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  • × theme_ss:"Social tagging"
  1. Peters, I.: Folksonomies : indexing and retrieval in Web 2.0 (2009) 0.02 
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    Abstract
    Kollaborative Informationsdienste im Web 2.0 werden von den Internetnutzern nicht nur dazu genutzt, digitale Informationsressourcen zu produzieren, sondern auch, um sie inhaltlich mit eigenen Schlagworten, sog. Tags, zu erschließen. Dabei müssen die Nutzer nicht wie bei Bibliothekskatalogen auf Regeln achten. Die Menge an nutzergenerierten Tags innerhalb eines Kollaborativen Informationsdienstes wird als Folksonomy bezeichnet. Die Folksonomies dienen den Nutzern zum Wiederauffinden eigener Ressourcen und für die Recherche nach fremden Ressourcen. Das Buch beschäftigt sich mit Kollaborativen Informationsdiensten, Folksonomies als Methode der Wissensrepräsentation und als Werkzeug des Information Retrievals.
    Footnote
    Zugl.: Düsseldorf, Univ., Diss., 2009 u.d.T.: Peters, Isabella: Folksonomies in Wissensrepräsentation und Information Retrieval Rez. in: IWP - Information Wissenschaft & Praxis, 61(2010) Heft 8, S.469-470 (U. Spree): "... Nachdem sich die Rezensentin durch 418 Seiten Text hindurch gelesen hat, bleibt sie unentschieden, wie der auffällige Einsatz langer Zitate (im Durchschnitt drei Zitate, die länger als vier kleingedruckte Zeilen sind, pro Seite) zu bewerten ist, zumal die Zitate nicht selten rein illustrativen Charakter haben bzw. Isabella Peters noch einmal zitiert, was sie bereits in eigenen Worten ausgedrückt hat. Redundanz und Verlängerung der Lesezeit halten sich hier die Waage mit der Möglichkeit, dass sich die Leserin einen unmittelbaren Eindruck von Sprache und Duktus der zitierten Literatur verschaffen kann. Eindeutig unschön ist das Beenden eines Gedankens oder einer Argumentation durch ein Zitat (z. B. S. 170). Im deutschen Original entstehen auf diese Weise die für deutsche wissenschaftliche Qualifikationsarbeiten typischen denglischen Texte. Für alle, die sich für Wissensrepräsentation, Information Retrieval und kollaborative Informationsdienste interessieren, ist "Folksonomies : Indexing and Retrieval in Web 2.0" trotz der angeführten kleinen Mängel zur Lektüre und Anschaffung - wegen seines beinahe enzyklopädischen Charakters auch als Nachschlage- oder Referenzwerk geeignet - unbedingt zu empfehlen. Abschließend möchte ich mich in einem Punkt der Produktinfo von de Gruyter uneingeschränkt anschließen: ein "Grundlagenwerk für Folksonomies".
    Weitere Rez. in: Library review 59(2010) no.7, S.566-568 (G. Macgregor)
    Object
    Web 2.0
    RSWK
    Information Retrieval
    World Wide Web 2.0
    Series
    Knowledge and information : studies in information science
    Subject
    Information Retrieval
    World Wide Web 2.0
  2. Heckner, M.: Tagging, rating, posting : studying forms of user contribution for web-based information management and information retrieval (2009) 0.02 
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    Abstract
    Die Entstehung von Social Software ermöglicht es Nutzern, in großem Umfang im Netz zu publizieren. Bisher liegen aber nur wenige empirische Befunde zu funktionalen Eigenschaften sowie Qualitätsaspekten von Nutzerbeiträgen im Kontext von Informationsmanagement und Information Retrieval vor. Diese Arbeit diskutiert grundlegende Partizipationsformen, präsentiert empirische Studien über Social Tagging, Blogbeiträge sowie Relevanzbeurteilungen und entwickelt Design und Implementierung einer "sozialen" Informationsarchitektur für ein partizipatives Onlinehilfesystem.
    Content
    The Web of User Contribution - Foundations and Principles of the Social Web - Social Tagging - Rating and Filtering of Digital Resources Empirical Analysisof User Contributions - The Functional and Linguistic Structure of Tags - A Comparative Analysis of Tags for Different Digital Resource Types - Exploring Relevance Assessments in Social IR Systems - Exploring User Contribution Within a Higher Education Scenario - Summary of Empirical Results and Implications for Designing Social Information Systems User Contribution for a Participative Information System - Social Information Architecture for an Online Help System
    Object
    Web 2.0
    RSWK
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
    Social Tagging / Filter / Web log / World Wide Web 2.0
    Subject
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
    Social Tagging / Filter / Web log / World Wide Web 2.0
  3. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.02 
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    Abstract
    Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative search. We propose a ranking model for each task that integrates the individual user's tagging history in the recommendation of tags and content, to align its suggestions to the individual user preferences. We demonstrate on two real data sets that for all three tasks, the personalized ranking should take into account both the user's own preference and the opinion of others.
