In the last decades, researchers have been provided with a huge amount of data thanks to the diffusion of online sources. Additionally, more companies are issuing reports and documents to share information with stakeholders about their sustainable approach to both strengthen and encourage people to adopt a similar approach. To support researchers in managing the increasing quantity of information, several tools have been provided for text mining studies, such as sentiment analysis, semantic analysis, and content analysis. We proposed to analyse the usefulness of automated and semi-automated techniques on a dataset composed of more than 875,000 tweets posted by the companies that Forbes (2020) considers to be the most sustainable. We chose to focus on sustainability because it is a topic of interest to the global community, as revealed by the significant amount of attention that companies are paying to it. In detail, we performed a double-step analysis: firstly, a comparison between exact words and stemmed words; secondly, a description of communication efforts and topics that firms opted for when dealing with sustainability. Our expected contribution is mainly methodological, as we provide suggestions regarding the advantages of performing the analysis in one of the two ways, while the research context offers insights into sustainability reporting.
One More Tweet: Firms Challenge a Sustainable Future / Tregua, Marco; D'Auria, Anna. - In: PUNTOORG. - ISSN 2499-1333. - 5:2(2020), pp. 201-219.
One More Tweet: Firms Challenge a Sustainable Future
Tregua, Marco
;
2020
Abstract
In the last decades, researchers have been provided with a huge amount of data thanks to the diffusion of online sources. Additionally, more companies are issuing reports and documents to share information with stakeholders about their sustainable approach to both strengthen and encourage people to adopt a similar approach. To support researchers in managing the increasing quantity of information, several tools have been provided for text mining studies, such as sentiment analysis, semantic analysis, and content analysis. We proposed to analyse the usefulness of automated and semi-automated techniques on a dataset composed of more than 875,000 tweets posted by the companies that Forbes (2020) considers to be the most sustainable. We chose to focus on sustainability because it is a topic of interest to the global community, as revealed by the significant amount of attention that companies are paying to it. In detail, we performed a double-step analysis: firstly, a comparison between exact words and stemmed words; secondly, a description of communication efforts and topics that firms opted for when dealing with sustainability. Our expected contribution is mainly methodological, as we provide suggestions regarding the advantages of performing the analysis in one of the two ways, while the research context offers insights into sustainability reporting.File | Dimensione | Formato | |
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