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