Semantic search for public opinions on urban affairs: A probabilistic topic modeling-based approach |
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| Institution: | 1. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, PR China;2. School of Public Policy and Management, Tsinghua University, Beijing 100084, PR China;3. School of Economics and Management, Tsinghua University, Beijing 100084, PR China;4. School of Management and Economics, University of Electronic Science and Technology of China, Chengdu 611731, PR China;1. Polytechnic Institute of Tomar, Tomar, Portugal;2. LIAAD/INESC TEC – INESC Technology and Science, Portugal\n;3. DCC – FCUP, University of Porto, Portugal;4. HULTECH/GREYC, University of Caen Basse-Normandie, Caen, France;5. Department of Mathematics, University of Beira Interior, Covilhã, Portugal;6. Center of Mathematics, University of Beira Interior, Covilhã, Portugal;1. Université de Toulouse, Laboratoire de Génie de Production (LGP), EA 1905, ENIT-INPT, 47 Avenue d’Azereix, BP 1629, Tarbes Cedex 65016, France;2. Université de Toulouse, Faculté de droit, 2 rue du Doyen Gabriel Marty, Toulouse cedex 9 31042, France;1. School of Electrical and Computer Engineering, College of Engineering, University of Tehran, P.O. Box 14395-515 Tehran, Iran;2. School of Computer Science, Institute for Research in Fundamental Sciences (IPM), P.O. Box 19395-5746 Tehran, Iran;3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong |
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| Abstract: | The explosion of online user-generated content (UGC) and the development of big data analysis provide a new opportunity and challenge to understand and respond to public opinions in the G2C e-government context. To better understand semantic searching of public comments on an online platform for citizens’ opinions about urban affairs issues, this paper proposed an approach based on the latent Dirichlet allocation (LDA), a probabilistic topic modeling method, and designed a practical system to provide users—municipal administrators of B-city—with satisfying searching results and the longitudinal changing curves of related topics. The system is developed to respond to actual demand from B-city's local government, and the user evaluation experiment results show that a system based on the LDA method could provide information that is more helpful to relevant staff members. Municipal administrators could better understand citizens’ online comments based on the proposed semantic search approach and could improve their decision-making process by considering public opinions. |
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