A review of the literature on applications of text mining in policy making

Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings

Volumn , Issue , 2016, Pages

  Ngai, E W T ^a   Lee, P T Y ^a  

^a HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Conceptual framework; E government; Literature review; Policy making; Text mining

Indexed keywords

BEHAVIORAL RESEARCH; DECISION MAKING; GOVERNMENT DATA PROCESSING; INFORMATION SYSTEMS; PUBLIC POLICY;

CONCEPTUAL FRAMEWORKS; E-GOVERNMENTS; LITERATURE REVIEWS; POLICY MAKING; TEXT MINING;

DATA MINING;

EID: 85011024206     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (55)

1. Aggarwal, C. C, & Zhai, C. (2012). An introduction to text mining. In Aggarwal, C. C, & Zhai, C. (Eds.), Mining text data (1-10). Springer.
2. Ahn, M. J., & Bretschneider, S. (2011). Politics of E-Government: E-Government and the Political Control of Bureaucracy. Public Administration Review, 71(3), 414-424.
3. Altaweel, M., & Bone, C. (2012). Applying content analysis for investigating the reporting of water issues. Computers, Environment and Urban Systems, 36(6), 599-613.
4. Al-Zaidy, R, Fung, B., Youssef, A. M., & Fortin, F. (2012). Mining criminal networks from unstructured text documents. Digital Investigation, 8(3), 147-160.
5. Brownstein, J. S., Freifeld, C. C, Reis, B. Y., & Mandl, K. D. (2008). Surveillance Sans Frontieres: Internet-based emerging infectious disease intelligence and the HealthMap project. PLoS medicine, 5(7), e151.
6. Cecchini, M., Aytug, H., Koehler, G J., & Pathak, P. (2010). Making words work: Using financial text as a predictor of financial events. Decision Support Systems, 50(1), 164-175.
7. Chadwick, A., & May, C. (2003). Interaction between States and Citizens in the Age of the Internet: "e-Government" in the United States, Britain, and the European Union. Governance, 16(2), 271-300.
8. Charalabidis, Y., & Loukis, E. (2012). Participative public policy making through multiple social media platforms utilization. International Journal of Electronic Government Research (IJEGR), 8(3), 78-97.
9. Chun, S. A., Shulman, S., Sandoval, R, & Hovy, E. (2010). Government 2.0: Making connections between citizens, data and government. Information Polity, 15(1), 1-9.
10. Collier, N., Doan, S., Kawazoe, A., Goodwin, R M., Conway, M., Tateno, Y.,... & Taniguchi, K. (2008). BioCaster: detecting public health rumors with a Web-based text mining system. Bioinformatics, 24(24), 2940-2941.
11. Corley, C. D., Cook, D. J., Mikler, A. R, & Singh, K. P. (2010). Text and structural data mining of influenza mentions in web and social media. International journal of environmental research and public health, 7(2), 596-615.
12. Dunn W (1994) Public policy analysis: an introduction. Prentice Hall, New Jersey
13. Evangelopoulos, N., & Visinescu, L. (2012). Text-mining the voice of the people. Communications of the ACM, 55(2), 62-69.
14. Gal-Tzur, A., Grant-Muller, S. M., Kuflik, T., Minkov, E., Nocera, S., & Shoor, I. (2014). The potential of social media in delivering transport policy goals. Transport Policy, 32, 115-123.
15. Ginsberg, J., Mohebbi, M. H., Patel, R. S., Brammer, L., Smolinski, M. S., & Brilliant, L. (2009). Detecting influenza epidemics using search engine query data. Nature, 457(7232), 1012-1014.
16. Grimmer, J. (2010). A Bayesian hierarchical topic model for political texts: Measuring expressed agendas in Senate press releases. Political Analysis, 18(1), 1-35.
17. Gupta, M. P., & Jana, D. (2003). E-government evaluation: A framework and case study. Government Information Quarterly, 20(4), 365-387.
18. Herman Tolentino, M. D., Raoul Kamadjeu, M. D., Michael Matters PhD, M. P. H, Marjorie Pollack, M. D., & Larry Madoff, M. D. (2007). Scanning the emerging infectious diseases Horizon-visualizing ProMED emails using EpiSPIDER. Advances in disease surveillance, 2, 169.
19. Hulth, A., Rydevik, G, & Linde, A. (2009). Web queries as a source for syndromic surveillance. PloS one, 4(2), e4378.
20. Jann, W., & Wegrich, K. (2007). 4 Theories of the Policy Cycle. Handbook of public policy analysis, 43.
21. Junqué de Fortuny, E., De Smedt, T., Martens, D., & Daelemans, W. (2012). Media coverage in times of political crisis: a text mining approach. Expert Systems with Applications, 39(14), 11616-11622.
22. Kokkinakos, P., Koussouris, S., Panopoulos, D., Askounis, D., Ramfos, A., Georgousopoulos, C, & Wittern, E. (2012). Citizens collaboration and co-creation in public service delivery: The COCKPIT project. International Journal of Electronic Government Research (IJEGR), 8(3), 33-62.
23. Kugo, A., Yoshikawa, H., Shimoda, H., & Wakabayashi, Y. (2005). Text mining analysis of public comments regarding high-level radioactive waste disposal. Journal of Nuclear Science and Technology, 42(9), 755-767.
24. Lim, E. T. (2002). Five trends in presidential rhetoric: An analysis of rhetoric from George Washington to Bill Clinton. Presidential Studies Quarterly, 32(2), 328-348.
25. Lindblom, Charles. 1959. The Science of "Muddling Through. " Public Administration Review 29(1):79-88.
26. Lee, S. M., Tan, X., & Trimi, S. (2005). Current practices of leading e-government countries. Communications of the ACM, 48(10), 99-104.
