Search (142 results, page 2 of 8)

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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

Type

a

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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.

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

Type

a

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Abstract

My keynote at the workshop "Social Tagging in Knowledge Organization" was a great opportunity to make and share new experiences. For the first time ever, I sat in my office at home and gave a live web video presentation to a conference audience elsewhere on the globe. At the same time, it was also an opportunity to premier my conceptual model "Matrix of Perception" to an interdisciplinary audience of researchers and practitioners with a variety of backgrounds - reaching from philosophy, psychology, pedagogy and computation to library science and economics. The interdisciplinary approach of the conference is also mirrored in the structure of this volume, with articles on the theoretical background, the empirical analysis and the potential applications of tagging, for instance in university libraries, e-learning, or e-commerce. As an introduction to the topic of "social tagging" I would like to draw your attention to some foundation concepts of the phenomenon I have racked my brain with for the last few month. One thing I have seen missing in recent research and system development is a focus on the variety of user perspectives in social tagging. Different people perceive tagging in complex variegated ways and use this form of knowledge organization for a variety of purposes. My analytical interest lies in understanding the personas and patterns in tagging systems and in being able to label their different perceptions. To come up with a concise picture of user expectations, needs and activities, I have broken down the perspectives on tagging into two different categories, namely "faces" and "depth". When put together, they form the "Matrix of Perception" - a nuanced view of stakeholders and their respective levels of participation.

Date

22. 6.2009 9:15:45

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a

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Content

- Theoretische Ansätze und empirische Untersuchungen Stefanie Panke & Birgit Gaiser: "With my head up in the clouds" - Social Tagging aus Nutzersicht Christoph Held& Ulrike Cress: Social Tagging aus kognitionspsychologischer Sicht Michael Derntl, Thorsten Hampel, Renate Motschnig & Tomas Pitner: Social Tagging und Inclusive Universal Access - Einsatz von Tagging in Hochschulen und Bibliotheken Christian Hänger: Good tags or bad tags? Tagging im Kontext der bibliothekarischen Sacherschließung Mandy Schiefner: Social Tagging in der universitären Lehre Michael Blank, Thomas Bopp, Thorsten Hampel & Jonas Schulte: Social Tagging = Soziale Suche? Andreas Harrer & Steffen Lohmann: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse Harald Sack & Jörg Waitelonis: Zeitbezogene kollaborative Annotation zur Verbesserung der inhaltsbasierten Videosuche - Kommerzielle Anwendungen von Tagging Karl Tschetschonig, Roland Ladengruber, Thorsten Hampel & Jonas Schulte: Kollaborative Tagging-Systeme im Electronic Commerce Tilman Küchler, Jan M. Pawlowski & Volker Zimmermann: Social Tagging and Open Content: A Concept for the Future of E-Learning and Knowledge Management? Stephan Schillenvein: Der .Business Case' für die Nutzung von Social Tagging in Intranets und internen Informationssystemen

Footnote

Kommentar M. Buzinkay: "Bibliotheken werden um Social Tagging nicht herum kommen, da schlichtweg die Kapazitäten für eine inhaltliche Erschließung fehlen. Stattdessen wäre es von Notwendigkeit, Normdateien zum Bestandteil des Tagging zu machen. Verfehlt wäre es, auf die bibliothekarische Erschließung zu verzichten, weil das zu Lasten des Verhältnisses von Recall und Precision gehen würde." (In: http://www.buzinkay.net/blog-de/2009/05/buchrezension-good-tags-bad-tags/)

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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".

Imprint

Berlin : de Gruyter, Saur

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Abstract

The goal of the study presented in this article is to investigate to what extent the classification of a web page by a single genre matches the users' perspective. The extent of agreement on a single genre label for a web page can help understand whether there is a need for a different classification scheme that overrides the single-genre labelling. My hypothesis is that a single genre label does not account for the users' perspective. In order to test this hypothesis, I submitted a restricted number of web pages (25 web pages) to a large number of web users (135 subjects) asking them to assign only a single genre label to each of the web pages. Users could choose from a list of 21 genre labels, or select one of the two 'escape' options, i.e. 'Add a label' and 'I don't know'. The rationale was to observe the level of agreement on a single genre label per web page, and draw some conclusions about the appropriateness of limiting the assignment to only a single label when doing genre classification of web pages. Results show that users largely disagree on the label to be assigned to a web page.

