Knowledge graph informed fake news classification via heterogeneous representation ensembles-Reference-Cited by-同舟云学术

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Knowledge graph informed fake news classification via heterogeneous representation ensembles

Published:2022-07 Issue: Volume:496 Page:208-226
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Koloski Boshko,Stepišnik Perdih Timen,Robnik-Šikonja Marko,Pollak Senja,Škrlj Blaž

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

1. Social media and fake news in the 2016 election;Allcott;J. Econ. Perspect.,2017

2. C.M. Pulido, L. Ruiz-Eugenio, G. Redondo-Sama, B. Villarejo-Carballido, A new application of social impact in social media for overcoming fake news in health, Int. J. Environ. Res. Public Health 17 (7). doi:10.3390/ijerph17072430. https://www.mdpi.com/1660-4601/17/7/2430.

3. A.B. Kadam, S.R. Atre, Negative impact of social media panic during the COVID-19 outbreak in India, J. Travel Med. 27 (3), taaa057.

4. Fake news detection on social media: A data mining perspective;Shu;ACM SIGKDD explorations newsletter,2017

5. K. Shu, S. Wang, D. Lee, H. Liu, Mining disinformation and fake news: Concepts, methods, and recent advancements, in: Disinformation, Misinformation, and Fake News in Social Media, Springer, 2020, pp. 1–19.

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