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Anxiety detection using the AMAS-C test and feeling analysis on the Facebook social network
This research exposes the proposal of a web application based on Facebook, Meaning Cloud and AMAS-C test tools, with the purpose of predicting anxiety in university students. For this purpose, a prediction algorithm was developed that takes the processed information from the publications of the Facebook users and compares it with the information of the previous learning, giving as a result the prediction of total anxiety of the individual. Finally, this research exposes an average absolute error 8 of 84 possible points, corresponding to the AMAS-C test scale, where 5 correct predictions, 12 medium correct predictions and 3 erroneous predictions were obtained. The conclusion is that the tools selected together with the proposed algorithm could be used as an alternative to the AMAS-C test.