nep-ict New Economics Papers
on Information and Communication Technologies
Issue of 2011‒06‒18
three papers chosen by
Walter Frisch
University Vienna

  1. Surfing Alone? The Internet and Social Capital: Evidence from an Unforeseeable Technological Mistake By Bauernschuster, Stefan; Falck, Oliver; Woessmann, Ludger
  2. Electronic governance, premise for implementation of electronic democracy By Matei, Ani; Grigorovici, Iulia
  3. Machine Learning-Based Search for Similar Unstructured Text Entries Using Only a Few Positive Samples with Ranking by Similarity By Jan Žižka; František Dařena; Arnošt Svoboda

  1. By: Bauernschuster, Stefan (Ifo Institute for Economic Research); Falck, Oliver (Ifo Institute for Economic Research); Woessmann, Ludger (Ifo Institute for Economic Research)
    Abstract: Does the Internet undermine social capital or facilitate inter-personal and civic engagement in the real world? Merging unique telecommunication data with geo-coded German individual-level data, we investigate how broadband Internet affects several dimensions of social capital. One identification strategy uses panel information to estimate value-added models. A second exploits a quasi-experiment in East Germany created by a mistaken technology choice of the state-owned telecommunication provider in the 1990s that still hinders broadband Internet access for many households. We find no evidence that the Internet reduces social capital. For some measures including children's social activities, we even find significant positive effects.
    Keywords: social capital, Internet
    JEL: Z13 J24
    Date: 2011–05
  2. By: Matei, Ani; Grigorovici, Iulia
    Abstract: Living in a rapidly changing society, where information travels with great speed and its upgrade is essential, we decided to approach certain aspects of e-democracy, as a dynamic way of citizen participation, using new Information and Communications Technologies. The theme chosen for this research, Electronic governance, premise for implementation of electronic democracy, is a part of Electronic Administration field and identifies the meanings of implementing e-government and e-democracy, the necessity and effects of putting them into practice and the conditions to be fulfilled for the development of electronic services and fostering citizen participation in their use. E-governance as well as edemocracy have a clear contribution in making social progress, thanks to capitalize the most important irreversible resource, the time for achievement of the main administrative operations. The overall objective of the research aims to establish the relationship between governance and electronic democracy. From this perspective, this paper will contain: analyzing the importance of both e-governance and e-democracy, risks and benefits for each one, clarifying the need and implications underlying the implementation of electronic systems and explain the conditions to be met by citizens in order to benefit from these services. To achieve the objectives set, will be dominant the analyzing method of the social phenomena in their evolution. They will also combine harmoniously with practical examples in various member states of the European Union.
    Keywords: e-governance; e-democracy
    JEL: D73 L31 O32
    Date: 2011–05–05
  3. By: Jan Žižka (Department of Informatics, FBE MENDELU in Brno); František Dařena (Department of Informatics, FBE MENDELU in Brno); Arnošt Svoboda (Department of Applied Mathematics and Computer Science, Faculty of Economics and Administration, Masaryk university)
    Abstract: This research was inspired by the procedures that are used by human bibliographic searchers: Given some textual, only ‘positive’ (interesting) examples, coming from one category find the most similar ones that belong to a relevant topic. The problem of categorization of unlabeled relevant and irrelevant textual documents is here solved by using a small subset of relevant available patterns labeled manually. Unlabeled text items are compared with such labeled patterns. The unlabeled samples are then ranked according their degree of similarity with the patterns. At the top of the rank, there are the most similar (relevant) items. Entries receding from the rank top represent less and less similar entries. This simple method, aimed at processing large volumes of text entries, provides practically acceptable filtering results from the accuracy point of view and users can avoid the demanding task of labeling too many training examples to be able to apply a chosen classifier. The ranking-based approach provides results that can be further used for the following text-item processing where the number of irrelevant items is already not so high as it is usually typical for, for example, only the raw browsing results provided by Internet search engines. Even if this relatively simple automatic search is not errorless, it can help process particularly very large textual unstructured data volumes. Such an approach can help also in the economics area, for example, to automatically categorize written opinions of customers (as is collecting via the Internet), process network-based discussion groups, and so like.
    Keywords: unlabeled text documents, one-class categorization, text similarity, ranking by similarity, pattern recognition, machine learning, natural language processing
    JEL: C8
    Date: 2011–03

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