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

Rights

Research Institute

Institute of Artificial Intelligence (IAI)