Utilize este identificador para referenciar este registo:
http://hdl.handle.net/10071/26472
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Guerreiro, J. | - |
dc.contributor.author | Loureiro, S. M. C. | - |
dc.contributor.editor | Sandra Maria Correia Loureiro | - |
dc.contributor.editor | Hans Ruediger Kaufmann | - |
dc.date.accessioned | 2022-11-24T10:13:40Z | - |
dc.date.available | 2022-11-24T10:13:40Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | 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 | - |
dc.identifier.isbn | 9781522585756 | - |
dc.identifier.uri | http://hdl.handle.net/10071/26472 | - |
dc.description.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. | eng |
dc.language.iso | eng | - |
dc.publisher | IGI Global | - |
dc.relation.ispartof | Exploring the power of electronic word-of-mouth in the services industry | - |
dc.rights | openAccess | - |
dc.subject | e-WOM | eng |
dc.subject | Text mining | eng |
dc.subject | Análise de sentimentos -- Sentiment analysis | eng |
dc.subject | NLP | eng |
dc.subject | LDA | eng |
dc.subject | CTM | eng |
dc.title | Unraveling e-WOM patterns using text mining and sentiment analysis | eng |
dc.type | bookPart | - |
dc.event.location | Hershey | eng |
dc.peerreviewed | yes | - |
dc.date.updated | 2022-11-24T10:11:41Z | - |
dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
dc.identifier.doi | 10.4018/978-1-5225-8575-6.ch006 | - |
iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-61019 | - |
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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