1 |
Ahn, S., & Jung, W.(2014). An Analysis of Influence Factors on the Satisfaction of Rural Village Development Projects, The Korean Association for Local Government Studies, 2, 1-34.
|
2 |
Asuncion, A., Welling, M., Smyth, P., & Teh, Y. W. (2009). On smoothing and inference for topic models. In Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, AUAI Press. 27-34.
|
3 |
Barranco, J. & Wisler, D.(1999). Validity and systematicity of newspaper data in event analysis. Eur Sociol Rev, 15(3), 301-322.
DOI
|
4 |
Battisti, F. D., Ferrara, A., & Salini, S.(2015). A decade of research in statistics: a topic model approach. Scientometrics, 103, 413-433.
DOI
|
5 |
Binkley, D., Heinz, D., Lawrie, D., & Overfelt, J.(2014). Understanding LDA in source code analysis. In Proceedings of the 22nd Int'l Conf. on Program Comprehension, ACM. 26-36.
|
6 |
Blei, D., & Jordan, M.(2003). Modeling annotated data. In Proceedings of the 26th annual international ACM SIGIR conference on Research and development in information retrieval, ACM. 127-134.
|
7 |
Blei, D.(2011). Introduction to probabilistic topic models. Communications of the ACM, 77-84.
|
8 |
Blei, D. M.(2012). Probabilistic topic models. Communications of the ACM, 55(4), 77-84.
DOI
|
9 |
Brauer, R. & Dymitrow, M.(2014). Quality of life in rural areas: A topic for the Rural Development policy?. Bulletin of Geography. Socio-economic Series, 25, 25-54.
DOI
|
10 |
Chandra, Y., Jiang, L. C., & Wang, C.(2016). Mining social entrepreneurship strategies using topic modeling. PLoS ONE, 11(3), 1-28.
|
11 |
Daniel, B.(2015). Big data and analytics in higher education: opportunities and challenges. British Journal of Educational Technology, 46(5), 904-920.
DOI
|
12 |
Ding, W., & Chen, C. (2014). Dynamic topic detection and tracking: A comparison of HDP, C-word, and cocitation methods. Journal of the Association for Information Science and Technology, 65(10), 2084-2097.
DOI
|
13 |
Earl, J., Martin, A., McCarthy, J. D., Soule, S. A.(2004). The use of newspaper data in the study of collective action. Annu Rev Sociol, 30, 65-80.
DOI
|
14 |
Friedman, J. H.(1997). On Bias, Variance, 0/1-Loss, and the Curse of Dimensionality, Data Mining and Knowledge Discovery, 1, 55-77.
DOI
|
15 |
Friedmann, J.(2001). Regional Development and Planning: The Story of a Collaboration, International Regional Science Review, 24(3), 386-395.
DOI
|
16 |
Gan, Q., Zhu, M., Li, M., Liang, T., Cao, Y., & Zhou, B.(2014). Document visualization: an overview of current research. Wiley Interdisciplinary Reviews: Computational Statistics, 6(1), 19-36.
DOI
|
17 |
Geman, S., Bienenstock, E., & Doursat, R.(1992). Neural Networks and the Bias/Variance Dilemma, Neural Computation, 4, 1-58.
DOI
|
18 |
Grant, S., Cordy, J. R., & Skillicorn, D. B. (2013). Using heuristics to estimate an appropriate number of latent topics in source code analysis. Science of Computer Programming, 78(9), 1663-1678.
DOI
|
19 |
Greene, D. & Cross, J. P.(2015). Unveiling the Political Agenda of the European Parliament Plenary: A Topical Analysis. Proceedings of the ACM Web Science Conference, ACM, 2.
|
20 |
Griffiths, T. L., & Steyvers, M.(2004). Finding scientific topics. Proceedings of the National academy of Sciences, 101(1), 5228-5235.
