2026-05-31T22:54:39Zhttps://riuma.uma.es/rest/oai/requestoai:riuma.uma.es:10630/193772026-02-03T10:56:14Zcom_10630_2254col_10630_37953
Opinion mining and sentiment analysis in marketing communications: a science mapping analysis in Web of Science (1998–2018)
Sánchez-Núñez, Pablo
De-las-Heras-Pedrosa, Carlos
Peláez-Sánchez, José Ignacio
Bibliometría
Opinion mining and sentiment analysis has become ubiquitous in our society, with
applications in online searching, computer vision, image understanding, artificial intelligence and
marketing communications (MarCom). Within this context, opinion mining and sentiment analysis
in marketing communications (OMSAMC) has a strong role in the development of the field by
allowing us to understand whether people are satisfied or dissatisfied with our service or product
in order to subsequently analyze the strengths and weaknesses of those consumer experiences. To
the best of our knowledge, there is no science mapping analysis covering the research about opinion
mining and sentiment analysis in the MarCom ecosystem. In this study, we perform a science
mapping analysis on the OMSAMC research, in order to provide an overview of the scientific work
during the last two decades in this interdisciplinary area and to show trends that could be the basis
for future developments in the field. This study was carried out using VOSviewer, CitNetExplorer
and InCites based on results from Web of Science (WoS). The results of this analysis show the
evolution of the field, by highlighting the most notable authors, institutions, keywords,
publications, countries, categories and journals.
2020-03-10T08:34:35Z
2020-03-10T08:34:35Z
2020
2020
journal article
Sánchez-Núñez, P., de las Heras-Pedrosa, C. & Peláez, J.I., 2020. Opinion Mining and Sentiment Analysis in Marketing Communications: A Science Mapping Analysis in Web of Science (1998–2018). Social Sciences, 9(3), p.23. http://dx.doi.org/10.3390/socsci9030023.
https://hdl.handle.net/10630/19377
http://dx.doi.org/10.3390/socsci9030023
eng
open access
MDPI