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iParticipate: Automatic Tweet Generation from Local Government Data

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Database Systems for Advanced Applications (DASFAA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7239))

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Abstract

With the recent rise of Open Government Data, innovative technologies are required to leverage this new wealth of information. Therefore, we present a system combining several information processing techniques with micro-blogging services to demonstrate how this data can be put to use in order to increase transparency in political processes, and encourage internet users to participate in local politics. Our system uses publicly available documents from city councils which are processed automtically to generate highly informative tweets.

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References

  1. Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., Nevill-Manning, C.G.: Domain-specific keyphrase extraction. In: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI 1999, pp. 668–673. Morgan Kaufmann Publishers Inc., San Francisco (1999)

    Google Scholar 

  2. George, J.M.: Can it help government to restore public trust?: Declining public trust and potential prospects of it in the public sector. In: Sprague, R. (ed.) Proceedings of the 36th Hawaii International Conference on Systems Sciences (HICSS 2003). IEEE Computer Society (2003)

    Google Scholar 

  3. Gibson, A.: Local by Social: How Local Authorities Can Use Social Media to Achieve More for Less. NESTA (2010)

    Google Scholar 

  4. Joachims, T.: Learning to Classify Text Using Support Vector Machines – Methods, Theory, and Algorithms. Kluwer/Springer (2002)

    Google Scholar 

  5. Mani, I.: Advances in Automatic Text Summarization. MIT Press, Cambridge (1999)

    Google Scholar 

  6. Parycek, P., Kripp, M.J., Edelmann, N. (eds.): CeDEM11 Proceedings of the International Conference for E-Democracy and Open Government. Edition Donau-Universität Krems (May 2011)

    Google Scholar 

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Author information

Authors and Affiliations

  1. IFIS, Carolo-Wilhelmina Universität Braunschweig, Germany

    Christoph Lofi

  2. L3S Research Center, Leibniz Universität Hannover, Germany

    Ralf Krestel

Authors
  1. Christoph Lofi
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  2. Ralf Krestel
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Editor information

Editors and Affiliations

  1. School of Computer Science and Engineering, Seoul National University, Gwanak-ro, Gwanak-gu, 151747, Seoul, South Korea

    Sang-goo Lee

  2. Computer School, Wuhan University, Luo-jia-shan, Wuchang, 430081, Wuhan, Hubei Province, China

    Zhiyong Peng

  3. School of Information Technology and Electrical Engineering, University of Queensland, 4072, Brisbane, QLD, Australia

    Xiaofang Zhou

  4. Department of Computer Science, Kangwon National University, 192-1, Hyoja2-Dong, 200701, Chuncheon, Kangwon, South Korea

    Yang-Sae Moon

  5. Institute for Computer Science and Business Information, University of Duisburg-Essen, Schützenbahn 70, 45117, Essen, Germany

    Rainer Unland

  6. School of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, 4072, Cheongju, Chungbuk, South Korea

    Jaesoo Yoo

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© 2012 Springer-Verlag Berlin Heidelberg

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Lofi, C., Krestel, R. (2012). iParticipate: Automatic Tweet Generation from Local Government Data. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_24

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  • DOI: https://doi.org/10.1007/978-3-642-29035-0_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29034-3

  • Online ISBN: 978-3-642-29035-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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