[HTML][HTML] Emotion detection for misinformation: A review

Z Liu, T Zhang, K Yang, P Thompson, Z Yu… - Information …, 2024 - Elsevier
With the advent of social media, an increasing number of netizens are sharing and reading
posts and news online. However, the huge volumes of misinformation (eg, fake news and …

Using artificial intelligence technology to fight COVID-19: a review

Y Peng, E Liu, S Peng, Q Chen, D Li, D Lian - Artificial intelligence review, 2022 - Springer
In late December 2019, a new type of coronavirus was discovered, which was later named
severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Since its discovery, the …

[PDF][PDF] Stance detection in COVID-19 tweets

K Glandt, S Khanal, Y Li, D Caragea… - Proceedings of the 59th …, 2021 - par.nsf.gov
The prevalence of the COVID-19 pandemic in day-to-day life has yielded large amounts of
stance detection data on social media sites, as users turn to social media to share their …

Monkeypox2022tweets: a large-scale twitter dataset on the 2022 monkeypox outbreak, findings from analysis of tweets, and open research questions

N Thakur - Infectious Disease Reports, 2022 - mdpi.com
The mining of Tweets to develop datasets on recent issues, global challenges, pandemics,
virus outbreaks, emerging technologies, and trending matters has been of significant interest …

Using Twitter data to understand public perceptions of approved versus off-label use for COVID-19-related medications

Y Hua, H Jiang, S Lin, J Yang, JM Plasek… - Journal of the …, 2022 - academic.oup.com
Objective Understanding public discourse on emergency use of unproven therapeutics is
essential to monitor safe use and combat misinformation. We developed a natural language …

Misinformation detection using multitask learning with mutual learning for novelty detection and emotion recognition

R Kumari, N Ashok, T Ghosal, A Ekbal - Information Processing & …, 2021 - Elsevier
Fake news or misinformation is the information or stories intentionally created to deceive or
mislead the readers. Nowadays, social media platforms have become the ripe grounds for …

What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion

R Kumari, N Ashok, T Ghosal, A Ekbal - Information Processing & …, 2022 - Elsevier
One of the most time-critical challenges for the Natural Language Processing (NLP)
community is to combat the spread of fake news and misinformation. Existing approaches for …

[HTML][HTML] Textual emotion detection in health: Advances and applications

AH Saffar, TK Mann, B Ofoghi - Journal of Biomedical Informatics, 2023 - Elsevier
Abstract Textual Emotion Detection (TED) is a rapidly growing area in Natural Language
Processing (NLP) that aims to detect emotions expressed through text. In this paper, we …

An augmented multilingual Twitter dataset for studying the COVID-19 infodemic

CE Lopez, C Gallemore - Social Network Analysis and Mining, 2021 - Springer
This work presents an openly available dataset to facilitate researchers' exploration and
hypothesis testing about the social discourse of the COVID-19 pandemic. The dataset …

Unmasking people's opinions behind mask-wearing during COVID-19 pandemic—a Twitter stance analysis

LA Cotfas, C Delcea, R Gherai, I Roxin - Symmetry, 2021 - mdpi.com
Wearing a mask by the general public has been a controversial issue from the beginning of
the COVID-19 pandemic as the public authorities have had mixed messages, either advising …