Title: Opinion mining of online product reviews using a lexicon-based algorithm

Authors: Ignacio Martín-Borregón Musso; Marina Bagić Babac

Addresses: Comillas Pontifical University, C. de Alberto Aguilera, 25, Madrid, Spain ' Faculty of Electrical Engineering and Computing, University of Zagreb, Zagreb, Croatia

Abstract: Worldwide social media is a rich resource of user-generated data, which can help organisations to formulate their business strategies, and affect the process of decision making in product or service design and implementation. The focus of this paper is on the extraction and analysis of unstructured product reviews for training predictive models, which recognise a specific range of human affective states such as emotions, moods, opinions, or attitudes. Based on the textual and reactions analysis, the emotional reactions lexicon of English words is built from the product posts and comments, and a lexicon-based algorithm is used to predict user opinions on social media.

Keywords: opinion mining; emotion analysis; product reviews; social media.

DOI: 10.1504/IJDATS.2022.129177

International Journal of Data Analysis Techniques and Strategies, 2022 Vol.14 No.4, pp.283 - 301

Received: 12 Aug 2021
Received in revised form: 18 Jul 2022
Accepted: 27 Oct 2022
Published online: 27 Feb 2023 *

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