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

SPARK

書目名稱Collaboration Technologies and Social Computing影響因子(影響力)




書目名稱Collaboration Technologies and Social Computing影響因子(影響力)學科排名




書目名稱Collaboration Technologies and Social Computing網(wǎng)絡公開度




書目名稱Collaboration Technologies and Social Computing網(wǎng)絡公開度學科排名




書目名稱Collaboration Technologies and Social Computing被引頻次




書目名稱Collaboration Technologies and Social Computing被引頻次學科排名




書目名稱Collaboration Technologies and Social Computing年度引用




書目名稱Collaboration Technologies and Social Computing年度引用學科排名




書目名稱Collaboration Technologies and Social Computing讀者反饋




書目名稱Collaboration Technologies and Social Computing讀者反饋學科排名

LAVE

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

avulsion

分發(fā)

四溢

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.

確定的事

確定的事

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

演講

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

EVICT

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