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Abstract

For a long while, the creation of Web content required at least basic knowledge of Web technologies, meaning that for many Web users, the Web was de facto a read-only medium. This changed with the arrival of the "social Web," when Web applications started to allow users to publish Web content without technological expertise. Here, content creation is often an inclusive, iterative, and interactive process. Examples of social Web applications include blogs, social networking sites, as well as many specialized applications, for example, for saving and sharing bookmarks and publishing photos. Social semantic Web applications are social Web applications in which knowledge is expressed not only in the form of text and multimedia but also through informal to formal annotations that describe, reflect, and enhance the content. These annotations often take the shape of RDF graphs backed by ontologies, but less formal annotations such as free-form tags or tags from a controlled vocabulary may also be available. Wikis are one example of social Web applications for collecting and sharing knowledge. They allow users to easily create and edit documents, so-called wiki pages, using a Web browser. The pages in a wiki are often heavily interlinked, which makes it easy to find related information and browse the content.

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Source

Journal of the American Society for Information Science and Technology. 64(2013) no.5, S.964-980

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Source

Journal of the Association for Information Science and Technology. 68(2017) no.2, S.348-364

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Abstract

Therefore our main research questions are as follows: - Is it possible to discover regular patterns in tag usage and to establish a stable category model? - Does a specific tagging language comparable to internet slang or chatspeak evolve? - How do social tags differ from traditional (author / expert) keywords? - To what degree are social tags taken from or findable in the full text of the tagged resource? - Do tags in a research literature context go beyond simple content description (e.g. tags indicating time or task-related information, cf. Kipp et al. 2006)?

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Abstract

Many libraries and other cultural institutions are incorporating Web 2.0 features and enhanced metadata into their catalogs (Trant 2006). These value-added elements include those typically found in commercial and social networking sites, such as book jacket images, reviews, and usergenerated tags. One such site that libraries are exploring as a model is LibraryThing (www.librarything.com) LibraryThing is a social networking site that allows users to "catalog" their own book collections. Members can add tags and reviews to records for books, as well as engage in online discussions. In addition to its service for individuals, LibraryThing offers a feebased service to libraries, where institutions can add LibraryThing tags, recommendations, and other features to their online catalog records. This poster will present data analyzing the quality and quantity of the metadata that a large academic library would expect to gain if utilizing such a service, focusing on the overlap between titles found in the library's catalog and in LibraryThing's database, and on a comparison between the controlled subject headings in the former and the user-generated tags in the latter. During February through April 2008, a random sample of 383 titles from the University of Minnesota Libraries catalog was searched in LibraryThing. Eighty works, or 21 percent of the sample, had corresponding records available in LibraryThing. Golder and Huberman (2006) outline the advantages and disadvantages of using controlled vocabulary for subject access to information resources versus the growing trend of tags supplied by users or by content creators. Using the 80 matched records from the sample, comparisons were made between the user-supplied tags in LibraryThing (social tags) and the subject headings in the library catalog records (controlled vocabulary system). In the library records, terms from all 6XX MARC fields were used. To make a more meaningful comparison, controlled subject terms were broken down into facets according to their headings and subheadings, and each unique facet counted separately. A total of 227 subject terms were applied to the 80 catalog records, an average of 2.84 per record. In LibraryThing, 698 tags were applied to the same 80 titles, an average of 8.73 per title. The poster will further explore the relationships between the terms applied in each source, and identify where overlaps and complementary levels of access occur.

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Footnote

Enthält die Beiträge der Tagung "Social Tagging in der Wissensorganisation" am 21.-22.02.2008 am Institut für Wissensmedien (IWM) in Tübingen. Volltext unter: http://www.waxmann.com/kat/inhalt/2039Volltext.pdf. Vgl. die Rez. unter: http://sehepunkte.de/2008/11/14934.html. Rez. in: IWP 60(1009) H.4, S.246-247 (C. Wolff): "Tagging-Systeme erfreuen sich in den letzten Jahren einer ungemein großen Beliebtheit, erlauben sie dem Nutzer doch die Informationserschließung "mit eigenen Worten", also ohne Rekurs auf vorgegebene Ordnungs- und Begriffsysteme und für Medien wie Bild und Video, für die herkömmliche Verfahren des Information Retrieval (noch) versagen. Die Beherrschung der Film- und Bilderfülle, wie wir sie bei Flickr oder YouTube vorfinden, ist mit anderen Mitteln als dem intellektuellen Einsatz der Nutzer nicht vorstellbar - eine professionelle Aufbereitung angesichts der Massendaten (und ihrer zu einem großen Teil auch minderen Qualität) nicht möglich und sinnvoll. Insofern hat sich Tagging als ein probates Mittel der Erschließung herausgebildet, das dort Lücken füllen kann, wo andere Verfahren (Erschließung durch information professionals, automatische Indexierung, Erschließung durch Autoren) fehlen oder nicht anwendbar sind. Unter dem Titel "Good Tags - Bad Tags. Social Tagging in der Wissensorganisation" und der Herausgeberschaft von Birgit Gaiser, Thorsten Hampel und Stefanie Panke sind in der Reihe Medien in der Wissenschaft (Bd. 47) Beiträge eines interdisziplinären Workshops der Gesellschaft für Medien in der Wissenschaft zum Thema Tagging versammelt, der im Frühjahr 2008 am Institut für Wissensmedien in Tübingen stattgefunden hat. . . .

