A Novel Two-Stage Framework for User Identification Across Social Networks

2019 ◽  
Author(s):  
Shuang Gu ◽  
Feng Yuan ◽  
Hanqian Wu ◽  
Han Shao ◽  
Lu Cheng
Keyword(s):  
Social Networks ◽  
Two Stage ◽  
User Identification

scholarly journals Two-Stage User Identification Based on User Topology Dynamic Community Clustering

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jiajing Zhang ◽  
Zhenhua Yuan ◽  
Neng Xu ◽  
Jinlan Chen ◽  
Juxiang Wang
Keyword(s):  
Social Networks ◽  
Two Stage ◽  
User Identification ◽  
Practical Applications ◽  
Identity Recognition ◽  
Network Communities ◽  
Average Accuracy ◽  
Label Node ◽  
Community Clustering ◽  
Dynamic Community

In order to solve the problem of node information loss during user matching in the existing user identification method of fixed community across the social network based on user topological relationship, Two-Stage User Identification Based on User Topology Dynamic Community Clustering (UIUTDC) algorithm is proposed. Firstly, we perform community clustering on different social networks, calculate the similarity between different network communities, and screen out community pairs with greater similarity. Secondly, two-way marriage matching is carried out for users between pairs of communities with high similarity. Then, the dynamic community clustering was performed by resetting the different community clustering numbers. Finally, the iteration is repeated until no new matching user pairs are generated, or the set number of iterations is reached. Experiments conducted on real-world social networks Twitter-Foursquare datasets demonstrate that compared with the global user matching method and hidden label node method, the average accuracy of the proposed UIUTDC algorithm is improved by 33% and 26.8%, respectively. In the case of only user topology information, the proposed UIUTDC algorithm effectively improves the accuracy of identity recognition in practical applications.

User identification across online social networks in practice: Pitfalls and solutions

2016 ◽  
Vol 44 (3) ◽  
pp. 377-391 ◽  
Author(s):  
Azadeh Esfandyari ◽  
Matteo Zignani ◽  
Sabrina Gaito ◽  
Gian Paolo Rossi
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Full Range ◽  
Application Programming Interface ◽  
User Identification ◽  
Application Programming ◽  
Test Sets ◽  
Set Up ◽  
Different Levels ◽  
Programming Interface

To take advantage of the full range of services that online social networks (OSNs) offer, people commonly open several accounts on diverse OSNs where they leave lots of different types of profile information. The integration of these pieces of information from various sources can be achieved by identifying individuals across social networks. In this article, we address the problem of user identification by treating it as a classification task. Relying on common public attributes available through the official application programming interface (API) of social networks, we propose different methods for building negative instances that go beyond usual random selection so as to investigate the effectiveness of each method in training the classifier. Two test sets with different levels of discrimination are set up to evaluate the robustness of our different classifiers. The effectiveness of the approach is measured in real conditions by matching profiles gathered from Google+, Facebook and Twitter.

Modeling rumor propagation and refutation with time effect in online social networks

2018 ◽  
Vol 29 (08) ◽  
pp. 1850068 ◽  
Author(s):  
Yaming Zhang ◽  
Yanyuan Su ◽  
Weigang Li ◽  
Haiou Liu
Keyword(s):  
Social Networks ◽  
Heterogeneous Networks ◽  
Online Social Networks ◽  
Negative Impact ◽  
Time Effect ◽  
Field Equations ◽  
Two Stage ◽  
Dynamical Mechanism ◽  
Rumor Propagation ◽  
Mean Field Equations

Rumor propagation and refutation form an important issue for spreading dynamics in online social networks (OSNs). In this paper, we introduce a novel two-stage rumor propagation and refutation model with time effect for OSNs. The dynamical mechanism of rumor propagation and refutation with time effect is investigated deeply. Then a two-stage model and the corresponding mean-field equations in both homogeneous and heterogeneous networks are obtained. Monte Carlo simulations are conducted to characterize the dynamics of rumor propagation and refutation in both Watts–Strogatz network and Barabási–Albert network. The results show that heterogeneous networks yield the most effective rumor and anti-rumor spreading. Besides, the sooner authority releases anti-rumor and the more attractive anti-rumor is, the less rumor influence is. What’s more, these findings suggest that individuals’ ability to control themselves and identify rumor accurately should be improved to reduce negative impact of rumor effectively. The results are helpful to understand better the mechanism of rumor propagation and refutation in OSNs.

Exploiting similarities of user friendship networks across social networks for user identification

2020 ◽  
Vol 506 ◽  
pp. 78-98 ◽  
Author(s):  
Yongjun Li ◽  
Zhaoting Su ◽  
Jiaqi Yang ◽  
Congjie Gao
Keyword(s):  
Social Networks ◽  
Friendship Networks ◽  
User Identification

scholarly journals How social networks facilitate collective responses to organizational paradoxes

2019 ◽  
Vol 73 (3) ◽  
pp. 401-428 ◽  
Author(s):  
Joshua Keller ◽  
Sze-Sze Wong ◽  
Shyhnan Liou
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mixed Method ◽  
Organizational Response ◽  
Mixed Method Study ◽  
Two Stage ◽  
Collective Response ◽  
Organizational Paradoxes ◽  
Research Institute

When organizations face paradoxical tensions, such as when they must simultaneously meet scientific and commercial objectives, individuals within the organization also experience tensions. How individuals’ responses to these tensions inform the collective organizational response remains a theoretical and empirical challenge. We address this challenge by introducing a social network perspective. In a two-stage mixed-method study of a research institute in Taiwan, we examined how individuals’ social networks facilitated the organization’s response to a science-commerce paradox. Our results demonstrated that the level of heterogeneity in each individual’s social network influenced how each individual contributed to the organization’s collective response. Specifically, individuals with heterogeneous instrumental networks were more likely to contribute to the organization-wide consensus response, whereas individuals with homogeneous expressive networks were more likely to contribute to a polarized subgroup response. Our findings suggest that individuals’ roles in shaping a collective organizational response to paradoxes depends on who they seek advice from and who they befriend.

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