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Titlebook: Collaboration Technologies and Social Computing; 29th International C Hideyuki Takada,D. Moritz Marutschke,Davinia Herna Conference proceed

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發(fā)表于 2025-3-21 19:27:57 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Collaboration Technologies and Social Computing
副標(biāo)題29th International C
編輯Hideyuki Takada,D. Moritz Marutschke,Davinia Herna
視頻videohttp://file.papertrans.cn/230/229359/229359.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Collaboration Technologies and Social Computing; 29th International C Hideyuki Takada,D. Moritz Marutschke,Davinia Herna Conference proceed
描述.This book constitutes the refereed proceedings of the 29th International Conference on Collaboration Technologies and Social Computing, CollabTech 2023, held in Osaka, Japan, during August 29–September 1, 2023, in hybrid mode..The 8 full papers presented in this book together with 12 short papers were carefully reviewed and selected from 31 submissions. ..The papers focus on innovative technical, human and organizational approaches to expand collaboration support including computer science, management science, design science, cognitive and social science..
出版日期Conference proceedings 2023
關(guān)鍵詞Collaborative and social computing systems and tools; Applied computing; Education; Collaborative learn
版次1
doihttps://doi.org/10.1007/978-3-031-42141-9
isbn_softcover978-3-031-42140-2
isbn_ebook978-3-031-42141-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Lab-Forming Fields and Field-Forming Labsg their peers’ rankings and interacting with them anonymously. Secondly, we compare positive, neutral, and negative sentiment variations in students’ written justifications for rankings before and after collaborating. Results show that students are highly likely to change their responses in the coll
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Lab-Forming Fields and Field-Forming Labser relationship shows that pathways of dynamic information diffusion are largely determined by the static follower topology. These findings provide strategic information for managing CS-related discussions.
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Kenju Akai,Kengo Hayashida,Nariaki Nishinoied this model to the joint Simon task. The results suggested that competition elicited better performance than cooperation. In conclusion, the classification model successfully distinguished subtle movements in the VR environment. This model could be used to analyze the state of pairs during collab
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https://doi.org/10.1007/978-3-540-72358-5he network. As such, we extracted 12,985 tweets from Twitter to understand the different topics being discussed about the BRI in Indonesia. Latent Dirichlet Allocation (LDA) topic model algorithm classified the tweets into topic groups and helped us understand each topic’s underlying theme. In addit
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