Exploring social responsibility, social marketing and happiness using artificial intelligence, automated text analysis and correspondence analysis

Abstract

Purpose

This work aims to examine the communication on Twitter of the most responsible companies in Spain to identify the topics covered on corporate social responsibility (CSR) from the perspective of happiness and social marketing. In addition, the profiles of the messages that show an association with the impact of the messages have been identified.

Design/methodology/approach

An empirical analysis of the Twitter posts of Spain's ten most responsible companies has been carried out. The methodology of this work combines data mining techniques, sentiment analysis and content analysis, both from a quantitative and qualitative approach.

Findings

The results show that most brand tweets do not deal with CSR-related topics. The topics they address the most are those related to sports and the weather. From the perspective of social marketing, conversational-type tweets are the most published and have achieved the most significant reaction from the public. In addition, four messages' profiles have been identified based on the company and the emotional connotation associated with the impact, giving rise to more outstanding promotion of social causes.

Originality/value

Our main contribution to this work has been to value positive communication and social marketing to promote better CSR on Twitter. In this sense, it has been verified that there is a relationship between the public's reaction, the affective connotation and the company that issues the messages.

Citation

Galiano-Coronil, A., Aguirre Montero, A., López Sánchez, J.A. and Díaz Ortega, R. (2024), "Exploring social responsibility, social marketing and happiness using artificial intelligence, automated text analysis and correspondence analysis", Management Decision, Vol. 62 No. 2, pp. 549-574. https://doi.org/10.1108/MD-01-2023-0099