Social tagging systems, known as ‘folksonomies’, represent an important part of web resource discovery as they enable free and unrestricted browsing through information space. Folksonomies consisting of subject designators (tags) assigned by users, however, have one important drawback: they do not express semantic relationships either hierarchical or associative between tags. As a consequence, the use of tags to browse information resources requires moving from one resource to another, based on coincidence and not on the pre-established meaningful or logical connections that may exist between related resources. We suggest that the semantic structure of the Universal Decimal Classification (UDC) may be used in complementing and supporting tag-based browsing. In this work, two specific questions were investigated: (1) Are terms used as tags in folksonomies included in the UDC? and (2) Which facets of UDC match the characteristics of documents or information objects that are tagged in folksonomies? A collection of the most popular tags from Amazon, LibraryThing, Delicious and 43Things was investigated. The universal nature of UDC was examined through the universality of topics and facets covering diverse human interests which are at the same time interconnected and form a rich and intricate semantic structure. The results suggest that UDC-supported folksonomies could be implemented in resource discovery, in particular in library portals and catalogues.

Im akademischen Bereich sind in Social-Software-Anwendungen wie Connotea, CiteULike und BibSonony umfangreiche Sammlungen von nutzergenerierten Metadaten entstanden. Im Vergleich zu kontrollierten Vokabularen, wie der Schlagwortnormdatei, handelt es sich dabei um personalisierte und in weiten Teilen „chaotische“ Inhaltserschließung. An der Universitätsbibliothek Mannheim wurde in einem DFG-Projekt untersucht, inwieweit das Potential dieser Art von Metadaten für eine bessere und nutzerorientierte Präsentation von Informationsressourcen eingesetzt werden kann. Ein Kernstück der Untersuchung war die Analyse von Tag-Daten des Systems BibSonomy. Es zeigte sich, dass nicht nur die mangelnde semantische Strukturiertheit der Tags, sondern auch ihre heterogene Gestalt einen limitierenden Faktor für die Verwendung in der bibliothekarischen Sacherschließung darstellt. Der Beitrag gibt anhand von Beispielen Einblick in das qualitative und strukturelle Chaos der untersuchten Tags und fasst die Ergebnisse des Projekts zusammen.

Tagging has become one of the key activities in next generation websites which allow users selecting short labels to annotate, manage, and share multimedia information such as photos, videos and bookmarks. Tagging does not require users any prior training before participating in the annotation activities as they can freely choose any terms which best represent the semantic of contents without worrying about any formal structure or ontology. However, the practice of free-form tagging can lead to several problems, such as synonymy, polysemy and ambiguity, which potentially increase the complexity of managing the tags and retrieving information. To solve these problems, this research aims to construct a lightweight indexing scheme to structure tags by identifying and disambiguating the meaning of terms and construct a knowledge base or dictionary. News has been chosen as the primary domain of application to demonstrate the benefits of using structured tags for managing the rapidly changing and dynamic nature of news information. One of the main outcomes of this work is an automatically constructed vocabulary that defines the meaning of each named entity tag, which can be extracted from a news article (including person, location and organisation), based on experts suggestions from major search engines and the knowledge from public database such as Wikipedia. To demonstrate the potential applications of the vocabulary, we have used it to provide more functionalities in an online news website, including topic-based news reading, intuitive tagging, clipping and sharing of interesting news, as well as news filtering or searching based on named entity tags. The evaluation results on the impact of disambiguating tags have shown that the vocabulary can help to significantly improve news searching performance. The preliminary results from our user study have demonstrated that users can benefit from the additional functionalities on the news websites as they are able to retrieve more relevant news, clip and share news with friends and families effectively.

Im akademischen Bereich sind in Social-Software-Anwendungen wie Connotea, CiteULike und BibSonony umfangreiche Sammlungen von nutzergenerierten Metadaten entstanden. Im Vergleich zu kontrollierten Vokabularen, wie der Schlagwortnormdatei, handelt es sich dabei um personalisierte und in weiten Teilen „chaotische“ Inhaltserschließung. An der Universitätsbibliothek Mannheim wurde in einem DFG-Projekt untersucht, inwieweit das Potential dieser Art von Metadaten für eine bessere und nutzerorientierte Präsentation von Informationsressourcen eingesetzt werden kann. Ein Kernstück der Untersuchung war die Analyse von Tag-Daten des Systems BibSonomy. Es zeigte sich, dass nicht nur die mangelnde semantische Strukturiertheit der Tags, sondern auch ihre heterogene Gestalt einen limitierenden Faktor für die Verwendung in der bibliothekarischen Sacherschließung darstellt. Der Beitrag gibt anhand von Beispielen Einblick in das qualitative und strukturelle Chaos der untersuchten Tags und fasst die Ergebnisse des Projekts zusammen.

