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  • × language_ss:"e"
  • × theme_ss:"Social tagging"
  1. Tsui, E.; Wang, W.M.; Cheung, C.F.; Lau, A.S.M.: ¬A concept-relationship acquisition and inference approach for hierarchical taxonomy construction from tags (2010) 0.00 
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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.
    Source
    Information processing and management. 46(2010) no.1, S.44-57
  2. Choi, N.; Joo, S.: Booklovers' world : an examination of factors affecting continued usage of social cataloging sites (2016) 0.00 
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    Abstract
    Little is known about what factors influence users' continued use of social cataloging sites. This study therefore examines the impacts of key factors from theories of information systems (IS) success and sense of community (SOC) on users' continuance intention in the social cataloging context. Data collected from an online survey of 323 social cataloging users provide empirical support for the research model. The findings indicate that both information quality (IQ) and system quality (SQ) are significant predictors of satisfaction and SOC, which in turn lead to users' intentions to continue using these sites. In addition, SOC was found to affect continuance intention not only directly, but also indirectly through satisfaction. Theoretically, this study draws attention to a largely unexplored but essential area of research in the social cataloging literature and provides a fundamental basis to understand the determinants of continued social cataloging usage. From a managerial perspective, the findings suggest that social cataloging service providers should constantly focus their efforts on the quality control of their contents and system, and the enhancement of SOC among their users.
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3022-3035
  3. Ding, Y.; Jacob, E.K.; Zhang, Z.; Foo, S.; Yan, E.; George, N.L.; Guo, L.: Perspectives on social tagging (2009) 0.00 
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    Abstract
    Social tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.12, S.2388-2401
  4. Ding, Y.; Jacob, E.K.; Fried, M.; Toma, I.; Yan, E.; Foo, S.; Milojevicacute, S.: Upper tag ontology for integrating social tagging data (2010) 0.00 
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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
  5. Hsu, M.-H.; Chen, H.-H.: Efficient and effective prediction of social tags to enhance Web search (2011) 0.00 
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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
  6. Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011) 0.00 
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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
  7. Lee, D.H.; Schleyer, T.: Social tagging is no substitute for controlled indexing : a comparison of Medical Subject Headings and CiteULike tags assigned to 231,388 papers (2012) 0.00 
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    Abstract
    Social tagging and controlled indexing both facilitate access to information resources. Given the increasing popularity of social tagging and the limitations of controlled indexing (primarily cost and scalability), it is reasonable to investigate to what degree social tagging could substitute for controlled indexing. In this study, we compared CiteULike tags to Medical Subject Headings (MeSH) terms for 231,388 citations indexed in MEDLINE. In addition to descriptive analyses of the data sets, we present a paper-by-paper analysis of tags and MeSH terms: the number of common annotations, Jaccard similarity, and coverage ratio. In the analysis, we apply three increasingly progressive levels of text processing, ranging from normalization to stemming, to reduce the impact of lexical differences. Annotations of our corpus consisted of over 76,968 distinct tags and 21,129 distinct MeSH terms. The top 20 tags/MeSH terms showed little direct overlap. On a paper-by-paper basis, the number of common annotations ranged from 0.29 to 0.5 and the Jaccard similarity from 2.12% to 3.3% using increased levels of text processing. At most, 77,834 citations (33.6%) shared at least one annotation. Our results show that CiteULike tags and MeSH terms are quite distinct lexically, reflecting different viewpoints/processes between social tagging and controlled indexing.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.9, S.1747-1757
  8. Huang, H.; Jörgensen, C.: Characterizing user tagging and Co-occurring metadata in general and specialized metadata collections (2013) 0.00 
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    Abstract
    This study aims to identify the categorical characteristics and usage patterns of the most popular image tags in Flickr. The "metadata usage ratio" is introduced as a means of assessing the usage of a popular tag as metadata. We also compare how popular tags are used as image tags or metadata in the Flickr general collection and the Library of Congress's photostream (LCP), also in Flickr. The Flickr popular tags in the list overall are categorically stable, and the changes that do appear reflect Flickr users' evolving technology-driven cultural experience. The popular tags in Flickr had a high number of generic objects and specific locations-related tags and were rarely at the abstract level. Conversely, the popular tags in the LCP describe more in the specific objects and time categories. Flickr users copied the Library of Congress-supplied metadata that related to specific objects or events and standard bibliographic information (e.g., author, format, time references) as popular tags in the LCP. Those popular tags related to generic objects and events showed a high metadata usage ratio, while those related to specific locations and objects showed a low image metadata usage ratio. Popular tags in Flickr appeared less frequently as image metadata when describing specific objects than specific times and locations for historical images in Flickr LCP collections. Understanding how people contribute image tags or image metadata in Flickr helps determine what users need to describe and query images, and could help improve image browsing and retrieval.
