Extracting a Heterogeneous Social Network of AcademicResearchers on the Web Based on Information Retrieved from Multiple Sources

Abstract

The majority of academic researchers present the results of their scientific activity on the Web. This trace can be used to derive useful information of their past, present activity and forecast the future intentions. Hence, social network of academic researchers can be of important value for scientific community. This information can be retrieved from various data source currently available on the Web. From each of them a separate net-work can be built. In this paper we present a method which can be used to combine multiple single-relational networks into a single network which will combine all relations, hence it will be multi-relational.

Share and Cite:

Alguliev, R. , Aliguliyev, R. and Ganjaliyev, F. (2011) Extracting a Heterogeneous Social Network of AcademicResearchers on the Web Based on Information Retrieved from Multiple Sources. American Journal of Operations Research, 1, 33-38. doi: 10.4236/ajor.2011.12005.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] J. Golbeck, “Web-based Social Networks: A Survey and Future Directions,” Technical Report, Citeseer, 2005.
[2] B. Poliqean, H. Tanev and M. Atkinson, “Extracting and Learning Social Networks out of Multilingual News,” Proceedings of the Social Networks and Application Tools Workshop, Skalica, September 2008, pp. 19-21.
[3] P. Nasirifard, V. Peristeras, C, Hayes and S. Decker, “Extracting and Utilizing Social Networks from Log Files of Shared Workspaces,” Proceedings of the 10th IFIP Working Conference on Virtual Enterprises, Thessaloniki, October 2009, pp. 7-9.
[4] G. Geleijnse and J. Korst, “Creating a Dead Poets Society: Extracting a Social Network of Historical Persons from the Web,” Proceedings of the 6th International and the 2nd Asian Conference on Asian Semantic Web Conference, Busan, Vol. 4825, October 2007, pp. 155-168.
[5] T. Nishimura and Y. Matsuo, “A Method of Social Network Extraction via Internet and Networked Sensing,” Proceedings of the 3rd International Conference on Networked Sensing Systems, Chicago, May-June 2006.
[6] H. Kautz, B. Selman and M. Shah, “The Hidden Web,” AI Magazine, Vol. 18, 1997, pp. 27-35.
[7] P. Mika, “Flink: Semantic Web Technology for Extraction and Analysis of Social Networks,” Journal of Web Semantics, Vol. 3, No. 2, October 2005, pp. 211-223. doi:10.1016/j.websem.2005.05.006
[8] A. Culotta, R. Bekkerman and A. McCallum, “Extracting Social Networks and Contact Information from Email and the Web,” Proceedings of the 1st Conference on Email and Anti-Spam, California, July 2004.
[9] Y. Matsuo, J. Mori and M. Hamasaki, “POLYPHONET: An Advanced Social Network Extraction System,” Proceedings of the 15th International Conference on World Wide Web, Edinburgh, May 2006, pp. 397-406.
[10] J. Tang, D. Zang and L. Yao, “Social Network Extraction of Academic Researchers,” Proceedings of the 7th IEEE International Conference on Data Mining, Omaha, 28-31 October 2007, pp. 292-301.
[11] V. Stroele, J. Oliveira, G. Zimbrao and J. M. Souza, “Mining and Analyzing Multi-relational Social Networks,” Proceedings of the 12th International Conference on Computational Science and Engineering, Vancouver, Vol. 4, 29-31 August 2009, pp. 711-716. doi:10.1109/CSE.2009.69
[12] R. Rowe, G. Creamer, S. Hershkop and S. J. Stoflo, “Automated Social Hierarchy Detection Through Email and Network Analysis,” Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, 12-15 August 2007, pp. 109-117.
[13] C. Bron and J. Kerbosch, “Finding All Cliques of an Undirected Graph,” Communications of the ACM, Vol. 16, No. 9, Septermber 1973, pp. 575-577.
[14] Q. Li and Y. B. Wu, “People Search: Searching People Sharing Similar Interests from the Web,” Journal of the American Society for Information Science and Technology, Vol. 59, No. 1, January 2008, pp. 111-125. doi:10.1002/asi.20736
[15] T. Finin, L. Ding and L. Zou, “Social Networking on the Semantic Web,” The Learning Organization, Vol. 12, No. 5, December 2005, pp. 418-435. doi:10.1108/09696470510611384
[16] B. Aleman-Meza, M. Nagarajan, C. Ramakrishnan, L. Ding, P. Kolari, A. Sheth, I. B. Arpinar, A. Joshi and T. Finin, “Semantic Analytics on Social Networks: Experiences in Addressing the Problem of Conflict of Interest Detection,” Proceedings of the 15th International World Wide Web Conference, Edinburgh, 23-26 May 2006, pp. 407-416. doi:10.1145/1135777.1135838
[17] J. Goldbeck and M. Rothstein, “Linking Social Networks on the Web with FOAF,” Proceedings of the 23rd National Conference on Artificial Intelligence, Chicago, Vol. 2, 13-17 July 2008, pp. 1138-1143.
[18] R. Alguliev, R. Aliguliyev and F. Ganjaliyev, “Investigation the Role of Similarity Measure and Ranking Algorithm in Mining Social Network,” Journal of Information Science, Vol. 37, No. 3, March 2011, pp. 229-234. doi:10.1177/0165551511400946
[19] N. Du, B. Wu, X. Pei, B. Wang and L. Xu, “Community Detection in Large-Scale Social Networks,” Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, August 2007, pp. 16-25.
[20] J. Baumes, M. Goldberg, M. Magdon and W. Wallace, “Discovering Hidden Groups in Communication Networks,” Proceedings of the 2nd NSF/NIJ Symposium on Intelligence and Security Informatics, Tucson, July 2004. doi:10.1007/978-3-540-25952-7_28
[21] D. Cai, Z. Shao, X. He, X. Yan and J. Han, “Mining Hidden Community in Heterogeneous Social Networks,” Proceeings of the 3rd International Workshop on Link Discovery, Chicago, 21-24 August 2005, pp. 58-65.
[22] F. Ganjaliyev, “Building a Heterogeneous Social Network of Academic Researchers,” Proceedings of the 3rd International Conference of Problems of Cybernetics and Informatics, Baku, 6-8 Septermber 2010, pp. 179-182.
[23] P. A. Rotshtein, “Fuzzy Multicriteria Choice among Alternatives: Worst-Case Approach,” Journal of Computer and Systems Sciences International, Vol. 25, No. 9, September 2010, pp. 948-957.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.