DOI
|
21 |
Guo, L., Vargo, C. J., Pan, Z., Ding, W., & Ishwar, P. (2016). Big social data analytics in journalism and mass communication: comparing dictionary-based text analysis and unsupervised topic modeling. Journalism & Mass Communication Quarterly, 93(2), 332-359.
DOI
|
22 |
Han, J., & Kamber, M.(2011). Data Mining: Concepts and Techniques, 3rd ed, Morgan Kaufmann Publishers.
|
23 |
Hannigan, T.(2015). Close encounters of the conceptual kind: disambiguating social structure from text. Big Data & Society, 2(2), 1-6.
|
24 |
Hastie, T., Tibshirani, R., & Friedman, J. H.(2008). The Elements of Statistical Learning: Data Mining, Inference, and prediction, 2nd ed, New York: Springer.
|
25 |
Hu, Y., & Li, W.(2011). Document sentiment classification by exploring description model of topical terms. Computer Speech and Language, 25, 386-403.
DOI
|
26 |
Huang, X., Wan, X. & Xiao, J.(2014). Comparative news summarization using concept-based optimization, Knowledge and information systems, 31(3). 391-716.
|
27 |
Jacobi, C., van Atteveldt, W., & Welbers, K.(2016). Quantitative analysis of large amounts of journalistic texts using topic modeling. Digital Journalism, 4(1), 89-106.
DOI
|
28 |
Jockers, M. L.(2014). Text analysis with R for students of literature. Switzerland: Springer International Publishing.
|
29 |
Jung, C., & Ahn, J.(2015). A Study on the Recognition of the Residential Environments Connected to Local Central Cities - Focusing on Gyeongnam Area of the West, Residential Environment Institute of Korea, 13(2), 41-52.
|
30 |
Karl, A., Wisnowski, J., & Rushing, W. H.(2015). A practical guide to text mining with topic extraction. Wiley Interdisciplinary Reviews: Computational Statistics, 7(5), 326-340.
DOI
|
31 |
Kelly, J., & Swindell, D.(2002). Service Quality Variation Across Urban Space: First Steps Toward a Model of Citizen Satisfaction, Journal of Urban Affairs, 24(3), 271-288.
DOI
|
32 |
Kim, E., Ahn, Y., & Lee, M.(2012). An Improvement of Evaluation Indicator System Geared towards Comprehensive Rearrangement Projects in Seats of Township and Town Offices: Based on the Existing Evaluation Indicator System of Small Town Promotion Projects, Korean Institute of Rural Architectures, 14(1), 45-56.
|
33 |
Kim, J., & Gim, U.(2013). Review and Proposal of Central place Improvement Project in Basic Settlement Area-Centered on Comprehensive Improvement Project of the Seat of Eup(Dong)Myon, JKRDA, 25(4), 133-152.
|
34 |
Kim, J., & Baek, S.(2016). Analysis of Issues on the College and University Structural Reform Evaluation Using Text Big Data Analytics, Asian Journal of Education, 17(3), 409-436.
DOI
|
35 |
Kim, Y., & Son, Y.(2017). The Residents' Perceptions on the Revitalization Project of Rural Centers Utilizing IPA: The Case of Janggye-myeon of Jangsu-gun, KSRP, 23(3), 133-145.
|
36 |
Ko, Y.(2009). Typical Development Models for Revitalization of Rural Market Towns, Department of Bio Systems & Rural Engineering, Chonnam National University.
|
37 |
Lee, S.(2011). An Comparative Analysis on the Regional Economic Effect of the Small Town Revitalization Project, Korean Association for Local Government Studies, 13(1), 31-54.
|
38 |
Lucas, C., Nielsen, R. A., Roberts, M. E., Stewart, B. M., Storer, A., & Tingley, D.(2015). Computer-assisted text analysis for comparative politics. Political Analysis, 23(2), 254-277.
