Mining triadic closure patterns in social networks
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Summary
The study uncovers how user demographics and network topology influence the process of triadic closure and presents a probabilistic graphical model to predict whether three persons will form a closed triad in dynamic networks.
- Type
- article
- Published
- 2014-04-07
- Cited by
- 67
- References
- 20
- Access
- Open access
- OpenAlex
- https://openalex.org/W82211948
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:1661841
Keywords
Closure (psychology), Triad (sociology), Microblogging, Computer science, Demographics
References
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- The WEKA data mining software: an update
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- Who will follow you back?: reciprocal relationship prediction
- The Directed Closure Process in Hybrid Social-Information Networks, with an Analysis of Link Formation on Twitter
- Group formation in large social networks: membership, growth, and evolution
- Social Networks that matter: Twitter under the Microscope
- Markov fields on finite graphs and lattices
Cited by
- Understanding the emotions behind social images: Inferring with user demographics
- Predicting Triadic Closure in Networks Using Communicability Distance Functions
- Triadic Closure Pattern Analysis and Prediction in Social Networks
- Uncovering the Formation of Triadic Closure in Social Networks
- Using weak ties to understand resource usage behaviors in an online community of educators
- Mining a Weighted Heterogeneous Network Extracted from Healthcare-Specific Social Media for Identifying Interactions between Drugs
- Framework for mining regular patterns in dynamic networks
- Probabilistic Relation between Triadic Closure and the Balance of Social Networks in Presence of Influence
- Gender homophily in online dyadic and triadic relationships
- Using weak ties to understand the resource usage and sharing patterns of a professional learning community
- A Neural Network Approach to Jointly Modeling Social Networks and Mobile Trajectories
- Impact of offline events on online link creation: a case study on events advertised on Facebook
- A Probabilistic Lifestyle-Based Trajectory Model for Social Strength Inference from Human Trajectory Data
- Computational Methodologies for Understanding the Dynamics of an Online Community of Educators
- Mining quad closure patterns in Instagram
- Emotion Analysis in Code-Switching Text With Joint Factor Graph Model
- Discovering Drug-Drug Interactions and Associated Adverse Drug Reactions with Triad Prediction in Heterogeneous Healthcare Networks
- Motifs in Temporal Networks
- Inferring Emotional Tags From Social Images With User Demographics
- Information diffusion on communication networks based on Big Data analysis
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