Fighting post-truth using natural language processing: A review and open challenges

E Saquete, D Tomás, P Moreda… - Expert systems with …, 2020 - Elsevier
Post-truth is a term that describes a distorting phenomenon that aims to manipulate public
opinion and behavior. One of its key engines is the spread of Fake News. Nowadays most …

From “networked publics” to “refracted publics”: A companion framework for researching “below the radar” studies

C Abidin - Social Media+ Society, 2021 - journals.sagepub.com
Reflecting on a decade (2009–2020) of research on influencer cultures in Singapore, the
Asia Pacific, and beyond, this article considers the potential of “below the radar” studies for …

SemEval-2023 task 5: Clickbait spoiling

M Fröbe, B Stein, T Gollub, M Hagen… - Proceedings of the 17th …, 2023 - aclanthology.org
In this overview paper, we report on the second PAN~ Clickbait Challenge hosted as Task~
5 at SemEval~ 2023. The challenge's focus is to better support social media users by …

Bert, xlnet or roberta: the best transfer learning model to detect clickbaits

P Rajapaksha, R Farahbakhsh, N Crespi - IEEE Access, 2021 - ieeexplore.ieee.org
Clickbait can be a spam or an advert which more often provides a link to commercial website
and it can also be a headline to news media website which makes money from page views …

Clickbait spoiling via question answering and passage retrieval

M Hagen, M Fröbe, A Jurk, M Potthast - arxiv preprint arxiv:2203.10282, 2022 - arxiv.org
We introduce and study the task of clickbait spoiling: generating a short text that satisfies the
curiosity induced by a clickbait post. Clickbait links to a web page and advertises its contents …

Did clickbait crack the code on virality?

P Mukherjee, S Dutta, A De Bruyn - Journal of the Academy of Marketing …, 2022 - Springer
Although clickbait is a ubiquitous tactic in digital media, we challenge the popular belief that
clickbait systematically leads to enhanced sharing of online content on social media. Using …

Clickbait detection in tweets using self-attentive network

Y Zhou - arxiv preprint arxiv:1710.05364, 2017 - arxiv.org
Clickbait detection in tweets remains an elusive challenge. In this paper, we describe the
solution for the Zingel Clickbait Detector at the Clickbait Challenge 2017, which is capable of …

[PDF][PDF] Bad news: Clickbait and deceptive ads on news and misinformation websites

E Zeng, T Kohno, F Roesner - … on Technology and …, 2020 - badads.cs.washington.edu
A key aspect of online ads that has not been systematically studied by the computer security
community is their visible, user-facing content. Motivated by anecdotal evidence of …

Reinforced co-training

J Wu, L Li, WY Wang - arxiv preprint arxiv:1804.06035, 2018 - arxiv.org
Co-training is a popular semi-supervised learning framework to utilize a large amount of
unlabeled data in addition to a small labeled set. Co-training methods exploit predicted …

[PDF][PDF] Clickbait detection: A literature review of the methods used

NA Zuhroh, NA Rakhmawati - Register: Jurnal Ilmiah Teknologi …, 2020 - journal.unipdu.ac.id
Online news portals are currently one of the fastest sources of information used by people.
Its impact is due to the credibility of the news produced by actors from the media industry …