which features are good?

Fajri Koto, Mirna Adriani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

20 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationNatural Language Processing and Information Systems - 20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015, Proceedings
EditorsSiegfried Handschuh, André Freitas, Elisabeth Métais, Chris Biemann, Farid Meziane
PublisherSpringer Verlag
Pages453-457
Number of pages5
ISBN (Print)9783319195803
DOIs
Publication statusPublished - 1 Jan 2015
Event20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015 - Passau, Germany
Duration: 17 Jun 201519 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9103
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Applications of Natural Language to Information Systems, NLDB 2015
CountryGermany
CityPassau
Period17/06/1519/06/15

Keywords

  • Comparative study
  • Polarity
  • Sentiment Analysis
  • Subjectivity
  • Twitter

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