1. Sentiment analysis to support business decision-making. A bibliometric study
- Author
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Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones, Aguilar Moreno, Juan Antonio, Palos Sánchez, Pedro Ramiro, Pozo Barajas, Rafael del, Universidad de Sevilla. Departamento de Economía Financiera y Dirección de Operaciones, Aguilar Moreno, Juan Antonio, Palos Sánchez, Pedro Ramiro, and Pozo Barajas, Rafael del
- Abstract
Customer feedback on online platforms is an unstructured database of growing importance for organizations, which, together with the rise of Natural Language Processing algorithms, is increasingly present when making decisions. In this paper, a bibliometric analysis is carried out with the intention of understanding the prevailing state of research about the adoption of sentiment analysis methods in organizations when making decisions. It is also a goal to comprehend which business sectors, and areas within the company, they are most applied, and to identify what future challenges that in this area may arise, as well as the main topics, authors, articles, countries, and universities most influential in the scientific literature. To this end, a total of 101 articles have been gathered from the Scopus and Clarivate Analytics Web of Science (WoS) databases, of which 85 were selected for analysis using the Bibliometrix tool. This study highlights the growing popularity of sentiment analysis methods combined with Multicriteria Decision Making and predictive algorithms. Twitter and Amazon are commonly used data sources, with applications across multiple sectors (supply chain, financial, etc.). Sentiment analysis enhances decision-making and promotes customer-centric approaches
- Published
- 2024