Social media tend to be rife with rumours while new reports are released piecemeal during breaking news. Interestingly, one can mine multiple reactions expressed by social media users in those situations, exploring their stance towards rumours, ultimately enabling the flagging of highly disputed rumours as being potentially false. In this work, we set out to develop an automated, supervised classifier that uses multi-task learning to classify the stance expressed in each individual tweet in a rumourous conversation as either supporting, denying or questioning the rumour. Using a classifier based on Gaussian Processes, and exploring its effectiveness on two datasets with very different characteristics and varying distributions of stances, we show that our approach consistently outperforms competitive baseline classifiers. Our classifier is especially effective in estimating the distribution of different types of stance associated with a given rumour, which we set forth as a desired characteristic for a rumour-tracking system that will warn both ordinary users of Twitter and professional news practitioners when a rumour is being rebutted.
There have been multiple attempts at defining rumours in the literature. Most of them are complementary to one another, with slight variations depending on the context of their analyses. The core concept that most researchers agree on matches the definition that major dictionaries provide, such as the Oxford English Dictionary http: www.oxforddictionaries.com definition english rumour defining a rumour as . For instance, DiFonzo and Bordia @cite_15 defined rumours as unverified and instrumentally relevant information statements in circulation.''
@cite_15
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The term ‘rumor’ is often used interchangeably with ‘gossip’ and ‘urban legend’ by both laypersons and scholars. In this article we attempt to clarify the construct of rumor by proposing a definition that delineates the situational and motivational contexts from which rumors arise (ambiguous, threatening or potentially threatening situations), the functions that rumors perform (sense-making and threat management), and the contents of rumor statements (unverified and instrumentally relevant information statements in circulation). To further clarify the rumor construct we also investigate the contexts, functions and contents of gossip and urban legends, juxtapose these with rumor, and analyze their similarities and differences.