DOI
|
39 |
Lim, C., Choi, S., & Sim, H.(2009). An Analysis on Spatial Characteristics in the Center Villages of Hub-Myun Site. KSRP, 15(3), 35-46.
|
40 |
Lim, H., & Park, S.(2015). A Tentative Approach for Regional Futures Strategy with Big Data: Through the Analysis using the Data of SNS and Newspaper. Journal of the Korean Cadastre Information Association, 17(1), 75-90.
|
41 |
MAFRA(2016). A New Approach to Rural Development.
|
42 |
MAFRA(2017). A Plan to Develop General Farming and Fishing Villages in 2019.
|
43 |
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburghh, C., & Byers, A. H.(2011). Big data: the next frontier for innovation, competition and productivity. McKinsey Global Institute Report.
|
44 |
Matthies, B., & Corners, A.(2015). Computer-aided text analysis of corporate disclosures-demonstration and evaluation of two approaches. The International Journal of Digital Accounting Research, 15, 69-98.
DOI
|
45 |
Moreno, A., & Redondo, T.(2015). Text analytics: the convergence of big data and artificial intelligence. International Journal of Interactive Multimedia and Artificial Intelligence, 3(6), 57-64.
DOI
|
46 |
Newman, M. E. J.(2004). Fast algorithm for detecting community structure in networks, Phys. Rev. E 69 066133.
DOI
|
47 |
Niedomysl, T. & Amcoff, J.(2011). Is there hidden potential for rural population growth in sweden?, Rural Sociology, 76(2), 257-279.
DOI
|
48 |
Park, S., & Kim, Y.(2014). A Study on the Revitalization of the Seat of Myeon for Rural Sustainability: Focusing on the Resident's Perceptions of Seat of Myeon in Jeollanam-do, Architectural Institute of Korea, 16(5), 45-53.
|
49 |
Oliver. P. E. & Myer, D. T.(1999). How events enter the public sphere: conflict, location, and sponsorship in local newspaper coverage of public events. Am J Sociol, 105(1), 38-87.
DOI
|
50 |
Park, K., & Lee, H.(2009). Residents' Participation and Satisfaction of the Altered Environment in the Development of Rural Agricultural Area, Korean Institute of Rural Architectures, 11(1), 57-66.
|
51 |
Paul, M. & Dredze, M.(2012). Factorial LDA: Sparse multi-dimensional text models. Advances in Neural Information Processing Systems, 2582-2590.
|
52 |
Ready, J., White, M. D. & Fisher, C.(2006). Shock value: a comparative analysis of news reports and official police records on TASER deployments. Policing An Int J Police Strateg Manag. 32(1), 148-170.
|
53 |
Shumueli, G., Patel, N. R., & Bruce, P. C.(2010). Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner, 2nd ed. New York: Wiley & Sons.
|
54 |
Shmueli, G., & Koppius, O.(2011). Predictive Analytics in Information Systems Research, MIS Quarterly, 35(3), 553-572.
DOI
|
55 |
Song, M., & Sung, J.(2004). A Study on the Evaluation and Model of participatory Community Development project in Korea, Korea Rural Economic Institute.
|
56 |
Steyvers, M., & Griffths, T.(2007). Probabilistic topic models. In Landauer, T. K., McNamara, D. S., Dennis, S. & Kintsch, W.(Eds.), Latent Semantic Analysis: A Road to Meaning. (427-448). Mahwah, NJ, US: Lawrence Erbaum Associates Publishers.
|
57 |
Zhang, X.-P., Zhou, X.-Z., Huang, H.-K., Feng, Q., Chen, S.-B. & Liu, B.-Y.(2011). Topic model for chinese medicine diagnosis and prescription regularities analysis: case on diabetes. Chinese journal of integrative medicine, 17, 307-313.
DOI
|
58 |
Visvaldis, V., Ainhoa, G. & Ralfs, P.(2013). Selecting indicators for sustainable development of small towns: the case of Valmiera municipality, Procedia Computer Science, 26, 21-32.
DOI
|
59 |
Wiedemann, G.(2013). Opening up to big data: computer-assisted analysis of textual data in social science. Forum Qualitative Social Research, 14(2), Art. 13.
|