TY - GEN
T1 - Characterizing collective knowledge sharing behaviors in social network
AU - Kang, Jian
AU - Yu, Zhiwen
AU - Liang, Yunji
AU - Xie, Jiayu
AU - Guo, Bin
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/8
Y1 - 2019/8
N2 - Knowledge sharing behaviors play important roles in the spread of new concepts, ideas, and emerging technologies. However, how knowledge is disseminated in large-scale populations and what kinds of factors are associated with the collective knowledge sharing behaviors are still open issues. In this paper, we characterize the knowledge sharing behaviors via collective interaction in large-scale Question and Answer (Q&A) social networks. Specifically, we study the knowledge sharing behaviors in Zhihu and Quora, and utilize kendall coefficient and logistic regression model to quantify the influence of factors linked with sharing behaviors including friend's influence and the users' interest. We find that the knowledge sharing behavior is contagious among friends. The contagion is asymmetric. The individuals who are less active or less popular are more likely to be affected. Meanwhile the trusted users in the community are more likely to infect others.
AB - Knowledge sharing behaviors play important roles in the spread of new concepts, ideas, and emerging technologies. However, how knowledge is disseminated in large-scale populations and what kinds of factors are associated with the collective knowledge sharing behaviors are still open issues. In this paper, we characterize the knowledge sharing behaviors via collective interaction in large-scale Question and Answer (Q&A) social networks. Specifically, we study the knowledge sharing behaviors in Zhihu and Quora, and utilize kendall coefficient and logistic regression model to quantify the influence of factors linked with sharing behaviors including friend's influence and the users' interest. We find that the knowledge sharing behavior is contagious among friends. The contagion is asymmetric. The individuals who are less active or less popular are more likely to be affected. Meanwhile the trusted users in the community are more likely to infect others.
KW - Behavioral contagion
KW - Knowledge sharing behavior
KW - Q&A social networks
UR - http://www.scopus.com/inward/record.url?scp=85083571051&partnerID=8YFLogxK
U2 - 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00178
DO - 10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00178
M3 - 会议稿件
AN - SCOPUS:85083571051
T3 - Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
SP - 869
EP - 876
BT - Proceedings - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Internet of People and Smart City Innovation, SmartWorld/UIC/ATC/SCALCOM/IOP/SCI 2019
Y2 - 19 August 2019 through 23 August 2019
ER -