Research Thrust
Social Network Analysis/Link Analysis/Group Detection
Social Network Analysis/Link Analysis/Group Detection seeks to discover interesting relationships and patterns among people or other entities, for example:
- Who communicates with whom? And who appears to avoid communicating with whom?
- Are there cliques of people who mostly communicate among themselves and rarely with others, or is communication more evenly distributed?
- Are there "stars" who are linked with a very large number or people, and/or isolated people who are only linked with one or two others?
- Might there be aliases? That is, if we see two people with essentially the same link patterns, but who are never linked with each other, might they in fact be the same person?
- How do patterns of association among entities evolve over time?
- Can we identify groups of entities, based on link data and/or demographic properties? If we know that a communication took place, but we don't know the identity of one of the participants, can we infer who that entity was?
Auton Lab researchers have developed--and continue to develop--many algorithms and associated software packages for investigating these kinds of questions. As usual at the Auton Lab, these technologies place great emphasis on efficient analysis of large datasets.
Software
AFDL
- Activity From Demographics and Links
Bayes Net
Learner - As the name sounds
SBNS -
Screen-based Bayes Net Structure search
GDA/k-groups
- Group Detection Algorithm
MNOP - Many
Names, One Person alias detection
XGDA - A
fast group detection algorithm
Datasets
Alias
detection Dataset - input forMany
Names One Person software software
Link Datasets -
for Link Detection, GDA, k-groups, cGraph, and Sparse Bayes Net search
More to come...
Papers
Rough List of Paper on this topic
| Name | Summary | Document Type | Tags | Actions |
|---|---|---|---|---|
| A Comparison of Statistical and Machine Learning Algorithms on the Task of Link Completion | Link data, consisting of a collection of subsets of entities, can be an important source of information for a variety of fields including the social sciences, biology, criminology, and business intelligence. However, these links may be incomplete, containing one or more unknown members. We consi... | Paper | GDA, Testing, Link Analysis, Efficient Statistical Algorithms, Applications | show |
| Finding Underlying Connections: A Fast Graph-Based Method for Link Analysis and Collaboration Queries | Many techniques in the social sciences and graph theory deal with the problem of examining and analyzing patterns found in the underlying structure and associations of a group of entities. However, much of this work assumes that this underlying structure is known or can easily be inferred from d... | Paper | GDA, Link Analysis | show |
| Stochastic Link and Group Detection | Link detection and analysis has long been important in the social sciences and in the government intelligence community. A significant effort is focused on the structural and functional analysis of "known" networks. Similarly, the detection of individual links is important but is usually done wi... | Paper | GDA, Link Analysis, Applications | show |
| Tractable Group Detection on Large Link Data Sets | Discovering underlying structure from co-occurrence data is an important task in a variety of fields, including: insurance, intelligence, criminal investigation, epidemiology, human resources, and marketing. Previously Kubica et. al. presented the group detection algorithm (GDA) - an algorithm f... | Paper | GDA, Link Analysis, Clustering, Efficient Statistical Algorithms, Optimization | show |
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