Inferring social ties across heterogenous networks

By Jie Tang, Tiancheng Lou, Jon M. Kleinberg. 2012

304 citations recorded by the source corpus.

Subfields: Information Systems, Statistical and Nonlinear Physics

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In Information Systems

In Statistical and Nonlinear Physics

Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “Social links between users can stem from friendship, trust or shared interests, and thus can embed different social cues [Tang et al. 2012].”
A Survey of Signed Network Mining in Social Media (2015, methodology): “In [Tang et al. 2012], a factor-graph model is learned with features from the source network to infer signs of the target network.”
Negative Link Prediction in Social Media (2014, background): “Tang et al. proposed a framework to incorporate social theories such as status theory into a machine learning model and infer the signs of links in a target network by borrowing knowledge from a diﬀerent source network [23].”
Opportunistic IoT: Exploring the harmonious interaction between human and the internet of things (2013, background): “[24] developed a framework for classifying the type of social relationships by learning across different networks (e.”
A Survey on Network Embedding (2017, methodology): “For example, whether network embedding is a new way to detect rumors in social network [93], [94]? Can we use network embedding to infer social ties [95]? Each real world application has its own characteristics, and incorporating their unique domain knowledge into network embedding is a key.”
Inferring anchor links across multiple heterogeneous social networks (2013, background): “In addition, another line of research works study the link prediction problems on multiple networks or domains [5, 7, 20, 24, 21].”