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Titlebook: Detecting Trust and Deception in Group Interaction; V. S. Subrahmanian,Judee K. Burgoon,Norah E. Dunba Book 2021 The Editor(s) (if applica

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發(fā)表于 2025-3-21 18:21:11 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Detecting Trust and Deception in Group Interaction
編輯V. S. Subrahmanian,Judee K. Burgoon,Norah E. Dunba
視頻videohttp://file.papertrans.cn/270/269181/269181.mp4
概述One of the first books to study the link between human behavior in group settings with facial expressions and speech analysis.One of the first books to illustrate how advanced machine learning and dee
叢書名稱Terrorism, Security, and Computation
圖書封面Titlebook: Detecting Trust and Deception in Group Interaction;  V. S. Subrahmanian,Judee K. Burgoon,Norah E. Dunba Book 2021 The Editor(s) (if applica
描述.This book analyzes the multimodal verbal and nonverbal behavior of humans in both an artificial game, based on the well-known Mafia and Resistance games, as well as selected other settings. This book develops statistical results linking different types of facial expressions (e.g. smile, pursed lips, raised eyebrows),?vocal features (e.g., pitch, loudness) and?linguistic features (e.g., dominant language, turn length)?with both unary behaviors (e.g. is person X lying?) to binary behaviors (Is person X dominant compared to person Y? Does X trust Y? Does X like Y?). In addition, this book describes machine learning and computer vision-based algorithms that can be used to predict deception, as well as the visual focus of attention of people during discussions that can be linked to many binary behaviors. It is written by a multidisciplinary team of both social scientists and computer scientists..Meetings are at the very heart of human activity. Whether you are involved in a business meeting or in a diplomatic negotiation, such an event has multiple actors, some cooperative and some adversarial. Some actors may be deceptive, others may have complex relationships with others in the group
出版日期Book 2021
關(guān)鍵詞Human behavior; deception; dominance; deference; like/dislike; trust; computer vision; machine learning; Fac
版次1
doihttps://doi.org/10.1007/978-3-030-54383-9
isbn_softcover978-3-030-54385-3
isbn_ebook978-3-030-54383-9Series ISSN 2197-8778 Series E-ISSN 2197-8786
issn_series 2197-8778
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Detecting Trust and Deception in Group Interaction
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Dominance in Groups: How Dyadic Power Theory Can Apply to Group Discussionseivers) were viewed as less dominant than Villagers (truth-tellers). Males were rated as more dominant, especially when in the Spy role. The implications for this study on the study of groups and power relations among group members are discussed.
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Behavioral Indicators of Dominance in an Adversarial Group Negotiation Gameuency, greater variability in loudness, higher voice quality, longer turn-at-talk duration, larger dominance ratio and a greater number of words. However, some features turn out not to be significantly correlated with dominance, such as mean level of loudness, polarity of emotions, hedging ratio and
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Incremental Information Disclosure in Qualitative Financial Reporting: Differences Between Fraudulenity of these measures using several classification schemes, achieving fraud-detection accuracy levels between 53% and 71%. The paper concludes with a discussion of the findings and avenues for future research.
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