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  • × author_ss:"Peters, I."
  • × year_i:[2010 TO 2020}
  1. Peters, I.: Folksonomies : nutzergenerierte Schlagwörter als Indexierungswerkzeug für die Massen (2011) 0.02
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    Abstract
    Die große Fülle an nutzergeneriertem Content im Web 2.0 bedarf einer Strukturierung, will man diese Inhalte sinnvoll nutzen können. Im Internet hat sich mit den Folksonomies eigenständig eine Methode zur inhaltlichen Erschließung von digitalen Ressourcen etabliert. Die Verschlagwortung durch freie, von den Nutzern erstellte Tags zeigt viel Potential, birgt aber auch einige Risiken. Der Beitrag soll grundlegend in die Funktionsweise von Folksonomies einführen und dabei auch Vor- und Nachteile dieser Methode der Wissensrepräsentation ansprechen. Außerdem soll anhand von Beispielen kurz gezeigt werden, wie Folksonomies sinnvoll von Bibliotheken eingesetzt werden können.
    Content
    Inhalt 1. Zur Notwendigkeit der Inhaltserschließung im Web 2.0 2. Funktion und Nutzen von Folksonomies 3. Folksonomies in Bibliotheken 4. Danksagung
    Object
    Web 2.0
  2. Peters, I.: Folksonomies, social tagging and information retrieval (2011) 0.02
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    Abstract
    Services in Web 2.0 generate a large quantity of information, distributed over a range of resources (e.g. photos, URLs, videos) and integrated into different platforms (e.g. social bookmarking systems, sharing platforms (Peters, 2009). To adequately use this mass of information and to extract it from the platforms, users must be equipped with suitable tools and knowledge. After all, the best information is useless if users cannot find it: 'The model of information consumption relies on the information being found' (Vander Wal, 2004). In Web 2.0, the retrieval component has been established through so-called folksonomies (Vander Wal, 2005a), which are considered as several combinations of an information resource, one or more freely chosen keywords ('tags') and a user. Web 2.0 services that use folksonomies as an indexing and retrieval tool are defined as 'collaborative information services' because they allow for the collaborative creation of a public database that is accessible to all users (registered, where necessary) via the tags of the folksonomy (Ding et al., 2009; Heymann, Paepcke and Garcia-Molina, 2010).
    Object
    Web 2.0
  3. Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011) 0.02
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    Abstract
    Folksonomies ermöglichen den Nutzern in Kollaborativen Informationsdiensten den Zugang zu verschiedenartigen Informationsressourcen. In welchen Fällen beide Bestandteile des Web 2.0 am besten für das Information Retrieval geeignet sind und wo sie die Websuche ggf. ersetzen können, wird in diesem Beitrag diskutiert. Dazu erfolgt eine detaillierte Betrachtung der Reichweite von Social-Bookmarking-Systemen und Sharing-Systemen sowie der Retrievaleffektivität von Folksonomies innerhalb von Kollaborativen Informationsdiensten.
    Source
    Handbuch Internet-Suchmaschinen, 2: Neue Entwicklungen in der Web-Suche. Hrsg.: D. Lewandowski
  4. Peters, I.; Stock, W.G.: Power tags in information retrieval (2010) 0.01
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    Abstract
    Purpose - Many Web 2.0 services (including Library 2.0 catalogs) make use of folksonomies. The purpose of this paper is to cut off all tags in the long tail of a document-specific tag distribution. The remaining tags at the beginning of a tag distribution are considered power tags and form a new, additional search option in information retrieval systems. Design/methodology/approach - In a theoretical approach the paper discusses document-specific tag distributions (power law and inverse-logistic shape), the development of such distributions (Yule-Simon process and shuffling theory) and introduces search tags (besides the well-known index tags) as a possibility for generating tag distributions. Findings - Search tags are compatible with broad and narrow folksonomies and with all knowledge organization systems (e.g. classification systems and thesauri), while index tags are only applicable in broad folksonomies. Based on these findings, the paper presents a sketch of an algorithm for mining and processing power tags in information retrieval systems. Research limitations/implications - This conceptual approach is in need of empirical evaluation in a concrete retrieval system. Practical implications - Power tags are a new search option for retrieval systems to limit the amount of hits. Originality/value - The paper introduces power tags as a means for enhancing the precision of search results in information retrieval systems that apply folksonomies, e.g. catalogs in Library 2.0environments.
  5. Haustein, S.; Peters, I.; Sugimoto, C.R.; Thelwall, M.; Larivière, V.: Tweeting biomedicine : an analysis of tweets and citations in the biomedical literature (2014) 0.01
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    Abstract
    Data collected by social media platforms have been introduced as new sources for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation analysis. Data generated from social media activities can be used to reflect broad types of impact. This article aims to provide systematic evidence about how often Twitter is used to disseminate information about journal articles in the biomedical sciences. The analysis is based on 1.4 million documents covered by both PubMed and Web of Science and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed and compared to citations to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter and how far tweets correlate with citation impact. With less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general but differs between journals and specialties. Correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework using the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media-based metrics.