Opinion Mining, Sentiment Analysis and Emotion Understanding in Advertising: A Bibliometric Analysis
Metadatos
Afficher la notice complèteEditorial
Institute of Electrical and Electronics Engineers (IEEE)
Materia
Advertising Research Bibliometrics Communication Consumer behavior Emotion Understanding Opinion Mining Science Mapping Analysis SciMAT Sentiment analysis VOSviewer Web of Science (WoS)
Date
2020Referencia bibliográfica
Sánchez-Núñez, P., Cobo, M. J., De Las Heras-Pedrosa, C., Peláez, J. I., & Herrera-Viedma, E. (2020). Opinion Mining, Sentiment Analysis and Emotion Understanding in Advertising: A Bibliometric Analysis. IEEE Access, 8, 134563-134576. [DOI: 10.1109/ACCESS.2020.3009482]
Patrocinador
Programa Operativo FEDER Andalucia UMA 18-FEDERJA-148Résumé
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).