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Abstract

Social Tagging ist eine weitverbreitete Methode, um nutzergenerierte Inhalte in Webdiensten zu indexieren. Dieser Artikel fasst die aktuelle Forschung zu Folksonomies und Effektivität von Tags in Retrievalsystemen zusammen. Es wurde ein TREC-ähnlicher Retrievaltest mit Tags und Ressourcen aus dem Social Bookmarking-Dienst delicious durchgeführt, welcher in Recall- und Precisionwerten für ausschließlich Tag-basierte Suchen resultierte. Außerdem wurden Tags in verschiedenen Stufen bereinigt und auf ihre Retrieval-Effektivität getestet. Testergebnisse zeigen, dass Retrieval in Folksonomies am besten mit kurzen Anfragen funktioniert. Hierbei sind die Recallwerte hoch, die Precisionwerte jedoch eher niedrig. Die Suchfunktion "power tags only" liefert verbesserte Precisionwerte.

Theme

Social tagging

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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.

Theme

Social tagging

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Theme

Social tagging

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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.

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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).