Detection and Resolution of Rumours in Social Media: A Survey
Arkaitz Zubiaga, Ahmet Aker, Kalina Bontcheva, Maria Liakata, Rob, Procter

TL;DR
This survey reviews methods for detecting, tracking, and verifying rumours on social media, highlighting challenges and progress in developing automated classification systems for unverified information.
Contribution
It provides a comprehensive overview of existing research on social media rumours and proposes a framework for future rumour classification systems.
Findings
Research has advanced in rumour detection and stance classification.
Various approaches exist for rumour veracity assessment.
Future research directions include improved real-time detection methods.
Abstract
Despite the increasing use of social media platforms for information and news gathering, its unmoderated nature often leads to the emergence and spread of rumours, i.e. pieces of information that are unverified at the time of posting. At the same time, the openness of social media platforms provides opportunities to study how users share and discuss rumours, and to explore how natural language processing and data mining techniques may be used to find ways of determining their veracity. In this survey we introduce and discuss two types of rumours that circulate on social media; long-standing rumours that circulate for long periods of time, and newly-emerging rumours spawned during fast-paced events such as breaking news, where reports are released piecemeal and often with an unverified status in their early stages. We provide an overview of research into social media rumours with the…
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See pages 1-last of csur-rumours.pdf
