The following open source software packages are developed within my research group and are available for use.

Structural Balance (github.com/rpitrust/structuralbalance) :

1. This code implements  the trust and distrust prediction (edge sign prediction) in networks given a network with signed (trust/distrust) edges with different level of strength (extreme/low trust, extreme/low distrust, neutral relations.)
   

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3. Citations:
   

4. •Y. Qian and S. Adali, "Extended Structural Balance Theory for Modeling Trust in Social Networks",  PST2013 Conference on Privacy, Security and Trust, 2013
   

5. •Y. Qian and S. Adali, “Foundations of Trust and Distrust in Networks: Extended Structural Balance Theory”, accepted to appear in ACM Transactions on the Web, TWEB, 2014.
   

6. •See also: blog entry
   

Attentive Betweenness Centrality  (github.com/rpitrust/prominence/AttnCentrality) :

1. This code implements betweenness centrality that considers the number of shortest and almost shortest paths a node lies in, and the degree of the nodes along these shortest paths. The method approximates betweenness closely, but reduces unintuitive results. 
   

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3. Citations:
   

4. •S. Adali, X. Lu and M. Magdon-Ismail, "Attentive Betweenness Centrality (ABC): Considering Options and Bandwidth When Measuring Criticality". SocialCom/PASSAT 2012: 358-367.
   

5. •See also: blog entry
   

Attentive Closeness Centrality  (github.com/rpitrust/prominence/AttentiveCLS) :

1. This code implements a version of closeness centrality that considers the average length of paths from a given node to all the others, taking into account the attention a node can provide to another based on its degree. The method improves on closeness centrality based on various external ground truth values.  
   

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3. Citations:
   

4. •S. Adali, X. Lu and M. Magdon-Ismail, "Computing Centrality When Actors Have Limited Attention and Information Flow is Multi-Path". Under review, available upon request.
   

Local and Community Centrality  (github.com/rpitrust/prominence/CommDistHashmap) :

1. This code implements closeness centrality for a community meta-graph and within each community. Given a set of non-overlapping communities found by a clustering algorithm, distance between different communities is computed. Closeness centrality now can be computed for the whole graph, within each community, or the community itself.
   

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3. Citations:
   

4. •S. Adali, X. Lu and M. Magdon-Ismail, "Deconstructing centrality: thinking locally and ranking globally in networks", accepted to appear in ASONAM 2013.
   

5. •S. Adali, X. Lu and M. Magdon-Ismail, "Local, community and global centrality methods for analyzing networks”, Under review and available upon request.
   

6. •See also: blog entry.
   

iHypR: Iterative prominence computation  (github.com/rpitrust/prominence/iHypR) :

1. This code takes as input a graph of collaborations: actors collaborate on objects, objects belong to common groups/venues. For example: authors of research papers are actors, and papers belong in venues. It then iterates within these three groups to compute the prominence of individuals in the whole network as a function of their objects, which are linked to the the venues. The “venues” are computed automatically.
   

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3. Citations:
   

4. •S. Adali, Xiaohui Lu and Malik Magdon-Ismail, "iHypR: Prominence Ranking in Networks of Collaborations with Hyperedges", ACM Transactions on Knowledge Discovery from Data, 7(4), November 2013. (ACM DL)
   

5. •See also: blog entry.
   

Agent Based Simulation of Information Sharing and Trust  (github.com/rpitrust/agentsimulation) :

1. This code provides an end-to-end simulation package in which agents share information in a network based on trust or organizational rules. The pairwise trust beliefs are composed of competence and willingness components. Agents have many characteristics that impact these beliefs.
   

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3. Citations:
   

4. •Kevin Chan, Jin-Hee Cho and Sibel Adali, “A Trust-Based Framework for Information Sharing Behavior in Command and Control Environments”, in Proceedings of the 22nd Annual Conference on Behavior Representation in Modeling Simulation, 2013 (best paper award)
   

5. •Kevin Chan, Jin-Hee Cho and Sibel Adali, “Composite trust model for an information sharing scenario”, in Proceeedings of The 9th IEEE International Conference on Autonomic and Trusted Computing (ATC 2012).
   

6. •Code Documentation
   

7. •See also: blog entry.