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With the evolution of Web 2.0, most social-networking sites let their members participate in content generation. Users can label items with tags in these websites. A tag can be anything but it is actually a short description of the item. Because tags represent the reason why a user likes an item, but not how much user likes it / they are better identifiers of user profiles than ratings, which are usually numerical values assigned to items by users. Thus, the tag-based contextual representations of music tracks are concentrated in this study. Items are generally represented by vector space models in the content based recommendation systems. In tag-based recommendation systems, users and items are defined in terms of weighted vectors of social tags. When there is a large amount of tags, calculation of the items to be recommended becomes hard, because working with huge vectors is a time-consuming job. The main objective of this thesis is to represent individual tracks (songs) in lower dimensional spaces. An approach is described for creating music recommendations based on user-supplied tags that are augmented with a hierarchical structure extracted for top level genres from Dbpedia. In this structure, each genre is represented by its stylistic origins, typical instruments, derivative forms, sub genres and fusion genres. In addition to very large vector space models, insufficient number of user tags is another problem in the recommendation field. The proposed method is evaluated with different user profiling methods in case of any insufficiency in the number of user tags. User profiles are extended with multi-domain information. By using multi-domain information, the goal of making more successful and realistic predictions is achieved.

Die große Freiheit von Tagging-Systemen, wie sie zunehmend auch von wissenschaftlichen Bibliotheken eingesetzt werden, ist ein ambivalentes Phänomen. Zum einen bietet das „Tagging“ Kundennähe und beachtliches kreatives Potenzial, zum anderen erzeugt es jedoch große Mengen völlig unkontrollierter Meta- Informationen, über deren Qualität noch Unklarheit besteht. Die Universität Mannheim widmet sich in zwei kooperierenden DFG-Projekten dieser Problematik. Im Vortrag wurde die Implementierung eines Tagging-Systems im Online-Katalog sowie die Anwendung einer selbst entwickelten Opensource-Software zur Qualitätskontrolle von Klassifikationen und Tagging-Daten mittels innovativer Visualisierungstechnik und statistischer Methoden vorgestellt.

Organizations are attempting to leverage their knowledge resources by integrating knowledge sharing systems, a key and new form of which are social computing tools. A large number of these initiatives fail, however, due to employees' reluctance to use, contribute content to, and share knowledge through such tools. Although research regarding one's motivation to share knowledge is extensive, there has been little research examining social computing systems, especially from the seeking and contributory perspectives—the two distinct, but closely interrelated facets of knowledge sharing. Motivated by such concerns, and by incorporating knowledge-seeking and knowledge- contribution perspectives in a single study, this research develops and empirically examines a theoretical model to explain what motivates employees to seek, contribute and share social tags using Enterprise Social Tagging Tools (ESTTs). Two research phases were employed to address the research objective. The goal of the first phase of the study was to explore factors affecting users’ tagging behavior in online social tagging tools. An extensive literature review was synthesized and a preliminary theoretical model emerged. A pilot study was conducted yielding 184 responses featuring eight different online social tagging tools. Mostly, the preliminary theoretical model showed positive influence on users’ tag behavior with a special focus on the newly developed concepts of information retrievability, information refindability. The goal of the study’s second phase was combining the results from the first phase with motivational theories to build and validate a belief-based and socio-organizational model that can explain employees’ tag seeking, contributing, and sharing behavior in ESTTs. The model was developed by employing theories such as Theory of Reasoned Action (TRA), Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and social exchange theory. Through a large-scale survey (n=481) in two large Information Technology (IT) companies, the model was validated. The results speak to the importance of the three newly developed factors impacting employees’ tag seeking, contributing and sharing behavior. These factors are uniquely context-specific reflecting actual features of social tagging tools and potentially social media in general. Particularly, the results reveal that employees' tag seeking behavior is affected by their perception of the ESTTs in terms of enjoyment, information retrievability, ease of use, and managerial influence. In the context of tag contribution and sharing, the results show that employees contribute and share tags because of their perception of information refindability, ease of use, altruism, and pro-sharing norms. Differences among the seeking, contributing and sharing model have implications for future research and practice. / The thesis investigates employees' motivation to participate in enterprise social tagging tools. It describes and validates a conceputal model composed of three types of motivations: technical, social, and organizational.

Zugl.: Düsseldorf, Univ., Diss., 2008