Automatic elicitation of semantic information from natural language texts is an important
research problem with many practical application areas. Especially after the recent …

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 …

False or unverified information spreads just like accurate information on the web, thus
possibly going viral and influencing the public opinion and its decisions. Fake news and …

The proliferation of fake news on social media has the probability to bring an unfavorable
impact on public opinion and social development. Many efforts have been paid to develop …

We contribute the largest publicly available dataset of naturally occurring factual claims for
the purpose of automatic claim verification. It is collected from 26 fact checking websites in …

We present a study on predicting the factuality of reporting and bias of news media. While
previous work has focused on studying the veracity of claims or documents, here we are …

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 …

Understanding attitudes expressed in texts, also known as stance detection, plays an
important role in systems for detecting false information online, be it misinformation …

In this study, we propose a new multi-task learning approach for rumor detection and stance
classification tasks. This neural network model has a shared layer and two task specific …

Fake news is the information or stories that are intentionally created to deceive or mislead
the readers. In recent times, Fake news detection has attracted the attention of researchers …