A comprehensive analysis of adverb types for mining user sentiments on Amazon product reviews

Chauhan, Ummara Ahmed and Afzal, Muhammad Tanvir and Shahid, Abdul and Abdar, Moloud and Basiri, Mohammad Ehsan and Zhou, Xujuan (2020) A comprehensive analysis of adverb types for mining user sentiments on Amazon product reviews. World Wide Web. ISSN 1386-145X


Abstract

Online shopping websites like Amazon stipulate a platform to the users where they can share their opinions about different products. Recently, it has been identified that prior to the purchasing, 81% of the users explore different online platforms in order to assess the reliability of product that they intend to buy. The reviews of different users are expressed by using natural language, which help a user to make an informed decision. From past few years, scientific community has payed attention to automatically specify the meaning of review through Sentiment Analysis. Sentiment Analysis is a research area which is gradually being evolved thus, helping the users to tackle the sentiment hidden in a review. To date, different sentiment analysis-based studies have been conducted in literature. For sentiment classification, the core ingredient is the exploitation of polarity bearing words present in the reviews e.g. adjectives, verbs, and adverbs etc. Different studies suggest the importance of different forms of adverbs in sentiment classification task. In literature, it has been reported that general adverbs strongly help to classify sentiments with better accuracy whereas other suggest that degree adverbs are important for sentiment classification. There are ten distinct forms of adverbs such as general adverbs, general superlative adverbs, general comparative adverbs, general-wh adverbs, degree adverbs, degree superlative adverbs, degree comparative adverbs, degree-wh adverbs, time adverbs and locative adverbs. In this paper, we intend to tackle a question that what is the impact of different forms of adverb on the classification of sentiments? For this, the impacts of all these forms have been evaluated on 51,005 reviews of two products, office products and musical DVDs acquired from Amazon. The outcomes of study revealed that two general superlative adverbs and degree-wh adverb hold more impact than the other forms of adverbs. The general superlative adverbs have attained F-measure of 0.86 and degree-wh adverbs have attained F-measure of 0.80.


Statistics for USQ ePrint 37722
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Published online: 20 February 2020. Permanent restricted access to ArticleFirst version, in accordance with the copyright policy of the publisher.
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Management and Enterprise (1 July 2013 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Management and Enterprise (1 July 2013 -)
Date Deposited: 11 Mar 2020 02:41
Last Modified: 08 May 2020 01:51
Uncontrolled Keywords: big data, forms of adverb, product reviews, role of adverbs, sentiment classification
Fields of Research (2008): 08 Information and Computing Sciences > 0806 Information Systems > 080699 Information Systems not elsewhere classified
Socio-Economic Objectives (2008): E Expanding Knowledge > 97 Expanding Knowledge > 970108 Expanding Knowledge in the Information and Computing Sciences
Identification Number or DOI: 10.1007/s11280-020-00785-z
URI: http://eprints.usq.edu.au/id/eprint/37722

Actions (login required)

View Item Archive Repository Staff Only