Stance detection on social media is an emerging opinion mining paradigm for various social
and political applications in which sentiment analysis may be sub-optimal. There has been a …

The proliferation of fake news on social media platforms poses significant challenges to
society and individuals, leading to negative impacts. As the tactics employed by purveyors of …

The explosion of social media allowed individuals to spread information without cost, with
little investigation and fewer filters than before. This amplified the old problem of fake news …

Automatic resolution of rumours is a challenging task that can be broken down into smaller
components that make up a pipeline, including rumour detection, rumour tracking and …

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 …

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 …

Stance detection determines whether the author of a text is in favor of, against or neutral to a
specific target and provides valuable insights into important events such as presidential …

Rumour stance classification, defined as classifying the stance of specific social media posts
into one of supporting, denying, querying or commenting on an earlier post, is becoming of …

This paper describes team Turing's submission to SemEval 2017 RumourEval: Determining
rumour veracity and support for rumours (SemEval 2017 Task 8, Subtask A). Subtask A …

Text data can pose a risk of harm. However, the risks are not fully understood, and how to
handle, present, and discuss harmful text in a safe way remains an unresolved issue in the …