University of Cambridge
Understanding the behaviour and influence of automated social agents
Abstract
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.
Degree
thesis:*- Name dc:type.qualificationname
- Doctor of Philosophy (PhD)
- Level dc:type.qualificationlevel
- Doctoral
- Grantor dc:publisher.institution
- University of Cambridge
- Year dc:date.issued
- 2018
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Gilani, Syed Zafar ul Hussan
- Advisor dc:contributor.advisor
-
- Crowcroft, Jonathan
Subjects
dc:subject × 7Rights
dc:rightsIdentifiers
dc:identifier.*- Author Identifier
- 0000-0002-7013-0121
- OAI identifier oai:identifier
- oai:www.repository.cam.ac.uk:1810/279022