Stance detection on social media: State of the art and trends

A AlDayel, W Magdy - Information Processing & Management, 2021 - Elsevier
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 …

Detection and resolution of rumours in social media: A survey

A Zubiaga, A Aker, K Bontcheva, M Liakata… - Acm Computing Surveys …, 2018 - dl.acm.org
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, ie, items of …

A survey on automated fact-checking

Z Guo, M Schlichtkrull, A Vlachos - Transactions of the Association for …, 2022 - direct.mit.edu
Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …

exbake: Automatic fake news detection model based on bidirectional encoder representations from transformers (bert)

H Jwa, D Oh, K Park, JM Kang, H Lim - Applied Sciences, 2019 - mdpi.com
News currently spreads rapidly through the internet. Because fake news stories are
designed to attract readers, they tend to spread faster. For most readers, detecting fake news …

MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims

I Augenstein, C Lioma, D Wang, LC Lima… - arXiv preprint arXiv …, 2019 - arxiv.org
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 …

[PDF][PDF] Semeval-2019 task 7: Rumoureval 2019: Determining rumour veracity and support for rumours

G Gorrell, E Kochkina, M Liakata, A Aker… - Proceedings of the 13th …, 2019 - pure.itu.dk
RumourEval 2019: Determining Rumour Veracity and Support for Rumours Page 1
RumourEval 2019: Determining Rumour Veracity and Support for Rumours Genevieve …

SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours

L Derczynski, K Bontcheva, M Liakata, R Procter… - arXiv preprint arXiv …, 2017 - arxiv.org
Media is full of false claims. Even Oxford Dictionaries named" post-truth" as the word of
2016. This makes it more important than ever to build systems that can identify the veracity of …

A survey on stance detection for mis-and disinformation identification

M Hardalov, A Arora, P Nakov, I Augenstein - arXiv preprint arXiv …, 2021 - arxiv.org
Understanding attitudes expressed in texts, also known as stance detection, plays an
important role in systems for detecting false information online, be it misinformation …

All-in-one: Multi-task learning for rumour verification

E Kochkina, M Liakata, A Zubiaga - arXiv preprint arXiv:1806.03713, 2018 - arxiv.org
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 …

Detect rumor and stance jointly by neural multi-task learning

J Ma, W Gao, KF Wong - Companion proceedings of the the web …, 2018 - dl.acm.org
In recent years, an unhealthy phenomenon characterized as the massive spread of fake
news or unverified information (ie, rumors) has become increasingly a daunting issue in …