Type

a

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Abstract

Taxonomy construction is a resource-demanding, top-down, and time consuming effort. It does not always cater for the prevailing context of the captured information. This paper proposes a novel approach to automatically convert tags into a hierarchical taxonomy. Folksonomy describes the process by which many users add metadata in the form of keywords or tags to shared content. Using folksonomy as a knowledge source for nominating tags, the proposed method first converts the tags into a hierarchy. This serves to harness a core set of taxonomy terms; the generated hierarchical structure facilitates users' information navigation behavior and permits personalizations. Newly acquired tags are then progressively integrated into a taxonomy in a largely automated way to complete the taxonomy creation process. Common taxonomy construction techniques are based on 3 main approaches: clustering, lexico-syntactic pattern matching, and automatic acquisition from machine-readable dictionaries. In contrast to these prevailing approaches, this paper proposes a taxonomy construction analysis based on heuristic rules and deep syntactic analysis. The proposed method requires only a relatively small corpus to create a preliminary taxonomy. The approach has been evaluated using an expert-defined taxonomy in the environmental protection domain and encouraging results were yielded.

Type

a

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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).

Type

a

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Content

This paper outlines a formal and systematic approach to explication of the role of structure in information organization. It presents a preliminary set of constructs that are useful for understanding the similarities and differences that obtain across information organization systems. This work seeks to provide necessary groundwork for development of a theory of structure that can serve as a lens through which to observe patterns across systems of information organization.

Type

a

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Abstract

There are close to a billion websites on the Internet with approximately 400 million users worldwide [www.internetworldstats.com]. People go to websites for a wide variety of different information tasks, from finding a restaurant to serious research. Many of the difficulties with searching the Web, as it is structured currently, can be attributed to increases to scale. The content of the Web is now so large that we only have a rough estimate of the number of sites and the range of information is extremely diverse, from blogs and photos to research articles and news videos.

Source

Categories, contexts and relations in knowledge organization: Proceedings of the Twelfth International ISKO Conference 6-9 August 2012, Mysore, India. Eds.: Neelameghan, A. u. K.S. Raghavan

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a

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Abstract

Large image collections on the Web need to be organized for effective retrieval. Metadata has a key role in image retrieval but rely on professionally assigned tags which is not a viable option. Current content-based image retrieval systems have not demonstrated sufficient utility on large-scale image sources on the web, and are usually used as a supplement to existing text-based image retrieval systems. We present two social tagging alternatives in the form of photo-sharing networks and image labeling games. Here we analyze these applications to evaluate their usefulness from the semantic point of view, investigating the management of social tagging for indexing. The findings of the study have shown that social tagging can generate a sizeable number of tags that can be classified as in terpretive for an image, and that tagging behaviour has a manageable and adjustable nature depending on tagging guidelines.

Type

a

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Abstract

This paper presents a methodological discussion of a study of tagging quality in subject indexing. The data analysis in the study was divided into 3 phases: analysis of indexing consistency, analysis of tagging effectiveness, and analysis of the semantic values of tags. To analyze indexing consistency, this study employed the vector space model-based indexing consistency measures. An analysis of tagging effectiveness with tagging exhaustivity and tag specificity was conducted to ameliorate the drawbacks of consistency analysis based on only the quantitative measures of vocabulary matching. To further investigate the semantic values of tags at various levels of specificity, a latent semantic analysis (LSA) was conducted. To test statistical significance for the relation between tag specificity and semantic quality, correlation analysis was conducted. This research demonstrates the potential of tags for web document indexing with a complete assessment of tagging quality and provides a basis for further study of the strengths and limitations of tagging.

