Rumour detection in social media

No Thumbnail Available
File version
Author(s)
Nguyen, Quoc Viet Hung
Stantic, Bela
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)

Pedersen, John Storm

Wilkinson, Adrian

Date
2019
Size
File type(s)
Location
License
Abstract

Our society is struggling with a large number of derogatory rumours that threaten economies, democracy and cybersecurity. A major source of rumours comes from social platforms due to their lack of information authentication. While rumours can have severe real-world implications, their detection is notoriously hard: content on social platforms is brief and lacks semantics; it spreads quickly through a dynamically evolving network; and without considering the context of content, it may be impossible to arrive at a truthful interpretation. In this chapter, we harness the advances of big data and artificial intelligence models for early detection of rumours before the damage is out of control. Successful rumour detection prevents deceptive content from polluting our social media and restores public’s trust.

Journal Title
Conference Title
Book Title

Big Data Promise, Application and Pitfalls

Edition
Volume
Issue
Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Information systems

Persistent link to this record
Citation

Nguyen, QVH; Stantic, B, Rumour detection in social media, Big Data Promise, Application and Pitfalls, 2019, pp. 348-365

Collections