An approach for analysing and segmenting messages about the SDGs on Twitter from the perspective of social marketing

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Abstract

This descriptive study aims to identify the most published SDGs by @GlobalGoalsUN, the United Nations' official account for sustainable development goals, and elaborate the segmentation profiles of these messages that promote a more significant impact from the perspective of social marketing and happiness. With more than 345 million active users in 2022, Twitter is a relevant social media tool for researching and knowing public reactions. In order to identify the most relevant SDGs, we have downloaded tweets from January 1, 2021, to September 30, 2022. The segmentation profiles have been elaborated with the classification tree using the division method called CHAID (Chi-square automatic interaction detector), which allows the automatic detection of interactions through Chi-square. This technique has made it possible to identify four homogeneous sub-samples corresponding to the segmentation profiles of messages based on impact, social marketing and happiness. The results of these profiles show the categories of the variables that best distinguish the messages. In addition, it has been verified that the most published SDGs do not coincide with those that have achieved the greatest impact. The climate has been the most published SDG (SDG 13 Climate action), but the one that has obtained the most significant reaction from the public has been the SDG related to well-being (SDG 3 Health and well-being). The most popular format has been video, the most recurrent emotional tone has been neutral, and, about social marketing, a category of action messages stands out, unlike behavioural ones, which do not specify the indications to carry out a specific initiative.

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Galiano-Coronil, A., Gil, M. O., Varela, B. M., & Ripoll, R. R. (2023). An approach for analysing and segmenting messages about the SDGs on Twitter from the perspective of social marketing. International Review on Public and Nonprofit Marketing, 20(3), 635–658. https://doi.org/10.1007/s12208-023-00369-3

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