Social Networks

Social Networks


Description
Personnel
Papers and Talks

Description


I have recently started working on network science aspects of social networks. With Sushant Khopkar (PhD student) and Prof. Alex Nikolaev (UB) we have proposed a new social network model that spans small world through scale-free networks.

I also work on fast, approximate and incremental centrality metric calculations.

I am also working on Influence Maximization and Viral Marketing.

Personnel


  • Rakesh Nagi
  • Alexander Nikolaev, University at Buffalo.

Graduate Students:

  • Sushant Khopkar; PhD 1/17 (UB). Dissertation title: “Computational Advances in Data Analytics with Social Networks.” (co-advised with Alexander Nikolaev.) Currently: Applied Research Scientist, Llama Soft, Ann Arbor, MI.
  • Mohammad Samadi (PhD student of Prof. Nikolaev). Currently at American Airlines.
  • Arash Ghayoori” (ongoing PhD at UIUC)

Papers and Talks


Papers:

Journal Papers accepted:

  • Samadi, M., Nagi, R., Semenov, A. and Nikolaev, A. “Seed Activation Scheduling for Influence Maximization in Social Networks,” OMEGA, The International Journal of Management Science, June 2018, Vol. 77, pp. 96-114.
  • Farasat, A., Gross, G., Nagi, R. and Nikolaev, A. “Social Network Analysis with Data Fusion,” IEEE Transactions on Computational Social Systems, June 2016, Vol. 3(2), pp. 88-99.
  • Samadi, M., Nikolaev, A. and Nagi, R. “The Temporal Aspects of Evidence-Based Influence Maximization in Social Networks,” Optimization Methods and Software, 2017, 32(2), pp. 290-311 (published online, Aug 2016).
  • Khopkar, S., Nagi, R. and Tauer, G. “A Penalty Box Approach for Approximation Betweenness and Closeness Centrality Algorithms,” Social Network Analysis and Mining (SNAM), December 2016, 6(1), 1-13.
  • Samadi, M., Nikolaev, A. and Nagi, R. “A Subjective Evidence Model for Influence Maximization in Social Networks,” OMEGA, The International Journal of Management Science, March 2016, Vol. 59, Part B, pp. 263-278.
  • Khopkar, S., Nagi, R., Nikolaev, A. and Bhembre, V. “Efficient Algorithms for Incremental All Pairs Shortest Paths, Closeness and Betweeness in Social Network Analysis,” Social Network Analysis and Mining (SNAM), December 2014, Vol. 4(1), Article 220.

Journal Papers submitted:

  • Ghayoori, A. and Nagi, R. “Seed Investment Bounds for Viral Marketing Strategies in Social Networks under Generalized Diffusion,” submitted to Social Network Analysis and Mining, March 2018.

Conference papers:

  • Date, K., Feng, K., Nagi, R., Xiong, J., Kim, N.S., and Hwu, W-M. Collaborative (CPU + GPU) algorithms for triangle counting and truss decomposition on the Minsky architecture. High Performance Extreme Computing Conference (HPEC), 2017 IEEE, Waltham, MA, 12-14 September 2017. [DARPA Graph Challenge Honorable Mention.]
  • Chronopoulou, A. and Nagi, R., “Online Community Detection for Fused Social Network Graphs,” 19th International Conference on Information Fusion, Heidelberg, Germany, 5-8 July 2016.
  • Gross, G.A., Little, E., Park, B., Llinas, J. and Nagi, R., “Application of Multi-level Fusion for Pattern of Life Analysis,” 18th International Conference on Information Fusion, Washington, DC, 6-9 July 2015.
  • Farasat, A., Gross, G.A., Nagi, R. and Nikolaev, A., “Social Network Extraction and High Value Individual (HVI) Identification within Fused Intelligence Data,” 2015 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction (SBP), Washington DC, 31 March-3 April 2015.
  • Ogaard, K., Roy, H., Kase, S., Nagi, R., Sambhoos, K. and Sudit, M. “Searching social networks for subgraph pattern occurrences,” 2013 SPIE Defense, Security, and Sensing (SPIE, DSS 2013), Baltimore, MD, April-May 2013.
  • Khopkar, S., Nagi, R. and Nikolaev, A. “An Efficient Map-Reduce Algorithm for the Incremental Computation of All-Pairs Shortest Paths in Social Networks,” 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2012, Istanbul, Turkey, 26-29 August 2012.

Talks:

  • To be completed.