    Source
    Information processing and management. 46(2010) no.1, S.58-70
    Year
    2010
  4. Voß, J.: Vom Social Tagging zum Semantic Tagging (2008) 0.01 
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    Abstract
    Social Tagging als freie Verschlagwortung durch Nutzer im Web wird immer häufiger mit der Idee des Semantic Web in Zusammenhang gebracht. Wie beide Konzepte in der Praxis konkret zusammenkommen sollen, bleibt jedoch meist unklar. Dieser Artikel soll hier Aufklärung leisten, indem die Kombination von Social Tagging und Semantic Web in Form von Semantic Tagging mit dem Simple Knowledge Organisation System dargestellt und auf die konkreten Möglichkeiten, Vorteile und offenen Fragen der Semantischen Indexierung eingegangen wird.
    Theme
    Semantic Web
  5. Huang, C.; Fu, T.; Chen, H.: Text-based video content classification for online video-sharing sites (2010) 0.01 
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    Abstract
    With the emergence of Web 2.0, sharing personal content, communicating ideas, and interacting with other online users in Web 2.0 communities have become daily routines for online users. User-generated data from Web 2.0 sites provide rich personal information (e.g., personal preferences and interests) and can be utilized to obtain insight about cyber communities and their social networks. Many studies have focused on leveraging user-generated information to analyze blogs and forums, but few studies have applied this approach to video-sharing Web sites. In this study, we propose a text-based framework for video content classification of online-video sharing Web sites. Different types of user-generated data (e.g., titles, descriptions, and comments) were used as proxies for online videos, and three types of text features (lexical, syntactic, and content-specific features) were extracted. Three feature-based classification techniques (C4.5, Naïve Bayes, and Support Vector Machine) were used to classify videos. To evaluate the proposed framework, user-generated data from candidate videos, which were identified by searching user-given keywords on YouTube, were first collected. Then, a subset of the collected data was randomly selected and manually tagged by users as our experiment data. The experimental results showed that the proposed approach was able to classify online videos based on users' interests with accuracy rates up to 87.2%, and all three types of text features contributed to discriminating videos. Support Vector Machine outperformed C4.5 and Naïve Bayes techniques in our experiments. In addition, our case study further demonstrated that accurate video-classification results are very useful for identifying implicit cyber communities on video-sharing Web sites.
    Object
    Web 2.0
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.891-906
    Year
    2010
  6. Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011) 0.01 
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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
  7. Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011) 0.01 
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    Abstract
    As the web has grown into an integral part of daily life, social annotation has become a popular manner for web users to manage resources. This method of management has many potential applications, but it is limited in applicability by the cold-start problem, especially for new resources on the web. In this article, we study automatic tag prediction for web pages comprehensively and utilize the predicted tags to improve search performance. First, we explore the stabilizing phenomenon of tag usage in a social bookmarking system. Then, we propose a two-stage tag prediction approach, which is efficient and is effective in making use of early annotations from users. In the first stage, content-based ranking, candidate tags are selected and ranked to generate an initial tag list. In the second stage, random-walk re-ranking, we adopt a random-walk model that utilizes tag co-occurrence information to re-rank the initial list. The experimental results show that our algorithm effectively proposes appropriate tags for target web pages. In addition, we present a framework to incorporate tag prediction in a general web search. The experimental results of the web search validate the hypothesis that the proposed framework significantly enhances the typical retrieval model.
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.8, S.1473-1487
  8. Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010) 0.01 
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    Abstract
    Data integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.505-521
    Year
    2010
  9. Good tags - bad tags : Social Tagging in der Wissensorganisation (2008) 0.01 
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    Abstract
    Teile und sammle könnte der moderne Leitspruch für das Phänomen Social Tagging heißen. Die freie und kollaborative Verschlagwortung digitaler Ressourcen im Internet gehört zu den Anwendungen aus dem Kontext von Web 2.0, die sich zunehmender Beliebtheit erfreuen. Der 2003 gegründete Social Bookmarking Dienst Del.icio.us und die 2004 entstandene Bildersammlung Flickr waren erste Anwendungen, die Social Tagging anboten und noch immer einen Großteil der Nutzer/innen an sich binden. Beim Blick in die Literatur wird schnell deutlich, dass Social Tagging polarisiert: Von Befürwortern wird es als eine Form der innovativen Wissensorganisation gefeiert, während Skeptiker die Dienste des Web 2.0 inklusive Social Tagging als globale kulturelle Bedrohung verdammen. Launischer Hype oder Quantensprung was ist dran am Social Tagging? Mit der Zielsetzung, mehr über die Erwartungen, Anwendungsbereiche und Nutzungsweisen zu erfahren, wurde im Frühjahr 2008 am Institut für Wissensmedien (IWM) in Tübingen ein Workshop der Gesellschaft für Medien in der Wissenschaft (GMW) durchgeführt. Die vorliegende Publikation fasst die Ergebnisse der interdisziplinären Veranstaltung zusammen.
