The Community for Technology Leaders
RSS Icon
Issue No.10 - Oct. (2013 vol.25)
pp: 2404-2417
Theodosis Moschopoulos , Technical University of Crete, Chania
Elias Iosif , Technical University of Crete, Chania
Leeda Demetropoulou , Technical University of Crete, Chania
Alexandros Potamianos , Technical University of Crete, Chania
Shrikanth Shri Narayanan , University of Southern California, Los Angeles
Policy networks are widely used by political scientists and economists to explain various financial and social phenomena, such as the development of partnerships between political entities or institutions from different levels of governance. The analysis of policy networks demands a series of arduous and time-consuming manual steps including interviews and questionnaires. In this paper, we estimate the strength of relations between actors in policy networks using features extracted from data harvested from the web. Features include webpage counts, outlinks, and lexical information extracted from web documents or web snippets. The proposed approach is automatic and does not require any external knowledge source, other than the specification of the word forms that correspond to the political actors. The features are evaluated both in isolation and jointly for both positive and negative (antagonistic) actor relations. The proposed algorithms are evaluated on two EU policy networks from the political science literature. Performance is measured in terms of correlation and mean square error between the human rated and the automatically extracted relations. Correlation of up to 0.74 is achieved for positive relations. The extracted networks are validated by political scientists and useful conclusions about the evolution of the networks over time are drawn.
Measurement, Feature extraction, Social network services, Context, Semantics, Data mining, Interviews, link analysis, Policy networks, social networks, relatedness metrics, similarity metrics, web search, policy actors
Theodosis Moschopoulos, Elias Iosif, Leeda Demetropoulou, Alexandros Potamianos, Shrikanth Shri Narayanan, "Toward the Automatic Extraction of Policy Networks Using Web Links and Documents", IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 10, pp. 2404-2417, Oct. 2013, doi:10.1109/TKDE.2012.159
[1] J. Peterson and E. Bomberg, Desicion-Making in the European Union. Palgrave Macmillan, 1999.
[2] P. Kenis and V. Schneider, Policy Networks and Policy Analysis: Scrutinizing a New Analytical Toolbox, pp. 25-59, Westview Press, 1991.
[3] L. Zhu, Computational Political Science Literature Survey, http://www.personal.psu.eduluz113, 2013.
[4] B. Monroe and P. Schrodt, "Introduction to the Special Issue: The Statistical Analysis of Political Text," Political Analysis, vol. 16, no. 4, pp. 351-355, 2008.
[5] M. Laver, K. Benoit, and J. Garry, "Extracting Policy Positions from Political Texts Using Words as Data," Am. Political Science Rev., vol. 97, no. 2, pp. 311-331, 2003.
[6] K. Benoit and M. Laver, "Estimating Irish Party Policy Positions Using Computer Wordscoring: The 2002 Elections - A Research Note," Irish Political Studies, vol. 18, no. 1, pp. 97-107, 2003.
[7] J.B. Slapin and S.-O. Proksch, "A Scaling Model for Estimating Time-Series Party Positions from Texts," Am. J. Political Science, vol. 52, no. 3, pp. 705-722, 2008.
[8] M. Thomas, B. Pang, and L. Lee, "Get Out the Vote: Determining Support or Opposition from Congressional Floor-debate Transcripts," Proc. Conf. Empirical Methods in Natural Language Processing, pp. 327-335, 2006.
[9] B. Chen, L. Zhu, D. Kifer, and D. Lee, "What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model," Proc. 24th AAAI Conf. on Artificial Intelligence, pp. 1007-1012, 2010.
[10] W. Gryc and K. Moilanen, "Leveraging Textual Sentiment Analysis with Social Network Modelling: Sentiment Analysis of Political Blogs in the 2008 U.S Presidential Election," Proc. 'From Text to Political Positions' Workshop, 2010.
[11] B. Monroe, M. Colaresi, and K. Quinn, "Fightin' Words: Lexical Feature Selection and Evaluation for Identifying the Content of Political Conflict," Political Analysis, vol. 16, no. 4, pp. 372-403, 2008.
[12] H. Kautz, B. Selman, and M. Shah, "The Hidden Web," AI Magazine, vol. 18, no. 2, pp. 27-36, 1997.
[13] Y. Matsuo, J. Mori, and M. Hamasaki, "POLYPHONET: An Advanced Social Network Extraction System from the Web," Proc. 15th Int'l World Wide Web Conf., pp. 397-406, 2006.
[14] H. Tomobe, Y. Matsuo, and K. Hasida, "Social Network Extraction of Conf. Participants," Proc. 12th Int'l World Wide Web Conf., 2003.
[15] Y. Jin, Y. Matsuo, and M. Ishizuka, "Extracting Social Networks among Various Entities on the Web," Proc. European Conf. The Semantic Web: Research and Applications, pp. 251-266, 2007.
[16] J. Mori, T. Tsujishita, Y. Matsuo, and M. Ishizuka, "Extracting Relations in Social Networks from the Web Using Similarity Between Collective Contexts," Proc. Fifth Int'l Semantic Web Conf., pp. 487-500, 2006.