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Abstract

A number of such utilities are presented here, together with an emergent new class of tools that caters more to the academic communities and that stores not only user-supplied tags, but also structured citation metadata terms wherever it is possible to glean this information from service providers. This provision of rich, structured metadata means that the user is provided with an accurate third-party identification of a document, which could be used to retrieve that document, but is also free to search on user-supplied terms so that documents of interest (or rather, references to documents) can be made discoverable and aggregated with other similar descriptions either recorded by the user or by other users. Matt Biddulph in an XML.com article last year, in which he reviews one of the better known social bookmarking tools, del.icio.us, declares that the "del.icio.us-space has three major axes: users, tags, and URLs". We fully support that assessment but choose to present this deconstruction in a reverse order. This paper thus first recaps a brief history of bookmarks, then discusses the current interest in tagging, moves on to look at certain social issues, and finally considers some of the feature sets offered by the new bookmarking tools. A general review of a number of common social bookmarking tools is presented in the annex. A companion paper describes a case study in more detail: the tool that Nature Publishing Group has made available to the scientific community as an experimental entrée into this field - Connotea; our reasons for endeavouring to provide such a utility; and experiences gained and lessons learned.

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Abstract

Das DFG-Projekt "Collaborative Tagging als neue Form der Sacherschließung" Im Oktober 2008 startete an der Universitätsbibliothek Mannheim das DFG-Projekt "Collaborative Tagging als neue Form der Sacherschließung". Über zwei Jahre hinweg wurde untersucht, welchen Beitrag das Web-2.0-Phänomen Tagging für die inhaltliche Erschließung von bisher nicht erschlossenen und somit der Nutzung kaum zugänglichen Dokumenten leisten kann. Die freie Vergabe von Schlagwörtern in Datenbanken durch die Nutzer selbst hatte sich bereits auf vielen Plattformen als äußerst effizient herausgestellt, insbesondere bei Inhalten, die einer automatischen Erschließung nicht zugänglich sind. So wurden riesige Mengen von Bildern (FlickR), Filmen (YouTube) oder Musik (LastFM) durch das Tagging recherchierbar und identifizierbar gemacht. Die Fragestellung des Projektes war entsprechend, ob und in welcher Qualität sich durch das gleiche Verfahren beispielsweise Dokumente auf Volltextservern oder in elektronischen Zeitschriften erschließen lassen. Für die Beantwortung dieser Frage, die ggf. weitreichende Konsequenzen für die Sacherschließung durch Fachreferenten haben konnte, wurde ein ganzer Komplex von Teilfragen und Teilschritten ermittelt bzw. konzipiert. Im Kern ging es aber in allen Untersuchungsschritten immer um zwei zentrale Dimensionen, nämlich um die "Akzeptanz" und um die "Qualität" des Taggings. Die Akzeptanz des Taggings wurde zunächst bei den Studierenden und Wissenschaftlern der Universität Mannheim evaluiert. Für bestimmte Zeiträume wurden Tagging-Systeme in unterschiedlichen Ausprägungen an die Recherchedienste der Universitätsbibliothek angebunden. Die Akzeptanz der einzelnen Systemausprägungen konnte dann durch die Analyse von Logfiles und durch Datenbankabfragen ausgewertet werden. Für die Qualität der Erschließung wurde auf einen Methodenmix zurückgegriffen, der im Verlauf des Projektes immer wieder an aktuelle Entwicklungen und an die Ergebnisse aus den vorangegangenen Analysen angepaßt wurde. Die Tags wurden hinsichtlich ihres Beitrags zum Information Retrieval mit Verfahren der automatischen Indexierung von Volltexten sowie mit der Erschließung durch Fachreferenten verglichen. Am Schluss sollte eine gut begründete Empfehlung stehen, wie bisher nicht erschlossene Dokumente am besten indexiert werden können: automatisch, mit Tags oder durch eine Kombination von beiden Verfahren.