Type

a

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Abstract

With the increasing popularity of social tagging systems, the potential for using social tags as a source of metadata is being explored. Social tagging systems can simplify the involvement of a large number of users and improve the metadata-generation process. Current research is exploring social tagging systems as a mechanism to allow nonprofessional catalogers to participate in metadata generation. Because social tags are not from controlled vocabularies, there are issues that have to be addressed in finding quality terms to represent the content of a resource. This research explores ways to obtain a set of tags representing the resource from the tags provided by users. Two metrics are introduced. Annotation Dominance (AD) is a measure of the extent to which a tag term is agreed to by users. Cross Resources Annotation Discrimination (CRAD) is a measure of a tag's potential to classify a collection. It is designed to remove tags that are used too broadly or narrowly. Using the proposed measurements, the research selects important tags (meta-terms) and removes meaningless ones (tag noise) from the tags provided by users. To evaluate the proposed approach to find classificatory metadata candidates, we rely on expert users' relevance judgments comparing suggested tag terms and expert metadata terms. The results suggest that processing of user tags using the two measurements successfully identifies the terms that represent the topic categories of web resource content. The suggested tag terms can be further examined in various usages as semantic metadata for the resources.

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Abstract

A longstanding area of study in indexing is the identification of factors affecting vocabulary usage and consistency. This topic has seen a recent resurgence with a focus on social tagging. Tagging data for scholarly articles made available by the social bookmarking Website CiteULike (www.citeulike.org) were used to test the use of inter-indexer/tagger consistency density values, based on a method developed by the authors by comparing calculations for highly tagged documents representing three subject areas (Science, Social Science, Social Software). The analysis revealed that the developed method is viable for a large dataset. The findings also indicated that there were no significant differences in tagging consistency among the three topic areas, demonstrating that vocabulary usage in a relatively new subject area like social software is no more inconsistent than the more established subject areas investigated. The implications of the method used and the findings are discussed.

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Abstract

Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.

Type

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Abstract

Marginalia or 'scribbling in the margins' is a means for readers to add a more in-depth level of granularity and subject representation to digital documents such as those present in social sharing environments like Flickr and del.icio.us. Social classification and social sharing sites development of user-defined descriptors or tags is discussed in the context of knowledge organization. With this position paper I present a rationale for the use of the resulting folksonomies and tag clouds being developed in these social sharing communities as a rich source of information about our users and their natural organization processes. The knowledge organization community needs to critically examine our understandings of these emerging classificatory schema and determine how best to adapt, augment, revitalize existing knowledge organization structures.

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Content

This paper presents a longitudinal case study and analysis of tagging patterns in del.icio.us. Previous research has indicated that a tagging vocabulary will stabilize over time, suggesting that convergence may occur. This case study investigates the possibility of stability and convergence in a subset of the tagging vocabulary used with del.icio.us.

Type

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Abstract

Knowledge organization structures are dependent upon domain-analytical processes for determining ontological imperatives. Boundary objects-terms used in multiple domains but understood differently in each-are ontological clash points. Cognitive Work Analysis is an effective qualitative methodology for domain analysis of a group of people who work together. CWA was used recently to understand the ontology of a human resources firm. Boundary objects from the taxonomy that emerged from narrative analysis are presented here for individual analysis.

Footnote

Part of a section: "Papers from the Fourth North American Symposium on Knowledge Organization, sponsored by ISKO-Canada, United States, 13-14 June, 2013, Milwaukee, Wisconsin"

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Abstract

This article examines tagging as knowledge organization. Tagging is a kind of indexing, a process of labelling and categorizing information made to support resource discovery for users. Social tagging generally means the practice whereby internet users generate keywords to describe, categorise or comment on digital content. The value of tagging comes when social tags within a collection are aggregated and shared through a folksonomy. This article examines definitions of tagging and folksonomy, and discusses the functions, advantages and disadvantages of tagging systems in relation to knowledge organization before discussing studies that have compared tagging and conventional library-based knowledge organization systems. Approaches to disciplining tagging practice are examined and tagger motivation discussed. Finally, the article outlines current research fronts.

Type

a