An Interpretability Assisted Empirical Study of Affective Traits in Visual Content of Disinformation
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-2602-2_18
Reference22 articles.
1. Martel C, Pennycook G, Rand DG (2020) Reliance on emotion promotes belief in fake news. Cogn Res Principles Implications 5(1):1–20
2. Rajamanickam S, Mishra P, Yannakoudakis H, Shutova E (2020) Joint modelling of emotion and abusive language detection. arXiv preprint arXiv:2005.14028
3. Nagaraj P, Das B (2022) Graph convolution-based joint learning of rumor with content, user credibility, propagation context, and cognitive as well as emotion signals. In: Sentimental analysis and deep learning. Springer, Berlin, pp 113–128
4. Ajao O, Bhowmik D, Zargari S (2019) Sentiment aware fake news detection on online social networks. In: ICASSP 2019—2019 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE, pp 2507–2511
5. Rajmohan M, Kamath R, Reddy AP, Das B (2022) Emotion enhanced domain adaptation for propaganda detection in Indian social media. In: Innovations in computational intelligence and computer vision. Springer, Berlin, pp 273–282
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