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Understanding the behaviour and influence of automated social agents

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cam.restrictionthesis_access_open
cam.supervisorCrowcroft, Jonathan
cam.supervisor.orcidCrowcroft, Jonathan [0000-0002-7013-0121]
cam.thesis.fundingfalse
dc.contributor.authorGilani, Syed Zafar ul Hussan
dc.date.accessioned2018-08-28T10:37:05Z
dc.date.available2018-08-28T10:37:05Z
dc.date.issued2018-08-24
dc.date.submitted2018-02-23
dc.date.updated2018-08-22T15:58:56Z
dc.descriptionSoft-bound submitted: Fri 23 Feb 2018 Corrections submitted: Mon 30 Jul 2018 Corrections approved: Tue 7 Aug 2018 Apollo submitted: Wed 22 Aug 2018 Hard-bound submitted: Fri 24 Aug 2018
dc.description.abstractOnline social networks (OSNs) have seen a remarkable rise in the presence of automated social agents, or social bots. Social bots are the new computing viral, that are surreptitious and clever. What facilitates the creation of social agents is the massive human user-base and business-supportive operating model of social networks. These automated agents are injected by agencies, brands, individuals, and corporations to serve their work and purpose; utilising them for news and emergency communication, marketing, social activism, political campaigning, and even spam and spreading malicious content. Their influence was recently substantiated by coordinated social hacking and computational political propaganda. The thesis of my dissertation argues that automated agents exercise a profound impact on OSNs that transforms into an array of influence on our society and systems. However, latent or veiled, these agents can be successfully detected through measurement, feature extraction and finely tuned supervised learning models. The various types of automated agents can be further unravelled through unsupervised machine learning and natural language processing, to formally inform the populace of their existence and impact.
dc.description.sponsorshipSep'14-Aug'17, Marie Curie ITN METRICS, Early-Stage Researcher Sep'17, UMobile, Research Associate Oct'17-Mar'18, EPSRC Global Challenges Research Fund, Research Associate
dc.identifier.doi10.17863/CAM.26395
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/279022
dc.language.isoen
dc.publisher.collegeSelwyn College
dc.publisher.departmentDepartment of Computer Science and Technology (Computer Laboratory)
dc.publisher.institutionUniversity of Cambridge
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectcomputational social science
dc.subjectautomated social agents
dc.subjectsocial bot characterisation
dc.subjectsocial bot detection
dc.subjectsocial bot typification
dc.subjectsocial bot information propagation
dc.subjectsocial bot influence
dc.titleUnderstanding the behaviour and influence of automated social agents
dc.typeThesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (PhD)
dc.type.qualificationtitlePhD in Computer Science

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