27. Lourenço, R. P., & Costa, J. P. (2007). Incorporating citizens' views in local policy decision making processes. Decision Support Systems, 43(4), 1499-1511.
28. Lu, Y. C, Shen, C. H., & Wei, Y. C. (2013). Revisiting early warning signals of corporate credit default using linguistic analysis. Pacific-Basin Finance Journal, 24, 1-21.
29. Malouf, R, & Mullen, T. (2008). Taking sides: User classification for informal online political discourse. Internet Research, 18(2), 177-190.
30. Mykhalovskiy, E., & Weir, L. (2006). The Global Public Health Intelligence Network and early warning outbreak detection: a Canadian contribution to global public health. Canadian Journal of Public Health/Revue Canadienne de Sante'e Publique, 42-44.
31. Nord, J. H., & Nord, G D. (1995). MIS research: Journal status and analysis. Information & Management, 29, 29-42.
32. Park, S. J., Lim, Y. S., Sams, S., Nam, S. M., & Park, H. W. (2011). Networked politics on Cyworld: The text and sentiment of Korean political profiles. Social Science Computer Review, 29(3), 288-299.
33. Polgreen, P. M., Chen, Y., Pennock, D. M., Nelson, F. D., & Weinstein, R A. (2008). Using internet searches for influenza surveillance. Clinical infectious diseases, 47(11), 1443-1448.
34. Quinn, K. M., Monroe, B. L., Colaresi, M., Crespin, M. H., & Radev, D. R (2010). How to analyze political attention with minimal assumptions and costs. American Journal of Political Science, 54(1), 209-228.
35. Sakaki, T., Okazaki, M., & Matsuo, Y. (2013). Tweet analysis for real-time event detection and earthquake reporting system development. Knowledge and Data Engineering, IEEE Transactions on, 25(4), 919-931.
36. Schonhardt-Bailey, C, Yager, E., & Lahlou, S. (2012). Yes, Ronald Reagan's rhetoric was unique-but statistically, how unique?. Presidential Studies Quarterly, 42(3), 482-513.
37. Simon, HA. (1996). The sciences of the artificial, 3d ed. Cambridge, Mass.: MIT Press.
38. Sobkowicz, P., Kaschesky, M., & Bouchard, G (2012). Opinion mining in social media: Modeling, simulating, and forecasting political opinions in the web. Government Information Quarterly, 29(4), 470-479.
39. Stylios, G., Christodoulakis, D., Besharat, J., Vonitsanou, M., Kotrotsos, I., Koumpouri, A., & Stamou, S. (2010). Public opinion mining for governmental decisions. Electronic Journal of e-Government, 8(2), 203-214.
40. Suh, J. H, Park, C. H, & Jeon, S. H. (2010). Applying text and data mining techniques to forecasting the trend of petitions filed to e-People. Expert Systems with Applications, 37(10), 7255-7268.
41. Talamini, E., Eduardo Caldarelli, C, Wubben, E. F., & Dewes, H. (2012). The composition and impact of stakeholders' agendas on US ethanol production. Energy Policy, 50, 647-658.
42. Talamini, E., & Dewes, H. (2012). The macro-environment for liquid Biofuels in Brazilian science and public policies. Science and Public Policy, scr002.
43. Talamini, E., Wubben, E. F., & Dewes, H. (2013). The Macro-Environment for Liquid Biofuels in German Science, Mass Media and Government. Review of European Studies, 5 (2). 33-47
44. Thelwall, M., Vann, K., & Fairclough, R. (2006). Web issue analysis: An integrated water resource management case study. Journal of the American Society for information Science and Technology, 57(10), 1303-1314.
45. Torii, M., Yin, L., Nguyen, T., Mazumdar, C. T., Liu, H., Hartley, D. M., & Nelson, N. P. (2011). An exploratory study of a text classification framework for internet-based surveillance of emerging epidemics. International journal of medical informatics, 80(1), 56-66.
46. Tseng, Y. H., Ho, Z. P., Yang, K. S., & Chen, C. C. (2012). Mining term networks from text collections for crime investigation. Expert Systems with Applications, 39(11), 10082-10090.
47. Velásquez, J. D., & González, P. (2010). Expanding the possibilities of deliberation: The use of data mining for strengthening democracy with an application to education reform. The Information Society, 26(1), 1-16.
48. Walker, M. A., Anand, P., Abbott, R, Tree, J. E. F., Martell, C, & King, J. (2012). That is your evidence?: Classifying stance in online political debate. Decision Support Systems, 53(4), 719-729.
49. Wandhöfer, T., Taylor, S., Alani, H, Joshi, S., Sizov, S., Walland, P.,... & Mutschke, P. (2012). Engaging politicians with citizens on social networking sites: the WeGov Toolbox. International Journal of Electronic Government Research (IJEGR), 8(3), 22-32.
50. Webster, J., & Watson, R. T. (2002). Analyzing the past to prepare for the future: Writing a literature review. Management Information Systems Quarterly, 26(2), 3.
51. Wildavsky, A. (1984). The Politics of the Budgetary Process. 4th ed. Boston: Little, Brown.
52. Wormell, I. (2000). Critical aspects of the Danish welfare state-as revealed by issue tracking. Scientometrics, 48(2), 237-250.
53. Young, L., & Soroka, S. (2012). Affective news: The automated coding of sentiment in political texts. Political Communication, 29(2), 205-231.
54. Zirn, C, & Stuckenschmidt, H. (2014). Multidimensional topic analysis in political texts. Data & Knowledge Engineering, 90, 38-53.
55. Zouridis, S., & Thaens, M. (2003). E-government: towards a public administration approach. Asian Journal of Public Administration, 25(2), 159-183.