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Analysing and detecting twitter spam

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posted on 2016-09-01, 00:00 authored by C Chen
Through in-depth data-drive analysis, we provide insights on deceptive information in Twitter spam, spammers' behaviours and emerging spamming strategies. We also firstly identify and solve the "spam drift" problem. Online social network providers can adopt our findings and proposed scheme to re-design their detection system to improve its efficiency and accuracy.<br>

History

Open access

  • Yes

Material type

thesis

Resource type

thesis

Language

eng

Copyright notice

The Author. All Rights Reserved.

Editor/Contributor(s)

J Zhang, Y Xiang

Pagination

xvi, 168 pages : illustrations, tables, graphs, some coloured

Degree type

Research doctorate

Degree name

PhD

Thesis faculty

Faculty of Science

Thesis school

Engineering and Built Environment

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