Linguistic Features to Identify Extreme Opinions: An Empirical Study

TítuloLinguistic Features to Identify Extreme Opinions: An Empirical Study
AutoresSattam Almatarneh, Pablo Gamallo
TipoComunicación para congreso
Fonte 19th International Conference on Intelligent Data Engineering and Automated Learning, Madrid (Spain), pp. 215-223 , 2018.
ISBN978-3-030-03493-1
ISSN1611-3349
DOI10.1007/978-3-030-03493-1_23
AbstractStudies in sentiment analysis and opinion mining have examined how different features are effective in polarity classification by making use of positive, negative or neutral values. However, the identification of extreme opinions (most negative and most positive opinions) have overlooked in spite of their wide significance in many applications. In our study, we will combine empirical features (e.g. bag of words, word embeddings, polarity lexicons, and set of textual features) so as to identify extreme opinions and provide a comprehensive analysis of the relative importance of each set of features using hotel reviews.
Palabras chaveSentiment Analysis, Opinion Mining, linguistic features, Classification, Extreme Opinion