Reading the riots: what were the police doing on Twitter?

Procter, Rob; Crump, Jeremy; Karstedt, Susanne; Voß, Alex; Cantijoch, Marta

doi:10.4324/9781315775104-2

Cited by 50 publications

(94 citation statements)

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“…However, their use presents major challenges, not least because information posted on social media is not always reliable and its veracity needs to be checked before it can be considered as fit for use in the reporting of news, or decision-making in the case of responses to civil emergencies [22] or natural disasters [2]. Hence, it is vital that tools be developed that can aid: a) the detection of rumours; b) determination of their likely veracity.…”

Section: Resultsmentioning

confidence: 99%

“…Social media and user-generated content (UGC) are increasingly important in a number of different ways for the work of not only journalists but also government agencies such as the police and civil protection agencies [22]. However, their use presents major challenges, not least because information posted on social media is not always reliable and its veracity needs to be checked before it can be considered as fit for use in the reporting of news, or decision-making in the case of responses to civil emergencies [22] or natural disasters [2].…”

Section: Resultsmentioning

confidence: 99%

“…However, the speed at which news unfolds on social media means that much of the information posted in the early stages of an event is unverified [22], which makes it more difficult for the public to distinguish verified information from rumours and covering the news becomes more challenging for journalists [29].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Exploiting Context for Rumour Detection in Social Media

Zubiaga

Liakata

Procter

2017

Lecture Notes in Computer Science

Self Cite

223

116

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Abstract. Tools that are able to detect unverified information posted on social media during a news event can help to avoid the spread of rumours that turn out to be false. In this paper we compare a novel approach using Conditional Random Fields that learns from the sequential dynamics of social media posts with the current state-of-the-art rumour detection system, as well as other baselines. In contrast to existing work, our classifier does not need to observe tweets querying the stance of a post to deem it a rumour but, instead, exploits context learned during the event. Our classifier has improved precision and recall over the state-of-the-art classifier that relies on querying tweets, as well as outperforming our best baseline. Moreover, the results provide evidence for the generalisability of our classifier.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Exploiting Context for Rumour Detection in Social Media

Zubiaga

Liakata

Procter

2017

Lecture Notes in Computer Science

Self Cite

223

116

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show abstract

“…Hashtags like #LondonRiots and #RiotCleanup used to organise these activities were estimated to have reached over 7 million Twitter users. Police forces used Twitter mainly for broadcasting purposes instead of intervening and systematically gathering information, which proved difficult due to the speed of events (Procter et al, 2013). However, the initiative to identify suspects following the release of CCTV images of rioters by the police proved to be very popular.…”

Section: Managing Uncertainty: the Riots Of August 2011mentioning

confidence: 99%

Social media in emergency management: Twitter as a tool for communicating risks to the public

Panagiotopoulos

Barnett

Bigdeli

et al. 2016

Technological Forecasting and Social Change

209

146

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One of the main challenges of emergency management lies in communicating risks to the public. On some occasions, risk communicators might seek to increase awareness over emerging risks, while on others the aim might be to avoid escalation of public reactions. Social media accounts offer an opportunity to rapidly distribute critical information and in doing so to mitigate the impact of emergencies by influencing public reactions. This article draws on theories of risk and emergency communication in order to consider the impact of Twitter as a tool for communicating risks to the public. We analyse 10,020 Twitter messages posted by the official accounts of UK local government authorities (councils) in the context of two major emergencies: the heavy snow of December 2010 and the riots of August 2011. Twitter was used in a variety of ways to communicate and manage associated risks including messages to provide official updates, encourage protective behaviour, increase awareness and guide public attention to mitigating actions. We discuss the importance of social media as means of increasing confidence in emergency management institutions.

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“…In the case of the former, the ability to sample freely and easily from the "Twitter firehose" has led to studies ranging from studies of criminal behavior [6], political voting, financial markets [7], population health [8], and even the advancement of the seasons. A strong case can now be made, especially in the case of Twitter, that the widespread availability of these data are driving the applications.…”

Section: Academic Studies Exploiting Novel Data Sources Are Scarce Tmentioning

confidence: 99%

Big Data for Social Science Research

Birkin¹

2018

Ubiquity

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Academic studies exploiting novel data sources are scarce. Typically, data is generated by commercial businesses or government organizations with no mandate and little motivation to share their assets with academic partners---partial exceptions include social messaging data and some sources of open data. The mobilization of citizen sensors at a massive scale has allowed for the development of impressive infrastructures. However, data availability is driving applications---problems are prioritized because data is available rather than because they are inherently important or interesting. The U.K. is addressing this through investments by the Economic and Social Research Council in its Big Data Network. A group of Administrative Data Research Centres are tasked with improving access to data sets in central government, while a group of Business and Local Government Centres are tasked with improving access to commercial and regional sources. This initiative is described. It is illustrated by examples from health care, transport, and infrastructure. In all of these cases, the integration of data is a key consideration. For social science problems relevant to policy or academic studies, it is unlikely all the answers will be found in a single novel data source, but rather a combination of sources is required. Through such synthesis great leaps are possible by exploiting models that have been constructed and refined over extended periods of time e.g., microsimulation, spatial interaction models, agents, discrete choice, and input-output models. Although interesting and valuable new methods are appearing, any suggestion that a new box of magic tricks labeled "Big Data Analytics" that sits easily on top of massive new datasets can radically and instantly transform our long-term understanding of society is naïve and dangerous. Furthermore, the privacy and confidentiality of personal data is a great concern to both the individuals concerned and the data owners.

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Reading the riots: what were the police doing on Twitter?

Cited by 50 publications

References 0 publications

Exploiting Context for Rumour Detection in Social Media

Exploiting Context for Rumour Detection in Social Media

Social media in emergency management: Twitter as a tool for communicating risks to the public

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