Uncovering Research Topics of Academic Communities of Scientific Collaboration Network

In order to improve the quality of applications, such as recommendation or retrieval in knowledge-based service system, it is very helpful to uncover research topics of academic communities in scientific collaboration network (SCN). Previous research mainly focuses on network characteristics measurement and community evolution, but it remains largely understudied on how to uncover research topics of each community. This paper proposes a nonjoint approach, consisting of three simple steps: (1) to detect overlapping academic communities in SCN with the clique percolation method, (2) to discover underlying topics and research interests of each researcher with author-topic (AT) model, and (3) to label research topics of each community with top N most frequent collaborative topics between members belonging to the community. Extensive experimental results on NIPS (neural information processing systems) dataset show that our simple procedure is feasible and efficient.

[1]  Lijun Zhu,et al.  Author-Topic over Time (AToT): A Dynamic Users' Interest Model , 2013, MUSIC.

[2]  A. Arenas,et al.  Community analysis in social networks , 2004 .

[3]  Mason A. Porter,et al.  Communities in Networks , 2009, ArXiv.

[4]  Antoni Rubí-Barceló,et al.  Core/periphery scientific collaboration networks among very similar researchers , 2012 .

[5]  Lijun Zhu,et al.  A Dynamic Users’ Interest Discovery Model with Distributed Inference Algorithm , 2014, Int. J. Distributed Sens. Networks.

[6]  Daniel Dajun Zeng,et al.  User community discovery from multi-relational networks , 2013, Decis. Support Syst..

[7]  Liaquat Hossain,et al.  Analyzing Academic Communities’ Collaboration and Performance , 2011 .

[8]  Tamás Vicsek,et al.  Overlapping Modularity at the Critical Point of k-Clique Percolation , 2012, Journal of Statistical Physics.

[9]  S. Borgatti,et al.  Analyzing Clique Overlap , 2009 .

[10]  T. S. Evans,et al.  Clique graphs and overlapping communities , 2010, ArXiv.

[11]  David B. Dunson,et al.  Probabilistic topic models , 2011, KDD '11 Tutorials.

[12]  Thomas Hofmann,et al.  Probabilistic latent semantic indexing , 1999, SIGIR '99.

[13]  M. Krawczyk,et al.  Communities in networks - a continuous approach , 2007, 0709.0923.

[14]  M E Newman,et al.  Scientific collaboration networks. I. Network construction and fundamental results. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[15]  Michael Kirley,et al.  Community evolution in a scientific collaboration network , 2012, 2012 IEEE Congress on Evolutionary Computation.

[16]  Thomas L. Griffiths,et al.  Probabilistic author-topic models for information discovery , 2004, KDD.

[17]  Luciano García-Bañuelos,et al.  Finding and Analyzing Social Collaboration Networks in the Mexican Computer Science Community , 2009, 2009 Mexican International Conference on Computer Science.

[18]  Dan Lu,et al.  Scientific Collaboration Networks in China's System Engineering Subject , 2013 .

[19]  Luka Kronegger,et al.  Collaboration structures in Slovenian scientific communities , 2012, Scientometrics.

[20]  Marko A. Rodriguez,et al.  Collaboration in sensor network research: an in-depth longitudinal analysis of assortative mixing patterns , 2009, Scientometrics.

[21]  M. Newman,et al.  Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  Andrew McCallum,et al.  Topics over time: a non-Markov continuous-time model of topical trends , 2006, KDD '06.

[23]  Thomas Krichel,et al.  A social network analysis of research collaboration in theeconomics community , 2006 .

[24]  Bin Wu,et al.  Research and Evaluation on Modularity Modeling in Community Detecting of Complex Network Based on Information Entropy , 2009, 2009 Third IEEE International Conference on Secure Software Integration and Reliability Improvement.

[25]  Bing He,et al.  Mining diversity subgraph in multidisciplinary scientific collaboration networks: A meso perspective , 2013, J. Informetrics.

[26]  Johan Bollen,et al.  Co-authorship networks in the digital library research community , 2005, Inf. Process. Manag..

[27]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[28]  Enrico Gregori,et al.  Parallel $(k)$-Clique Community Detection on Large-Scale Networks , 2013, IEEE Transactions on Parallel and Distributed Systems.

[29]  Ernst Fehr,et al.  A Social Network Analysis of Research Collaboration in the Economics Community , 2022 .

[30]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[31]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[32]  Ryutaro Ichise,et al.  Research Community Mining with Topic Identification , 2006, Tenth International Conference on Information Visualisation (IV'06).

[33]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Michel Crampes,et al.  Survey on Social Community Detection , 2013, Social Media Retrieval.

[35]  Thomas L. Griffiths,et al.  The Author-Topic Model for Authors and Documents , 2004, UAI.

[36]  Narsingh Deo,et al.  Algorithms for discovering communities in complex networks , 2006 .

[37]  Renaud Lambiotte,et al.  Community structure and patterns of scientific collaboration in Business and Management , 2011, Scientometrics.

[38]  Liaquat Hossain,et al.  Exploring the Relationship between Research Impact and Collaborations for Information Science , 2012, 2012 45th Hawaii International Conference on System Sciences.

[39]  Reinhard C. Laubenbacher,et al.  Evolutionary events in a mathematical sciences research collaboration network , 2012, Scientometrics.

[40]  Aric Hagberg,et al.  Exploring Network Structure, Dynamics, and Function using NetworkX , 2008, Proceedings of the Python in Science Conference.

[41]  Mohammed Shahadat Uddin,et al.  Evolutionary dynamics of scientific collaboration networks: multi-levels and cross-time analysis , 2011, Scientometrics.