Identifying offenders on Twitter: A law enforcement practitioner guide

被引:4
|
作者
Horsman, Graeme [1 ]
Ginty, Kevin [1 ]
Cranner, Paul [1 ]
机构
[1] Univ Sunderland, Informat Ctr, St Peters Way, Sunderland SR6 0DD, Durham, England
关键词
Twitter; Crime; Digital forensics; Offender identification; Social media; SOCIAL NETWORK; ONLINE;
D O I
10.1016/j.diin.2017.09.004
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Twitter remains one of the most popular social media network sites in use today and continues to attract criticism over the volume of unsavoury and illegal content circulated by its users. When breaches of legislation occur, appropriate officials are left with the task of identifying and apprehending the physical user of an offending account, which is not always a simple task. This article provides a law enforcement practitioner focused analysis of the Twitter platform and associated services for the purposes of offender identification. Using our bespoke message harvesting tool 'Twitterstream', an analysis of the data available via Twitter's Streaming and REST APIs are presented, along with the message metadata which can be gleaned. The process of identifying those behind offending Twitter accounts is discussed in line with available API content and current Twitter data retention policies in order to support law enforcement investigations surrounding this social media platform. (c) 2017 Elsevier Ltd. All rights reserved.
引用
收藏
页码:63 / 74
页数:12
相关论文
共 50 条
  • [1] Focusing law enforcement when offenders can choose location
    Friehe, Tim
    Miceli, Thomas J.
    INTERNATIONAL REVIEW OF LAW AND ECONOMICS, 2015, 42 : 105 - 112
  • [2] UK-EU law enforcement cooperation post-Brexit: A UK law enforcement practitioner perspective
    Shellaker, Matthew
    Tong, Stephen
    Swallow, Paul
    CRIMINOLOGY & CRIMINAL JUSTICE, 2024, 24 (04) : 841 - 861
  • [3] A policy guide to the state of drug law enforcement research
    Mazerolle, Lorraine
    INTERNATIONAL JOURNAL OF DRUG POLICY, 2017, 41 : 164 - 165
  • [4] Identifying Communication Topologies on Twitter
    Kustudic, Mijat
    Xue, Bowen
    Zhong, Huifen
    Tan, Lijing
    Niu, Ben
    ELECTRONICS, 2021, 10 (17)
  • [5] The Impact of Police Attitudes Towards Offenders on Law-Enforcement Assisted Diversion Decisions
    Schaible, Lonnie
    Gant, Lauren
    Ames, Stephanie
    POLICE QUARTERLY, 2021, 24 (02) : 205 - 232
  • [6] Constructing influence on Twitter facing the announcement of the Referendum Law in Catalonia
    Moragas-Fernandez, Carlota M.
    Grau-Masot, Josep-Maria
    Capdevila-Gomez, Arantxa
    PROFESIONAL DE LA INFORMACION, 2019, 28 (03):
  • [7] A survey of current social network and online communication provision policies to support law enforcement identify offenders
    Horsman, Graeme
    DIGITAL INVESTIGATION, 2017, 21 : 65 - 75
  • [8] Twitter turing test: Identifying social machines
    Alarifi, Abdulrahman
    Alsaleh, Mansour
    Al-Salman, AbdulMalik
    INFORMATION SCIENCES, 2016, 372 : 332 - 346
  • [9] In Search of UX Translators: Analyzing Researcher-Practitioner Interactions on Twitter
    Brier, Jason
    Gray, Colin M.
    Kou, Yubo
    DIS'17 COMPANION: PROCEEDINGS OF THE 2017 ACM CONFERENCE ON DESIGNING INTERACTIVE SYSTEMS, 2017, : 111 - 115
  • [10] Identifying interesting Twitter contents using topical analysis
    Yang, Min-Chul
    Rim, Hae-Chang
    EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (09) : 4330 - 4336