Resumo

CABRERA ARRIAGA, Tania et al. Scrutiny of depression and anxiety on Twitter through a word analysis program. Investigación educ. médica [online]. 2015, vol.4, n.13, pp.16-21. ISSN 2007-5057.

Introduction: Twitter is the second most used social network in the country, with about 10.2 million users. It is possible that mood may be reflected in texts posted by users of Twitter. A group of specialists designed a software that attempted to analyze the statements posted on Twitter and to detect various components of personality. The study focused on ascertaining whether it is possible to use these postings as elements for depression or anxiety, and comparing the consistency between the interpretation of software testing and in vivo using a standardized diagnostic inventory. Methods: A correlational comparative study with convenience sampling of 18 to 24 year-old medical students from the Autonomous Metropolitan University who have active Twitter accounts by applying, in person, the Depression and Beck Anxiety Inventories. Once applied, it was used in the accounts of Twitter Software Analyze Words for the analysis of their postings. The results were downloaded and analyzed using the SPSS program. Results: The minimum score for the Beck Anxiety Inventory was 0, the maximum was 29, and the mean was 9.37. For depression, the minimum was 0, the maximum 20, and the mean 4.94. For the tests performed by the Words Analyze software for anxiety, the lowest result was 19, a maximum of 99, and a mean of 54.58. A minimum of 35, a maximum of 66, and a mean of 51.89 was obtained for depression. A value of Pearson correlation of -.197 was obtained for anxiety in the analysis with the Beck inventory and Analyze Words software. Similarly, Pearson R value of .047 was obtained in the same tests for depression. Conclusions: There is no agreement between the results, and it is considered that the software is designed for the U.S. population and postings by Mexican users do not project their emotions as it does for Americans and would not have the necessary characteristics to determine mood. In conclusion this study shows that Twitter is not a diagnosis indicator of probable depressive or anxiety disorders.

Palavras-chave : Anxiety; Depression; Moods; Analyze Words Software.

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