Predictive Analytics

This article is based on a research project conducted by the SecDev Group in collaboration with the U.S. National Institute for Justice (NIJ) in San Diego.

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This article is a seminal piece and a foundational resource in the field of social media analytics and open source intelligence by some of the field’s leading authors.

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This is a foundational report and a seminal work in the study of social media intelligence and open source research. The paper reviews 245 papers in a semi-systematic literature review of how information and insight can be drawn from open social media sources.

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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.

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This article addresses the degree to which geolocation prediction is vital to geospatial applications like localised search and local event detection.

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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.

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This paper investigates the possibility of forecasting spikes in social tension – defined by the UK police service as “any incident that would tend to show that the normal relationship between individuals or groups has seriously deteriorated” – through social media.

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This explanatory thesis is concerned with user generated text, audio and video media. According to Tsagkias two aspects, the social and user generated content, led to the development of two main research branches in social media analysis.

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This article attempts to address the challenge of surveilling potential lone-wolf terrorists. Since these individuals act on their own, information cannot be collected using traditional police methods such as infiltration or wiretapping. Cohen et al.

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This article concerns whether social media is a valid indicator of political behavior. As the authors discuss, there is considerable debate about the validity of data extracted from social media for studying offline behavior.

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