Alexithymia is a condition that partially or completely deprives you of the ability to identify and describe emotions, and to show affective connotations in the actions of an individual. This problem has been taken to different research projects that seek to study its characteristics, forms of prevention, and implications, and that try to determine a measurement for the experience of an individual with this construct as well as the responses they provide to certain stimuli. Other studies that were reviewed aimed to find a connection between the responses of subjects diagnosed with alexithymia when facing a dynamic of emotional facial expressions to recognize and their assigned grade based on the Toronto Alexithymia Scale (TAS), a metric frequently used to evaluate the presence or absence of alexithymia in an individual. In this work, a review of the different articles that study this connection, as well as articles that describe the state of the art of the implementation of artificial intelligence algorithms applied to the treatment or prevention of secondary alexithymia is presented.

Suicide prevention is one of the great issues of the current era. Institutions such as the World Health Organization, have continued to search for all possible alternatives for early detection and timely prevention. Suicide rates have grown more and more in the world, and Mexico, although it is not the country with the most suicides, is one of the countries with the highest growth in recent years. At present, the use of social networks has generated great changes in the way we communicate. Expressing yourself through a social network begins to be more common than expressing ourselves to human beings. Several studies, which will be presented later, show that it is possible to determine from the content of social networks: cases of depression, risk of suicide, and other mental problems. The use of technological tools, such as Natural Language Processing, has served as an effective ally for the early detection of risks, such as abuse, bullying or even detecting emotional problems. The present research seeks to carry out an in-depth analysis in the state of the art of the application of Natural Language Processing as an ally for the detection of suicide risk from the analysis of texts for Mexican Spanish in Social Networks.