Like, Share, and React: Twitter Capture for Research and Corporate Decisions



Main Article Content

Djeison Siedschlag
https://orcid.org/0000-0001-6986-573X orcid
Jeferson Lana
https://orcid.org/0000-0002-9787-1114 orcid
Roberto Gonçalves Augusto Junior
https://orcid.org/0000-0002-8735-931X orcid
Rosilene Marcon
https://orcid.org/0000-0002-0478-7715 orcid

Abstract

Context: social media have an immense amount of information, being a space for its dissemination. Individuals, online connections, are able to filter or give visibility to certain information, to the detriment of others. The central problem lies in monitoring posts and reactions aimed at corporate actions and strategies. In addition to this monitoring, companies can make decisions based on the data collected. Objective: to develop and structure a social media management tool. Methods: to achieve the general objective, the article was developed in three main steps. The first was to suggest a free software script for capturing and initial analysis of Twitter posts. The second step was to categorize this analysis and identify resources and competencies needed by companies. Finally, actions to be taken by companies for social media management were suggested. Results: the developed script enabled the automated extraction of data, which were stored in a database for analysis and management of online interactions. The actions were proposed based on the case study developed. Conclusions: in the practical field, this study contributes to the process of extracting data from Twitter by proposing a new script for capturing data, identifying the main categories of influence of digital activists and monitoring social media through strategic actions. By demonstrating that the script is effective in extracting data, it is possible to carry out further studies and implement the social media management monitoring process.



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How to Cite
Siedschlag, D., Lana, J., Augusto Junior, R. G., & Marcon, R. (2022). Like, Share, and React: Twitter Capture for Research and Corporate Decisions. Journal of Contemporary Administration, 27(2), e220008. https://doi.org/10.1590/1982-7849rac2023220008.en
Section
Technological Articles

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