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Towards Trustworthy Deception Detection: Benchmarking Model Robustness across Domains, Modalities, and Languages.

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Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods., , , , , , , , и . Comput. Math. Organ. Theory, 29 (1): 220-241 (марта 2023)Towards Trustworthy Deception Detection: Benchmarking Model Robustness across Domains, Modalities, and Languages., , , , и . CoRR, (2021)CrystalBall: A Visual Analytic System for Future Event Discovery and Analysis from Social Media Data., , , , и . VAST, стр. 25-35. IEEE Computer Society, (2017)Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking., , , , и . EMNLP, стр. 2931-2937. Association for Computational Linguistics, (2017)Inferring Latent User Properties from Texts Published in Social Media., , , и . AAAI, стр. 4296-4297. AAAI Press, (2015)Explaining Multimodal Deceptive News Prediction Models., , , , и . ICWSM, стр. 659-662. AAAI Press, (2019)Propagation from Deceptive News Sources: Who Shares, How Much, How Evenly, and How Quickly?, , и . CoRR, (2018)Exploring Sentiment in Social Media: Bootstrapping Subjectivity Clues from Multilingual Twitter Streams., , и . ACL (2), стр. 505-510. The Association for Computer Linguistics, (2013)Inferring Perceived Demographics from User Emotional Tone and User-Environment Emotional Contrast., и . ACL (1), The Association for Computer Linguistics, (2016)Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter., , , и . ACL (2), стр. 647-653. Association for Computational Linguistics, (2017)