Twitter

This paper evaluates two tools for the automated identification of demographic and occupational data from the profile descriptions of Twitter users in the United Kingdom.

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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 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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This paper sets out to interpolate and predict state-level polling at the daily level by employing a dataset of over 500GB of political tweets from the final months of the 2012 presidential campaign.

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McCreadie, Macdonald and Ounis discuss the use of social media platforms, such as Twitter, to track significant events. Emergency response agencies are increasingly looking to social media as a source of real-time information about such events.

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In 2013, The SecDev Group undertook a 10-month Kanishka-funded project that set out, in part,  to explore methodologies and technologies for open source social media (OSSM) research and their potential utility for detecting weak signals of radicalization towards violent extremism online.

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This research note summarizes experimental research conducted by The SecDev Group in 2013, as part of a Public Safety Canada, Kanishka-funded project looking at social media analytics and the prevention of violent extremism.

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This experiment used the Twitter profile of a U.K. national, verified to be an active foreign fighter (FF) in the Syrian civil war, as the seed for constructing a network topology based on social media interactions.

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This summary captures the main findings of a longitudinal content analysis of a known foreign fighter’s (FF) public social media activity for signs of radicalization toward violent extremism.

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This 2013 article focuses on identifying and measuring the influence of extremist accounts on Twitter, assessing extremist content, and determining ways to counter violent extremism (CVE) in online social networks.

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