Since social media platforms also contain great clues about the personalities of those who share, they can also be a center where research and new technologies are developed in the scientific world. Much of this research is done on Twitter. The latest technology developed by scientists is of great importance.
According to new research published in the journal IEEE Transactions on Affective Computing, scientists have developed an algorithm that can detect whether users are depressed on Twitter. Moreover, it was shared that the success rate of the algorithm is almost 90%. So how does the algorithm know if a person is depressed?
Users analyzed from 38 data points
Algorithm based on shared details, users’ profile photos on Twitter, content in their posts, sharing times, other users in their social circles It evaluates by taking a total of 38 data points. To be successful, the algorithm was trained with two different databases that contain the Twitter history of thousands of Twitter users and display their mental health status.
80% of the data in the database was used to train the algorithm, while the remaining data was kept for testing the algorithm. As a result of the tests performed with this data, which the algorithm has never seen before, it was announced that the algorithm achieved 89% success. In John Hopkins University’s CLPsych 2015 data, this success rate dropped to 71%.
Scientists announced that if the algorithm in question is developed, social media such as Twitter and Facebook can constantly monitor the mental health of users for prevention purposes. On the other hand, although the data used in this study is given at the request of the user, the fact that not everyone wants to share their data in the future has already started the data discussions.
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