Policing cyber-neighbourhoods: tension monitoring and social media networks
Policing cyber-neighbourhoods: tension monitoring and social media networks
复制标题
网络社区治安：紧张局势监控和社交媒体网络
DOI：
10.1080/10439463.2013.780225
复制
发表时间：
2013
影响因子：
2.7
通讯作者：
Luke S Sloan
中科院分区：
文献类型：
--
作者：
M. Williams;Adam Edwards;W. Housley;P. Burnap;O. Rana;Nick Avis;Jeffrey Morgan;Luke S Sloan
我们建议，晚现代警务的做法，依赖于邻里情报，紧张局势的监测，监视和警务住宿，需要加强在新兴的“网络邻里”，即社交媒体网络。2011年的英格兰骚乱是第一次证明社交媒体平台被广泛用于组织和应对骚乱。警方装备不足，无法利用来自这些非地球网络的情报，而且被发现在更精通技术的暴徒和公众面前处于不利地位。在本文中，我们概述了卡迪夫在线社交媒体ObServatroy（COSMOS）的“张力引擎”组件的开发。该引擎为用户提供了监控社交媒体数据流的能力，以发现可以分析的高度紧张迹象，从而确定偏离“规范”（凝聚力/低紧张水平）的情况。这种分析可以叠加到一个精心策划的数据库上，例如关于邻里犯罪、贫困和人口统计的官方统计数据，以提供一个“地面”和“网络”街道的多维图景。因此，这种“邻里信息学”通过参考用户生成的社交媒体账户及其与其他精心策划的社会和经济数据的关系，使人们能够质疑官方对内乱的解释。
We propose that late modern policing practices, that rely on neighbourhood intelligence, the monitoring of tensions, surveillance and policing by accommodation, need to be augmented in light of emerging ‘cyber-neighbourhoods’, namely social media networks. The 2011 riots in England were the first to evidence the widespread use of social media platforms to organise and respond to disorder. The police were ill-equipped to make use of the intelligence emerging from these non-terrestrial networks and were found to be at a disadvantage to the more tech-savvy rioters and the general public. In this paper, we outline the development of the ‘tension engine’ component of the Cardiff Online Social Media ObServatroy (COSMOS). This engine affords users with the ability to monitor social media data streams for signs of high tension which can be analysed in order to identify deviations from the ‘norm’ (levels of cohesion/low tension). This analysis can be overlaid onto a palimpsest of curated data, such as official statistics about neighbourhood crime, deprivation and demography, to provide a multidimensional picture of the ‘terrestrial’ and ‘cyber’ streets. As a consequence, this ‘neighbourhood informatics’ enables a means of questioning official constructions of civil unrest through reference to the user-generated accounts of social media and their relationship to other, curated, social and economic data.
DOI：
10.1016/j.techfore.2013.04.013
发表时间：
2015-06-01
影响因子：
12
作者：
Burnap, Pete;Rana, Omer F.;Sloan, Luke
通讯作者：
Sloan, Luke