Point Process Modelling of Rumour Dynamics in Social Media
نویسندگان
چکیده
Rumours on social media exhibit complex temporal patterns. This paper develops a model of rumour prevalence using a point process, namely a log-Gaussian Cox process, to infer an underlying continuous temporal probabilistic model of post frequencies. To generalize over different rumours, we present a multi-task learning method parametrized by the text in posts which allows data statistics to be shared between groups of similar rumours. Our experiments demonstrate that our model outperforms several strong baseline methods for rumour frequency prediction evaluated on tweets from the 2014 Ferguson riots.
منابع مشابه
FootballWhisper: Transfer Rumour Detection
Social media has been shown to have potential to predict various real world events, such as movements in the stock market and the outcomes of political elections. In this paper we present the Football Whispers (FW), a website dedicated to fans discussing transfer rumours. The unique selling point of the site is that it provides a crowdsourced assessment of those rumours, measuring the relative ...
متن کاملLearning Reporting Dynamics during Breaking News for Rumour Detection in Social Media
Breaking news leads to situations of fast-paced reporting in social media, producing all kinds of updates related to news stories, albeit with the caveat that some of those early updates tend to be rumours, i.e., information with an unverified status at the time of posting. Flagging information that is unverified can be helpful to avoid the spread of information that may turn out to be false. D...
متن کاملUsing Gaussian Processes for Rumour Stance Classification in Social Media
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 cla...
متن کاملAnalysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads
As breaking news unfolds people increasingly rely on social media to stay abreast of the latest updates. The use of social media in such situations comes with the caveat that new information being released piecemeal may encourage rumours, many of which remain unverified long after their point of release. Little is known, however, about the dynamics of the life cycle of a social media rumour. In...
متن کاملExploiting Context for Rumour Detection in Social Media
Tools that are able to detect unverified information posted on social media during a news event can help to avoid the spread of rumours that turn out to be false. In this paper we compare a novel approach using Conditional Random Fields that learns from the sequential dynamics of social media posts with the current state-of-the-art rumour detection system, as well as other baselines. In contras...
متن کامل