This 2012 article focuses on predictive analytics and in particular crime prediction using events and data extracted from Twitter posts. The authors present a preliminary investigation of Twitter-based criminal incident prediction.
This paper addresses several of the key issues facing creation of a classifier for hate-speech on forums, blogs, or other areas of web discourse.
This article presents methods for identifying the recruitment activities of violent groups within extremist social media websites.
This article focuses on challenges to law enforcement when dealing with massive amounts of data in criminal investigations.
This article deals with a supervised machine learning text classifier, trained and tested to distinguish between hateful and/or antagonistic response with a focus on race, ethnicity or religion; and more general responses.
This article addresses the degree to which geolocation prediction is vital to geospatial applications like localised search and local event detection.
This paper concerns the creation of a prototype for sentiment analysis, capable of discerning key aspects of an entity under review, and the type of polarity in the response associated with it.
This article reveals just how vital geographical location is to geospatial applications like local search and event detection. In this paper, the research team investigates and seeks to improve on the task of text-based geolocation prediction of Twitter users.
In this paper, the authors argue that despite the widespread use of social media in various domains (e.g.
This portal gathers an annotated collection of recent research on the ways in which social media and new technologies may be leveraged in the fight against violent extremism