Opinion Mining, Sentiment Analysis and Emotion Understanding in Advertising: A Bibliometric Analysis

Identificadores
URI: http://hdl.handle.net/10498/23610
DOI: 10.1109/ACCESS.2020.3009482
ISSN: 2169-3536
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Mostrar el registro completo del ítemFecha
2020Departamento/s
Ingeniería InformáticaFuente
IEEE Access ( Volume: 8 ) Page(s): 134563 - 134576Resumen
In the last decade, the advertising industry has experienced a quantum leap, powered by recent advances in neuroscience, a large investment in artificial intelligence, and a high degree of consumer expertise. Within this context, opinion mining, sentiment analysis, and emotion understanding bring us closer to one of the most sought-after objectives of advertising: to offer relevant ads at scale. The importance of studies about opinion mining, sentiment analysis, and emotion understanding in advertising has been rising exponentially over the last years. The peak of this new situation has been the interest of the research community in studying the relationship between such innovations and the spread of smart and contextual advertising. This article analyzes those works that address the relationship between sentiment analysis, opinion mining, and emotion understanding in advertising. The main objective is to clarify the current state of these studies, explore issues, methods, findings, themes, and gaps as well as to define their significance within the current convergence advertising research scenario. To reach such objectives, a bibliometric analysis was conducted, retrieving and analyzing 919 research works published between 2010 and 2019 based on results from Web of Science (WoS).
Materias
Advertising; Sentiment analysis; Bibliometrics; Organizations; Registers; Indexes; Computer science; Advertising research; bibliometrics; communication; consumer behavior; emotion understanding; opinion mining; science mapping analysis; SciMAT; sentiment analysis; VOSviewer; Web of Science (WoS)Colecciones
- Artículos Científicos [12009]
- Articulos Científicos Ing. Inf. [313]
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