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Publication . Conference object . 2020

User Identity Linkage in Social Media Using Linguistic and Social Interaction Features

Despoina Chatzakou; Juan Soler-Company; Theodora Tsikrika; Leo Wanner; Stefanos Vrochidis; Ioannis Kompatsiaris;
Open Access
Published: 28 May 2020
Publisher: ACM

Social media users often hold several accounts in their effort to multiply the spread of their thoughts, ideas, and viewpoints. In the particular case of objectionable content, users tend to create multiple accounts to bypass the combating measures enforced by social media platforms and thus retain their online identity even if some of their accounts are suspended. User identity linkage aims to reveal social media accounts likely to belong to the same natural person so as to prevent the spread of abusive/illegal activities. To this end, this work proposes a machine learning-based detection model, which uses multiple attributes of users' online activity in order to identify whether two or more virtual identities belong to the same real natural person. The models efficacy is demonstrated on two cases on abusive and terrorism-related Twitter content.

Subjects by Vocabulary

Microsoft Academic Graph classification: Order (business) Social relation Linkage (mechanical) law.invention law Online identity Computer science Natural person Social media Viewpoints Internet privacy business.industry business Identity (social science)


Actor identity resolution, Abusive and Illegal content, Twitter

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Funded by
InterCONnected NEXt-Generation Immersive IoT Platform of Crime and Terrorism DetectiON, PredictiON, InvestigatiON, and PreventiON Services
  • Funder: European Commission (EC)
  • Project Code: 786731
  • Funding stream: H2020 | RIA
Validated by funder
Prediction and Visual Intelligence for Security Information
  • Funder: European Commission (EC)
  • Project Code: 833115
  • Funding stream: H2020 | IA
Validated by funder
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