    Content
    - Tagging im Semantic Web Benjamin Birkenhake: Semantic Weblog. Erfahrungen vom Bloggen mit Tags und Ontologien Simone Braun, Andreas Schmidt, Andreas Walter & Valentin Zacharias: Von Tags zu semantischen Beziehungen: kollaborative Ontologiereifung Jakob Voß: Vom Social Tagging zum Semantic Tagging Georg Güntner, Rolf Sint & Rupert Westenthaler: Ein Ansatz zur Unterstützung traditioneller Klassifikation durch Social Tagging Viktoria Pammer, Tobias Ley & Stefanie Lindstaedt: tagr: Unterstützung in kollaborativen Tagging-Umgebungen durch Semantische und Assoziative Netzwerke Matthias Quasthoff Harald Sack & Christoph Meinet: Nutzerfreundliche Internet-Sicherheit durch tag-basierte Zugriffskontrolle
    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. . . .
  10. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.01 
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    Abstract
    A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.
    Date
    25.12.2012 15:22:37
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2488-2502
  11. Hänger, C.; Krätzsch, C.; Niemann, C.: Was vom Tagging übrig blieb : Erkenntnisse und Einsichten aus zwei Jahren Projektarbeit (2011) 0.01 
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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.
    Object
    Web 2.0
  12. Aparecida Moura, M.; Assis, J.: Social networks, indexing languages and organization of knowledge : a semiotic approach 0.01 
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    Abstract
    This study will present a theoretical discussion about the semiotics categories and its application in the information organization. An experiment about the performance of the Gemet and Eurovoc thesauri with the subject "sustainable development" comparing with the folksonomies and distributed classification systems available on the online repositories of individual or collective information is presented. The new configuration of warrant (literary, structural and of usage) in the process of constructing indexing languages in digital environments will also be discussed. It suggested in the methodological terms that the new theoretical and informational mediations have to be incorporated in the construction process of indexing languages.
    Source
    Paradigms and conceptual systems in knowledge organization: Proceedings of the Eleventh International ISKO conference, Rome, 23-26 February 2010, ed. Claudio Gnoli, Indeks, Frankfurt M
  13. Danowski, P.: Authority files and Web 2.0 : Wikipedia and the PND. An Example (2007) 0.01 
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    Abstract
    More and more users index everything on their own in the web 2.0. There are services for links, videos, pictures, books, encyclopaedic articles and scientific articles. All these services are library independent. But must that really be? Can't libraries help with their experience and tools to make user indexing better? On the experience of a project from German language Wikipedia together with the German person authority files (Personen Namen Datei - PND) located at German National Library (Deutsche Nationalbibliothek) I would like to show what is possible. How users can and will use the authority files, if we let them. We will take a look how the project worked and what we can learn for future projects. Conclusions - Authority files can have a role in the web 2.0 - there must be an open interface/ service for retrieval - everything that is indexed on the net with authority files can be easy integrated in a federated search - O'Reilly: You have to found ways that your data get more important that more it will be used
    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
    Object
    Web 2.0
  14. Vaidya, P.; Harinarayana, N.S.: ¬The comparative and analytical study of LibraryThing tags with Library of Congress Subject Headings (2016) 0.01 
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    Abstract
    The internet in its Web 2.0 version has given an opportunity among users to be participative and the chance to enhance the existing system, which makes it dynamic and collaborative. The activity of social tagging among researchers to organize the digital resources is an interesting study among information professionals. The one way of organizing the resources for future retrieval through these user-generated terms makes an interesting analysis by comparing them with professionally created controlled vocabularies. Here in this study, an attempt has been made to compare Library of Congress Subject Headings (LCSH) terms with LibraryThing social tags. In this comparative analysis, the results show that social tags can be used to enhance the metadata for information retrieval. But still, the uncontrolled nature of social tags is a concern and creates uncertainty among researchers.
