Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/26472
Autoria: | Guerreiro, J. Loureiro, S. M. C. |
Editor: | Sandra Maria Correia Loureiro Hans Ruediger Kaufmann |
Data: | 2020 |
Título próprio: | Unraveling e-WOM patterns using text mining and sentiment analysis |
Título e volume do livro: | Exploring the power of electronic word-of-mouth in the services industry |
Referência bibliográfica: | 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 |
Palavras-chave: | e-WOM Text mining Análise de sentimentos -- Sentiment analysis NLP LDA CTM |
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. |
Arbitragem científica: | yes |
Acesso: | Acesso Aberto |
Aparece nas coleções: | BRU-CLI - Capítulos de livros internacionais |
Ficheiros deste registo:
Ficheiro | Tamanho | Formato | |
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bookPart_61019.pdf | 1,3 MB | Adobe PDF | Ver/Abrir |
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