New machine learning models can detect hate speech and violence from texts | Phys.Org - Technology - Computer Sciences
"The words we use and
our writing styles can reveal information about our preferences,
thoughts, emotions and behaviours." summarizes Phys.Org
Using this information, a new study from the University of Eastern Finland has developed machine learning models that can detect antisocial behaviours, such as hate speech and indications of violence, from texts.
Historically, most attempts to address antisocial behaviour have been done from education, social and psychological points of view. This new study has, however, demonstrated the potential of using natural language processing techniques to develop state-of-the-art solutions to combat antisocial behaviour in written communication.
The study created solutions that can be integrated in web forums or social media websites to automatically or semi-automatically detect potential incidences of antisocial behaviour with high accuracies, allowing for fast and reliable warnings and interventions to be made before the possible acts of violence are committed.
One of the great challenges in detecting antisocial behaviour is first defining what precisely counts as antisocial behaviour and then determining how to detect such phenomena. Thus, using an exploratory and interdisciplinary approach, the study applied natural language processing techniques to identify, extract and utilise the linguistic features, including emotional features, pertaining to antisocial behaviour.