Consensus in Sentiment Analysis
Date
2021-05
Advisors
Journal Title
Journal ISSN
ISSN
Volume Title
Publisher
Springer International Publishing
Type
Book chapter
Peer reviewed
Yes
Abstract
The objective of this chapter is to present a method applicable in group decision-making where computing the opinion of the majority of participants is key. In this article, we present a method that makes use of Induced Ordered Weighted Averaging (IOWA) operators to aggregate a majority opinion out of a number of Sentiment Analysis (SA) classification systems. The numerical output of each SA classification method is used as input to a carefully chosen IOWA operator that is semantically equivalent to the fuzzy linguistic quantifier ‘most of’. The object of the aggregation will be the intensity of the previously determined sentence polarity in such a way that the results represent what the majority thinks.
Description
Keywords
Sentiment analysis Consensus Majority support Sentiment aggregation Ordered weighted averaging OWA Induced ordered weighted averaging, Sentiment analysis, Consensus Majority support, Sentiment aggregation, Ordered weighted averaging, OWA Induced ordered weighted averaging
Citation
Appel, O., Chiclana, F., Carter, J. and Fujita, H. (2021) Consensus in Sentiment Analysis. In: Jenny Carter, Francisco Chiclana, Arjab Singh Khuman, Tianhua Chen (Eds.): Fuzzy Logic: Recent Applications and Developments. Springer International Publishing, pp. 35-49