뉴스데이터의 LDA 토픽 분석을 통한 장수군 농촌지역 활성화 사업의 특징- 관광·생활 키워드를 중심으로 -
Features of the Rural Revitalization Projects in Jang-su County Using LDA Topic Analysis of News Data - Focused on Keyword of Tourism and Livelihood -
0
조회
0
다운로드
14
인용
0
참고문헌
키워드
초록
In this study, we typified the project for revitalizing the rural area through text analysis using news data, and analyzed the main direction and characteristics of the project. In order to examine the factors emphasized among the issues related to the revitalization of rural areas, we used news data related to 'tourism' and 'livelihood', which are the main keyword of the project to promote rural areas. In the analysis, text mining techniques were used. Topic modeling was conducted on LDA techniques for major projects in 'tourism' and 'livelihood' keyword. Based on this, this study typified the projects that are carried out for the activation of rural areas by topic. As a result of the analysis, it was fount that the topics included in the project were distributed in 11 sub-types(Tourism Promotion, Regional Specialization, Local Festival, Development of Regional Scale, Urban and Rural Exchange, Agricultural Support, Community Forest Management, Improve the Settlement Environment, General Welfare Service, Low Class Support, Others). The characteristics of the rural revitalization projects were examined, and it was confirmed that domestic projects were carried out by tourism-oriented projects. To summarize, the government is making projects to revitalize rural areas through related ministries. Within the structure where the project is spreading to the region, a lot of projects are being carried out. It is understood that the tourism and welfare oriented projects are being carried out in the revitalization project of the domestic rural area. Therefore, in order to achieve the goal of rural revitalization, it is believed that it will be effective to carry out a balanced project to improve the settlement environment of the residents.
Abstract
In this study, we typified the project for revitalizing the rural area through text analysis using news data, and analyzed the main direction and characteristics of the project. In order to examine the factors emphasized among the issues related to the revitalization of rural areas, we used news data related to 'tourism' and 'livelihood', which are the main keyword of the project to promote rural areas. In the analysis, text mining techniques were used. Topic modeling was conducted on LDA techniques for major projects in 'tourism' and 'livelihood' keyword. Based on this, this study typified the projects that are carried out for the activation of rural areas by topic. As a result of the analysis, it was fount that the topics included in the project were distributed in 11 sub-types(Tourism Promotion, Regional Specialization, Local Festival, Development of Regional Scale, Urban and Rural Exchange, Agricultural Support, Community Forest Management, Improve the Settlement Environment, General Welfare Service, Low Class Support, Others). The characteristics of the rural revitalization projects were examined, and it was confirmed that domestic projects were carried out by tourism-oriented projects. To summarize, the government is making projects to revitalize rural areas through related ministries. Within the structure where the project is spreading to the region, a lot of projects are being carried out. It is understood that the tourism and welfare oriented projects are being carried out in the revitalization project of the domestic rural area. Therefore, in order to achieve the goal of rural revitalization, it is believed that it will be effective to carry out a balanced project to improve the settlement environment of the residents.
