Capítulo de livro
Unraveling e-WOM patterns using text mining and sentiment analysis
João Guerreiro (Guerreiro, J.); Sandra Loureiro (Loureiro, S. M. C.);
Título Livro
Exploring the power of electronic word-of-mouth in the services industry
Ano (publicação definitiva)
2020
Língua
Inglês
País
Estados Unidos da América
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N.º de citações: 1

(Última verificação: 2024-03-29 07:25)

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Abstract/Resumo
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.
Agradecimentos/Acknowledgements
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Palavras-chave
e-WOM,Text mining,Sentiment analysis,NLP,LDA,CTM