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.9, S.1878-1889
  9. Kipp, M.E.; Beak, J.; Choi, I.: Motivations and intentions of flickr users in enriching flick records for Library of Congress photos (2017) 0.00 
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    Abstract
    The purpose of this study is to understand users' motivations and intentions in the use of institutional collections on social tagging sites. Previous social tagging studies have collected social tagging data and analyzed how tagging functions as a tool to organize and retrieve information. Many studies focused on the patterns of tagging rather than the users' perspectives. To provide a more comprehensive picture of users' social tagging activities in institutional collections, and how this compares to social tagging in a more personal context, we collected data from social tagging users by surveying 7,563 participants in the Library of Congress's Flickr Collection. We asked users to describe their motivations for activities within the LC Flickr Collection in their own words using open-ended questions. As a result, we identified 11 motivations using a bottom-up, open-coding approach: affective reactions, opinion on photo, interest in subject, contribution to description, knowledge sharing, improving findability, social network, appreciation, personal use, and personal relationship. Our study revealed that affective or emotional reactions play a critical role in the use of social tagging of institutional collections by comparing our findings to existing frameworks for tagging motivations. We also examined the relationships between participants' occupations and our 11 motivations.
    Source
    Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2364-2379
  10. Xu, C.; Zhang, Q.: ¬The dominant factor of social tags for users' decision behavior on e-commerce websites : color or text (2019) 0.00 
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    Footnote
    Beitrag in einem 'Special issue on neuro-information science'.
    Source
    Journal of the Association for Information Science and Technology. 70(2019) no.9, S.942-953
  11. Naderi, H.; Rumpler, B.: PERCIRS: a system to combine personalized and collaborative information retrieval (2010) 0.00 
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    Abstract
    Purpose - This paper aims to discuss and test the claim that utilization of the personalization techniques can be valuable to improve the efficiency of collaborative information retrieval (CIR) systems. Design/methodology/approach - A new personalized CIR system, called PERCIRS, is presented based on the user profile similarity calculation (UPSC) formulas. To this aim, the paper proposes several UPSC formulas as well as two techniques to evaluate them. As the proposed CIR system is personalized, it could not be evaluated by Cranfield, like evaluation techniques (e.g. TREC). Hence, this paper proposes a new user-centric mechanism, which enables PERCIRS to be evaluated. This mechanism is generic and can be used to evaluate any other personalized IR system. Findings - The results show that among the proposed UPSC formulas in this paper, the (query-document)-graph based formula is the most effective. After integrating this formula into PERCIRS and comparing it with nine other IR systems, it is concluded that the results of the system are better than the other IR systems. In addition, the paper shows that the complexity of the system is less that the complexity of the other CIR systems. Research limitations/implications - This system asks the users to explicitly rank the returned documents, while explicit ranking is still not widespread enough. However it believes that the users should actively participate in the IR process in order to aptly satisfy their needs to information. Originality/value - The value of this paper lies in combining collaborative and personalized IR, as well as introducing a mechanism which enables the personalized IR system to be evaluated. The proposed evaluation mechanism is very valuable for developers of personalized IR systems. The paper also introduces some significant user profile similarity calculation formulas, and two techniques to evaluate them. These formulas can also be used to find the user's community in the social networks.
  12. Furner, J.: User tagging of library resources : toward a framework for system evaluation (2007) 0.00 
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    Content
    Vortrag anlässlich: WORLD LIBRARY AND INFORMATION CONGRESS: 73RD IFLA GENERAL CONFERENCE AND COUNCIL 19-23 August 2007, Durban, South Africa. - 157 - Classification and Indexing
  13. Rafferty, P.; Hidderley, R.: Flickr and democratic Indexing : dialogic approaches to indexing (2007) 0.00 
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    Abstract
    Purpose - The purpose of this paper is two-fold: to examine three models of subject indexing (i.e. expert-led indexing, author-generated indexing, and user-orientated indexing); and to compare and contrast two user-orientated indexing approaches (i.e. the theoretically-based Democratic Indexing project, and Flickr, a working system for describing photographs). Design/methodology/approach - The approach to examining Flickr and Democratic Indexing is evaluative. The limitations of Flickr are described and examples are provided. The Democratic Indexing approach, which the authors believe offers a method of marshalling a "free" user-indexed archive to provide useful retrieval functions, is described. Findings - The examination of both Flickr and the Democratic Indexing approach suggests that, despite Shirky's claim of philosophical paradigm shifting for social tagging, there is a residing doubt amongst information professionals that self-organising systems can work without there being some element of control and some form of "representative authority". Originality/value - This paper contributes to the literature of user-based indexing and social tagging.
  14. Wolfram, D.; Olson, H.A.; Bloom, R.: Measuring consistency for multiple taggers using vector space modeling (2009) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.10, S.1995-2003
  15. Antin, J.; Earp, M.: With a little help from my friends : self-interested and prosocial behavior on MySpace Music (2010) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.952-963
  16. Wang, J.; Clements, M.; Yang, J.; Vries, A.P. de; Reinders, M.J.T.: Personalization of tagging systems (2010) 0.00 
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    Source
    Information processing and management. 46(2010) no.1, S.58-70
  17. Raban, D.R.; Ronen, I.; Guy, I.: Acting or reacting? : Preferential attachment in a people-tagging system (2011) 0.00 
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  18. Golbeck, J.; Koepfler, J.; Emmerling, B.: ¬An experimental study of social tagging behavior and image content (2011) 0.00 
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  19. Estellés Arolas, E.; González Ladrón-de-Guevar, F.: Uses of explicit and implicit tags in social bookmarking (2012) 0.00 
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  20. Choi, Y.: ¬A complete assessment of tagging quality : a consolidated methodology (2015) 0.00 
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