참고문헌 (59)
- Ahn, S., "An Analysis of Influence Factors on the Satisfaction of Rural Village Development Projects", The Korean Association for Local Government Studies, 2, pp.1~34 (2014)
- Asuncion, A., "On smoothing and inference for topic models", Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, pp.27~34 (2009), AUAI Press
- Barranco, J., "Validity and systematicity of newspaper data in event analysis", Eur Sociol Rev, 15(3), pp.301~322 (1999)
- Battisti, F. D., "A decade of research in statistics : a topic model approach", Scientometrics, 103, pp.413~433 (2015)
- Binkley, D., "Understanding LDA in source code analysis", Proceedings of the 22nd Int’l Conf. on Program Comprehension, pp.26~36 (2014), ACM
- Blei, D., "Modeling annotated data", Proceedings of the 26th annual international ACM SIGIR conference on Research and development in information retrieval, pp.127~134 (2003), ACM
- Blei, D., "Introduction to probabilistic topic models", Communications of the ACM, pp.77~84 (2011)
- Blei, D. M., "Probabilistic topic models", Communications of the ACM, 55(4), pp.77~84 (2012)
- Brauer, R., "Quality of life in rural areas: A topic for the Rural Development policy?", Bulletin of Geography. Socio-economic Series, 25, pp.25~54 (2014)
- Chandra, Y., "Mining social entrepreneurship strategies using topic modeling", PLoS ONE, 11(3), pp.1~28 (2016)
- Daniel, B., "Big data and analytics in higher education : opportunities and challenges", British Journal of Educational Technology, 46(5), pp.904~920 (2015)
- Ding, W., "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), pp.2084~2097 (2014)
- Earl, J., "The use of newspaper data in the study of collective action", Annu Rev Sociol, 30, pp.65~80 (2004)
- Friedman, J. H., "On Bias, Variance, 0", 1-Loss, and the Curse of Dimensionality, 1997, pp.1, 55~77
- Friedmann, J., "Regional Development and Planning : The Story of a Collaboration", International Regional Science Review, 24(3), pp.386~395 (2001)
- Gan, Q., "Document visualization : an overview of current research", Wiley Interdisciplinary Reviews : Computational Statistics, 6(1), pp.19~36 (2014)
- Geman, S., "Neural Networks and the Bias", Variance Dilemma, 1992, pp.4, 1~58
- Grant, S., "Using heuristics to estimate an appropriate number of latent topics in source code analysis", Science of Computer Programming, 78(9), pp.1663~1678 (2013)
- Greene, D., "Unveiling the Political Agenda of the European Parliament Plenary:A Topical Analysis", Proceedings of the ACM Web Science Conference, pp.2~ (2015), ACM
- Griffiths, T. L., "Finding scientific topics", Proceedings of the National academy of Sciences, 101(1), pp.5228~5235 (2004)
- Guo, L., "Big social data analytics in journalism and mass communication : comparing dictionary-based text analysis and unsupervised topic modeling", Journalism & Mass Communication Quarterly, 93(2), pp.332~359 (2016)
- Han, J., "Data Mining: Concepts and Techniques" (2011), Morgan Kaufmann Publishers
- Hannigan, T., "Close encounters of the conceptual kind : disambiguating social structure from text", Big Data & Society, 2(2), pp.1~6 (2015)
- Hastie, T., "The Elements of Statistical Learning: Data Mining, Inference, and prediction" (2008), Springer
- Hu, Y., "Document sentiment classification by exploring description model of topical terms", Computer Speech and Language, 25, pp.386~403 (2011)
- Huang, X., "Comparative news summarization using concept-based optimization", Knowledge and information systems, 31(3), pp.391~716 (2014)
- Jacobi, C., "Quantitative analysis of large amounts of journalistic texts using topic modeling", Digital Journalism, 4(1), pp.89~106 (2016)
- Jockers, M. L., "Text analysis with R for students of literature" (2014), Springer International Publishing
- 정창호, "지역 중심도시와 연계한 정주환경 인식에 관한 연구- 서부경남지역을 대상으로 -", 주거환경, 13(2), pp.41~52 (2015), 한국주거환경학회
