"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.
Read more...
Source: Phys.Org