Detecting Traces of Self-harm on Reddit Through Emotional Patterns

AbstractCurrently, self-harm is considered one of the leading causes of death by suicide in young people. Timely detection of self-inflicted injury is important to help people before the illness gets worse, minimizing disabilities and returning them to their normal life. A popular way for people to share information is using social media platforms, where they tend to share topics related to work issues and personal matters. In fact, people suffering from mental disorders tend to share information about their concerns looking for some advice, support, or just because they want to relieve suffering. This creates an excellent opportunity to, for example, automatically detect users that have a suicidal intention and refer them as soon as possible to seek professional help. In this chapter, we describe a new text representation named Bag of Sub-Emotions (BoSE), which considers fine-grained emotions as the key information for the detection of users suffering from self-harm. We also present some extensions to BoSE aimed to better model and capture the emotional changes expressed by social media users through their posts. The proposed approach showed competitive performance in comparison to other methods evaluated in the eRisk collections but providing an easier understanding and interpretability of results.