Please use this identifier to cite or link to this item: http://hdl.handle.net/10071/26472
Author(s): Guerreiro, J.
Loureiro, S. M. C.
Editor: Sandra Maria Correia Loureiro
Hans Ruediger Kaufmann
Date: 2020
Title: Unraveling e-WOM patterns using text mining and sentiment analysis
Book title/volume: Exploring the power of electronic word-of-mouth in the services industry
Reference: Guerreiro, J., Loureiro, S. M. C. (2020). Unraveling e-WOM patterns using text mining and sentiment analysis. EM Sandra Maria Correia Loureiro, Hans Ruediger Kaufmann (Eds.). Exploring the power of electronic word-of-mouth in the services industry. IGI Global. 10.4018/978-1-5225-8575-6.ch006
ISBN: 9781522585756
DOI (Digital Object Identifier): 10.4018/978-1-5225-8575-6.ch006
Keywords: e-WOM
Text mining
Análise de sentimentos -- Sentiment analysis
NLP
LDA
CTM
Abstract: Electronic word-of-mouth (e-WOM) is a very important way for firms to measure the pulse of its online reputation. Today, consumers use e-WOM as a way to interact with companies and share not only their satisfaction with the experience, but also their discontent. E-WOM is even a good way for companies to co-create better experiences that meet consumer needs. However, not many companies are using such unstructured information as a valuable resource to help in decision making. First, because e-WOM is mainly textual information that needs special data treatment and second, because it is spread in many different platforms and occurs in near-real-time, which makes it hard to handle. The current chapter revises the main methodologies used successfully to unravel hidden patterns in e-WOM in order to help decision makers to use such information to better align their companies with the consumer’s needs.
Peerreviewed: yes
Access type: Open Access
Appears in Collections:BRU-CLI - Capítulos de livros internacionais

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