The communication of corporate social responsibility (CSR) highlights the behavior of the business toward CSR and their framework of sustainable development (SD), thus helping policymakers understand the role businesses play with respect to the 2030 Agenda. Despite its importance, this is still a relatively underexamined and emerging topic. In our paper, we focus on what businesses communicate about CSR through social media and how this relates to the Sustainable Development Goals (SDGs). We identified the topics discussed on Twitter, their evolution over time, and the differences across sectors. We applied the structural topic model (STM) algorithm, which allowed us to estimate the model, including document-level metadata (time and sector). This model proved to be a powerful tool for topic detection and the estimation of the effects of time and sector on the discussion proportion of the topics. Indeed, we found that the topics were well identified overall, and the model allowed catching signals from the data. We derived CSR communication indexes directly from the topic model (TM) results and propose the use of dissimilarity and homogeneity indexes to describe the communication mix and highlight differences and identify clusters.

(2022). Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics [journal article - articolo]. In SOCIAL INDICATORS RESEARCH. Retrieved from http://hdl.handle.net/10446/227529

Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics

Bianchi, Annamaria
2022-01-01

Abstract

The communication of corporate social responsibility (CSR) highlights the behavior of the business toward CSR and their framework of sustainable development (SD), thus helping policymakers understand the role businesses play with respect to the 2030 Agenda. Despite its importance, this is still a relatively underexamined and emerging topic. In our paper, we focus on what businesses communicate about CSR through social media and how this relates to the Sustainable Development Goals (SDGs). We identified the topics discussed on Twitter, their evolution over time, and the differences across sectors. We applied the structural topic model (STM) algorithm, which allowed us to estimate the model, including document-level metadata (time and sector). This model proved to be a powerful tool for topic detection and the estimation of the effects of time and sector on the discussion proportion of the topics. Indeed, we found that the topics were well identified overall, and the model allowed catching signals from the data. We derived CSR communication indexes directly from the topic model (TM) results and propose the use of dissimilarity and homogeneity indexes to describe the communication mix and highlight differences and identify clusters.
articolo
20-ago-2022
2022
Inglese
cartaceo
online
164
3
1217
1248
Settore SECS-S/03 - Statistica Economica
Corporate sustainability; Indicators; Social media; Structural topic model; Sustainable development; Text mining;
Salvatore, Camilla; Biffignandi, Silvia; Bianchi, Annamaria
info:eu-repo/semantics/article
open
(2022). Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics [journal article - articolo]. In SOCIAL INDICATORS RESEARCH. Retrieved from http://hdl.handle.net/10446/227529
Non definito
3
1.1 Contributi in rivista - Journal contributions::1.1.01 Articoli/Saggi in rivista - Journal Articles/Essays
262
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/227529
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