The aim of this paper is to provide a framework for the construction of a composite indicator (CI) to characterize Corporate Social responsibility (CSr) online communication. To this purpose we focus on the firms included in the Dow Jones Industrial Average index and their Twitter accounts. The proposed CI results from the combination of two macro-dimensions: communication content and communication modality (information and media richness). In order to identify the content, we use the Structural Topic Model (STM) which allows to discover and link the topics to CSr dimensions. We discuss the construction of simple indexes, and we address aggregation strategies. The proposed composite indicator may help researchers and policy makers to monitor the behaviour of companies with reference to sustainable development and the Agenda 2030. It also contributes to the advancement of methodological knowledge for the construction of socioeconomic composite indicators using textual data.
Salvatore, C., Biffignandi, S., Bianchi, A. (2022). Assessing Corporate Social Responsibility Communication on Twitter: A Composite Indicator Approach. In Proceedings of the 16th International Conference on statistical analysis of textual data vol.2 (pp.787-793). Cosenza : Erranti.
Assessing Corporate Social Responsibility Communication on Twitter: A Composite Indicator Approach
Salvatore, C;
2022
Abstract
The aim of this paper is to provide a framework for the construction of a composite indicator (CI) to characterize Corporate Social responsibility (CSr) online communication. To this purpose we focus on the firms included in the Dow Jones Industrial Average index and their Twitter accounts. The proposed CI results from the combination of two macro-dimensions: communication content and communication modality (information and media richness). In order to identify the content, we use the Structural Topic Model (STM) which allows to discover and link the topics to CSr dimensions. We discuss the construction of simple indexes, and we address aggregation strategies. The proposed composite indicator may help researchers and policy makers to monitor the behaviour of companies with reference to sustainable development and the Agenda 2030. It also contributes to the advancement of methodological knowledge for the construction of socioeconomic composite indicators using textual data.
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