Anorexia Nervosa (AN) is a serious mental disorder that has
been proved to be traceable on social media through the analysis of users’
written posts. Here we present an approach to generate word embeddings
enhanced for a classification task dedicated to the detection of Reddit
users with AN. Our method extends Word2vec’s objective function in
order to put closer domain-specific and semantically related words. The
approach is evaluated through the calculation of an average similarity
measure, ...
Anorexia Nervosa (AN) is a serious mental disorder that has
been proved to be traceable on social media through the analysis of users’
written posts. Here we present an approach to generate word embeddings
enhanced for a classification task dedicated to the detection of Reddit
users with AN. Our method extends Word2vec’s objective function in
order to put closer domain-specific and semantically related words. The
approach is evaluated through the calculation of an average similarity
measure, and via the usage of the embeddings generated as features for
the AN screening task. The results show that our method outperforms
the usage of fine-tuned pre-learned word embeddings, related methods
dedicated to generate domain adapted embeddings, as well as representations
learned on the training set using Word2vec. This method can
potentially be applied and evaluated on similar tasks that can be formalized
as document categorization problems. Regarding our use case, we
believe that this approach can contribute to the development of proper
automated detection tools to alert and assist clinicians.
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