- Karl, A., "A practical guide to text mining with topic extraction", Wiley Interdisciplinary Reviews : Computational Statistics, 7(5), pp.326~340 (2015)
- Kelly, J., "Service Quality Variation Across Urban Space : First Steps Toward a Model of Citizen Satisfaction", Journal of Urban Affairs, 24(3), pp.271~288 (2002)
- 김은정, "읍·면 소재지 종합정비사업 평가지표 체계의 개선방안 -기존 소도읍 육성 사업의 평가지표 체계 분석을 바탕으로-", 한국농촌건축학회논문집, 14(1), pp.45~56 (2012), 한국농촌건축학회
- 김정연, "기초생활권 중심지 정비사업의 평가와 개선방안 - 일반농산어촌지역 읍(동)면소재지종합정비사업을 중심으로 -", 한국지역개발학회지, 25(4), pp.133~152 (2013), 한국지역개발학회
- 김지은, "텍스트 빅데이터 분석 기법을 활용한 대학구조개혁 평가의 쟁점 분석", 아시아교육연구, 17(3), pp.409~436 (2016), 교육연구소
- 김용진, "IPA를 활용한 농촌중심지 활성화 사업에 대한 거주민 인식 - 장수군 장계면을 중심으로 -", 농촌계획, 23(3), pp.133~145 (2017), 한국농촌계획학회[DOI]
- Ko, Y., "Typical Development Models for Revitalization of Rural Market Towns", Department of Bio Systems & Rural Engineering, pp.2009
- 이순배, "소도읍육성사업의 경제적 효과에 관한 비교분석", 한국지방자치연구, 13(1), pp.31~54 (2011), 대한지방자치학회
- 임창수, "농촌 거점면 중심지의 공간구조 특성 분석", 농촌계획, 15(3), pp.35~46 (2009), 한국농촌계획학회
- 임화진, "빅데이터를 이용한 지역미래전략 수립에 관한 시론적 연구- SNS 및 언론기사 분석을 통하여-", 한국지적정보학회지, 17(1), pp.75~90 (2015), 한국지적정보학회
- Lucas, C., "Computer-assisted text analysis for comparative politics", Political Analysis, 23(2), pp.254~277 (2015)
- A New Approach to Rural Development, "MAFRA", ~ (2016)
- A Plan to Develop General Farming and Fishing Villages in 2019, "MAFRA", ~ (2017)
- Big data:the next frontier for innovation, competition and productivity, "Manyika, J.", McKinsey Global Institute, ~ (2011)
- Matthies, B., "Computer-aided text analysis of corporate disclosures-demonstration and evaluation of two approaches", The International Journal of Digital Accounting Research, 15, pp.69~98 (2015)
- Moreno, A., "Text analytics : the convergence of big data and artificial intelligence", International Journal of Interactive Multimedia and Artificial Intelligence, 3(6), pp.57~64 (2015)
- Newman, M. E. J., "Fast algorithm for detecting community structure in networks", Phys. Rev, pp.E 69066133~ (2004)
- Niedomysl, T., "Is there hidden potential for rural population growth in sweden?", Rural Sociology, 76(2), pp.257~279 (2011)
- Oliver. P. E., "How events enter the public sphere : conflict, location, and sponsorship in local newspaper coverage of public events", Am J Sociol, 105(1), pp.38~87 (1999)
- 박경옥, "농촌활성화사업 마을주민의 사업참여도와 마을 환경변화에 대한 만족도", 한국농촌건축학회논문집, 11(1), pp.57~66 (2009), 한국농촌건축학회
- 박성진, "농촌지역 지속성을 위한 면소재지 활성화에 관한 연구 - 전라남도 내 면소재지의 주민 인식도 조사를 중심으로 -", 대한건축학회연합논문집, 16(5), pp.45~53 (2014), 대한건축학회지회연합회
- Paul, M., "Factorial LDA: Sparse multi-dimensional text models", Advances in Neural Information Processing Systems, pp.2582~2590 (2012)
- Ready, J., "Shock value : a comparative analysis of news reports and official police records on TASER deployments", Policing An Int J Police Strateg Manag, 32(1), pp.148~170 (2006)
- Shumueli, G., "Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner" (2010), Wiley &Sons
- Shmueli, G., "Predictive Analytics in Information Systems Research", MIS Quarterly, 35(3), pp.553~572 (2011)
- A Study on the Evaluation and Model of participatory Community Development project in Korea, "Song, M.", Korea Rural Economic Institute, ~ (2004)
- Steyvers, M., "Latent Semantic Analysis: A Road to Meaning", pp.427~448 (2007), Lawrence Erbaum Associates Publishers
- Visvaldis, V., "Selecting indicators for sustainable development of small towns : the case of Valmiera municipality", Procedia Computer Science, 26, pp.21~32 (2013)
- Wiedemann, G., "Opening up to big data:computer-assisted analysis of textual data in social science", Forum Qualitative Social Research, 14(2), pp.Art. 13~ (2013)
- Zhang, X. -P., "Topic model for chinese medicine diagnosis and prescription regularities analysis : case on diabetes", Chinese journal of integrative medicine, 17, pp.307~313 (2011)