  15. Rorissa, A.: ¬A comparative study of Flickr tags and index terms in a general image collection (2010) 0.01 
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    Abstract
    Web 2.0 and social/collaborative tagging have altered the traditional roles of indexer and user. Traditional indexing tools and systems assume the top-down approach to indexing in which a trained professional is responsible for assigning index terms to information sources with a potential user in mind. However, in today's Web, end users create, organize, index, and search for images and other information sources through social tagging and other collaborative activities. One of the impediments to user-centered indexing had been the cost of soliciting user-generated index terms or tags. Social tagging of images such as those on Flickr, an online photo management and sharing application, presents an opportunity that can be seized by designers of indexing tools and systems to bridge the semantic gap between indexer terms and user vocabularies. Empirical research on the differences and similarities between user-generated tags and index terms based on controlled vocabularies has the potential to inform future design of image indexing tools and systems. Toward this end, a random sample of Flickr images and the tags assigned to them were content analyzed and compared with another sample of index terms from a general image collection using established frameworks for image attributes and contents. The results show that there is a fundamental difference between the types of tags and types of index terms used. In light of this, implications for research into and design of user-centered image indexing tools and systems are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.11, S.2230-2242
    Year
    2010
  16. Bentley, C.M.; Labelle, P.R.: ¬A comparison of social tagging designs and user participation (2008) 0.01 
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    Abstract
    Social tagging empowers users to categorize content in a personally meaningful way while harnessing their potential to contribute to a collaborative construction of knowledge (Vander Wal, 2007). In addition, social tagging systems offer innovative filtering mechanisms that facilitate resource discovery and browsing (Mathes, 2004). As a result, social tags may support online communication, informal or intended learning as well as the development of online communities. The purpose of this mixed methods study is to examine how undergraduate students participate in social tagging activities in order to learn about their motivations, behaviours and practices. A better understanding of their knowledge, habits and interactions with such systems will help practitioners and developers identify important factors when designing enhancements. In the first phase of the study, students enrolled at a Canadian university completed 103 questionnaires. Quantitative results focusing on general familiarity with social tagging, frequently used Web 2.0 sites, and the purpose for engaging in social tagging activities were compiled. Eight questionnaire respondents participated in follow-up semi-structured interviews that further explored tagging practices by situating questionnaire responses within concrete experiences using popular websites such as YouTube, Facebook, Del.icio.us, and Flickr. Preliminary results of this study echo findings found in the growing literature concerning social tagging from the fields of computer science (Sen et al., 2006) and information science (Golder & Huberman, 2006; Macgregor & McCulloch, 2006). Generally, two classes of social taggers emerge: those who focus on tagging for individual purposes, and those who view tagging as a way to share or communicate meaning to others. Heavy del.icio.us users, for example, were often focused on simply organizing their own content, and seemed to be conscientiously maintaining their own personally relevant categorizations while, in many cases, placing little importance on the tags of others. Conversely, users tagging items primarily to share content preferred to use specific terms to optimize retrieval and discovery by others. Our findings should inform practitioners of how interaction design can be tailored for different tagging systems applications, and how these findings are positioned within the current debate surrounding social tagging among the resource discovery community. We also hope to direct future research in the field to place a greater importance on exploring the benefits of tagging as a socially-driven endeavour rather than uniquely as a means of managing information.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  17. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.01 
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    Abstract
    Social tagging or collaborative tagging has become a new trend in the organization, management, and discovery of digital information. The rapid growth of shared information mostly controlled by social tags poses a new challenge for social tag-based information organization and retrieval. A plausible approach for this challenge is linking social tags to a controlled vocabulary. As an introductory step for this approach, this study investigates ways of predicting relevant subject headings for resources from social tags assigned to the resources. The prediction of subject headings was measured by five different similarity measures: tf-idf, cosine-based similarity (CoS), Jaccard similarity (or Jaccard coefficient; JS), Mutual information (MI), and information radius (IRad). Their results were compared to those by professionals. The results show that a CoS measure based on top five social tags was most effective. Inclusions of more social tags only aggravate the performance. The performance of JS is comparable to the performance of CoS while tf-idf is comparable with up to 70% less than the best performance. MI and IRad have inferior performance compared to the other methods. This study demonstrates the application of the similarity measuring techniques to the prediction of correct Library of Congress subject headings.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1658-1672
    Year
    2010
  18. Weiand, K.; Hartl, A.; Hausmann, S.; Furche, T.; Bry, F.: Keyword-based search over semantic data (2012) 0.01 
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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.
    Source
    Semantic search over the Web. Eds.: R. De Virgilio, et al
    Theme
    Semantic Web
  19. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.01 
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    Abstract
    Libraries are the tools we use to learn and to answer our questions. The quality of our work depends, among others, on the quality of the tools we use. Recent research in digital libraries is focused, on one hand on improving the infrastructure of the digital library management systems (DLMS), and on the other on improving the metadata models used to annotate collections of objects maintained by DLMS. The latter includes, among others, the semantic web and social networking technologies. Recently, the semantic web and social networking technologies are being introduced to the digital libraries domain. The expected outcome is that the overall quality of information discovery in digital libraries can be improved by employing social and semantic technologies. In this chapter we present the results of an evaluation of social and semantic end-user information discovery services for the digital libraries.
    Date
    1. 8.2010 12:35:22
  20. Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011) 0.01 
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    Abstract
    Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.12, S.2364-2381

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