Abstract
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.
Highlights
Sentiment analysis and opinion mining are an automatic mass classification of textual and visual information, which focuses on cataloguing and classifying data according to the polarity—the positive or negative connotation—of the language used in them (Pang and Lee 2008; Prabowo and Thelwall 2009)
The results derived from bibliometric analysis obtained theofWeb of Science (WoS)
OMSAMC has been acquiring a crucial role in both research and commercial applications because of their probable applicability to numerous diverse fields, such as the identification of brand awareness, reputation and popularity at a specific moment or over time, the tracking of consumer reception of new products or features, the pinpoint targeting of an audience or the evaluation performance success of a marketing campaign
Summary
Sentiment analysis and opinion mining are an automatic mass classification of textual and visual information, which focuses on cataloguing and classifying data according to the polarity—the positive or negative connotation—of the language used in them (Pang and Lee 2008; Prabowo and Thelwall 2009) These positive or negative connotations of the language are reflected in opinions, attitudes and emotions expressed by Internet users (Mostafa 2013) in online mentions on digital ecosystems (Kennedy 2012; Mäntylä et al 2018). User opinions help people make informed decisions, and help organizations identify customer opinions, attitudes and emotions about the products and services they offer (Peláez et al 2019a) In this context, Opinion Mining and Sentiment Analysis in Marketing Communications (OMSAMC) are extremely important when it comes to analyzing consumer buying patterns.
Sign-in/Register to view highlights & summary 
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call