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Titlebook: Disinformation in Open Online Media; 5th Multidisciplinar Davide Ceolin,Tommaso Caselli,Marina Tulin Conference proceedings 2023 The Editor

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楼主: enamel
发表于 2025-3-23 10:51:58 | 显示全部楼层
Conference proceedings 2023elected from 19 submissions. The papers focus on misinformation, disinformation, hate speech, disinformation campaigns, social network analysis, large language models, generative AI, and multi-modal embeddings..
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The Commonwealth Of The Bahamas, poorly detectable campaigns at the content level. Thus, we evaluate classical classifiers and a new method based on siamese neural networks. Our results show that campaigns can be detected despite the limited reliability of the classifiers as long as they are based on a large amount of simultaneously spread artificial content.
发表于 2025-3-23 22:17:11 | 显示全部楼层
The Commonwealth Of The Bahamas,ubsequent flow of misinformation about the election, we find that in a number of instances content moderation reduced the flow of social media misinformation. We estimate that Twitter’s actions, on the universe of tweets we study in our paper, reduced the flow of misinformation on Twitter by approximately 15%.
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The Commonwealth Of The Bahamas,udy to examine the contribution of textualized image information to campaign recognition. The results indicate that, using image captions separate from or alongside tweet texts, connections between campaigns can be identified, and new campaigns detected.
发表于 2025-3-24 11:35:50 | 显示全部楼层
,Towards Multimodal Campaign Detection: Including Image Information in Stream Clustering to Detect Sudy to examine the contribution of textualized image information to campaign recognition. The results indicate that, using image captions separate from or alongside tweet texts, connections between campaigns can be identified, and new campaigns detected.
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Conference proceedings 202323, which was held in Amsterdam, The Netherlands, during November 21–22, 2023..The 13 full papers presented in this book were carefully reviewed and selected from 19 submissions. The papers focus on misinformation, disinformation, hate speech, disinformation campaigns, social network analysis, large
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Generative AI for Explainable Automated Fact Checking on the FactEx: A New Benchmark Dataset,at classify evidence into binary or multi-class verdicts. However, there are few studies on predicting textual verdicts to explain claims’ credibility. This field focuses on generating a textual verdict to explain a given claim based on a given news article. This paper presents our three-fold contri
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