Casas-Valadez, Mariano Alberto, Faz-Mendoza, Alberto, Medina-Rodríguez, Cesar Esau, Castorena-Robles, Andrea, Gamboa-Rosales, Nadia Karina and López-Robles, José Ricardo Decision Models in Marketing: The role of Sentiment Analysis from bibliometric analysis., 2020 . In The 2020 International Conference on Decision Aid Sciences and Applications (DASA'20), Bahrain (online), 8th – 9th November 2020. (Unpublished) [Conference paper]
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English abstract
With the exponential growth in the use of social networks and the massive generation of information on the internet, by 2020 it is expected that more than half of the world's population will have access to the internet and 84% will use a social network. These networks act as meeting points between people, create links and virtual communities with common interests or activities and allow contact between them, so they can communicate and exchange information; for its range and development, these digital media have great potential as a tool for companies to get to know their customers and with the increase in social media activities, emotions are seen as valuable products from a commercial perspective. By carefully evaluating people's opinion and feelings, companies can reasonably find out what people think about a product or service, and consequently make the most appropriate decision. The tool that support us to extract this information is the Sentiment Analysis and to learn more about it a review was developed based on a Bibliometric Analysis to know more about its evolution, trends, research areas, authors and outstanding publications.
Item type: | Conference paper |
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Keywords: | decision models; marketing; sentiment analysis; competitive intelligence; business intelligence; artificial intelligence; bibliometric analysis; science mapping; strategic intelligence |
Subjects: | I. Information treatment for information services I. Information treatment for information services > IB. Content analysis (A and I, class.) |
Depositing user: | J.R. López-Robles |
Date deposited: | 19 Feb 2021 23:10 |
Last modified: | 19 Feb 2021 23:10 |
URI: | http://hdl.handle.net/10760/41774 |
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