[17] F. Mesquita, Y. Merhav, and D. Barbosa, "Extracting Information Networks from the Blogosphere: State-of-the-Art and Challenges," Proc. Fourth Int'l Conf. Weblogs and Social Media, Data Challenge Workshop, 2010.
[18] R. Xiang, J. Neville, and M. Rogati, "Modeling Relationship Strength in Online Social Networks," Proc. 19th Int'l World Wide Web Conf., pp. 981-990, 2010.
[19] P. Mika, "Flink: Semantic Web Technology for the Extraction and Analysis of Social Networks," J. Web Semantics, vol. 3, no. 2, pp. 211-223, 2005.
[20] P. Mika, "Ontlogies Are Us: A Unified Model of Social Networks and Semantics," J. Web Semantics, vol. 5, no. 1, pp. 5-15, 2007.
[21] A. Culotta, R. Bekkerman, and A. Mccallum, "Extracting Social Networks and Contact Information from Email and the Web," Proc. First Conf. Email and Anti-Spam, 2004.
[22] A. Gruzd and C. Haythornthwaite, "Automated Discovery and Analysis of Social Networks from Threaded Discussions," Proc. Int'l Network of Social Network Analysis, 2008.
[23] B. Pouliquen, R. Steinberg, and J. Belyaeva, "Multilingual Multi-Document Continuously-Updated Social Networks," Proc. Int'l Conf. in Recent Advances in Natural Language Processing, pp. 25-32, 2007.
[24] D.K. Elson, N. Dames, and K.R. McKeown, "Extracting Social Networks from Literary Fiction," Proc. 48th Ann. Meeting of the Assoc. Computational Linguistics, pp. 138-147, 2010.
[25] P. Nasirifard, V. Peristeras, C. Hayes, and S. Decker, "Extracting and Utilizing Social Networks from Log Files of Shared Workspaces," Proc. 10th IFIP Working Conf. Virtual Enterprises, pp. 643-650, 2009.
[26] E. Iosif and A. Potamianos, "Unsupervised Semantic Similarity Computation Using Web Search Engines," Proc. IEEE/WIC/ACM Int'l Conf. Web Intelligence, pp. 381-387, 2007.
[27] E. Iosif and A. Potamianos, "Unsupervised Semantic Similarity Computation between Terms Using Web Documents," IEEE Trans. Knowledge and Data Eng., vol. 22, no. 11, pp. 1637-1647, Nov. 2010.
[28] D. Bollegala, Y. Matsuo, and M. Ishizuka, "Measuring Semantic Similarity between Words Using Web Search Engines," Proc. 16th Int'l World Wide Web Conf., pp. 757-766, 2007.
[29] J. Gracia, R. Trillo, M. Espinoza, and E. Mena, "Querying the Web: A Multiontology Disambiguation Method," Proc. Sixth Int'l Conf. Web Eng., pp. 241-248, 2006.
[30] R. Cilibrasi and P. Vitanyi, "The Google Similarity Distance," IEEE Trans. Knowledge and Data Eng., vol. 19, no. 3, pp. 370-383, Mar. 2007.
[31] P. Vitanyi, "Universal Similarity," Proc. Information Theory Workshop Coding and Complexity, pp. 238-243, 2005.
[32] P. Calado, M. Cristo, E. Moura, N. Ziviani, B. Ribeiro-Neto, and M.A. Gonçalves, "Combining Link-Based and Content-Based Methods for Web Document Classification," Proc. 12th Int'l Conf. Information and Knowledge Management, pp. 394-401, 2003.
[33] S. Chakrabarti, Mining the Web: Discovering Knowledge from Hypertext Data. Morgan-Kauffman, 2002.
[34] N. Rees, B. Quinn, and B. Connaughton, "Ireland's Pragmatic Adaptation to Regionalization: The Mid-West Region," Regional and Fed. Studies, vol. 14, no. 3, pp. 379-404, 2004.
[35] P. Getimis and L. Demetropoulou, "Europeanization towards New Forms of Regional Governance in Greece," Proc. Regional Studies Assoc. Int'l Conf., 2003.
[36] K. Frantzi, S. Ananiadou, and H. Mima, "Automatic Recognition of Multi-Word Terms: The C-Value/NC-Value Method," Int'l J. Digital Libraries, vol. 3, no. 2, pp. 115-130, 2000.
[37] F. Lazarinis, "Engineering and Utilizing a Stopword List in Greek Web Retrieval," J. Am. Soc. Information Science and Technology, vol. 58, no. 11, pp. 1645-1652, 2007.
[38] M.E.J. Newman, "Analysis of Weighted Networks," Physical Rev. E, vol. 70, no. 5, pp. 056131-1-056131-9, 2004.
[39] T. Kamada and S. Kawai, "An Algorithm for Drawing General Undirected Graphs," Information Processing Letters, vol. 31, no. 1, pp. 7-15, 1989.
32 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool