Search (65 results, page 2 of 4)

  • × theme_ss:"Social tagging"
  • × year_i:[2010 TO 2020}
  1. Seeman, D.: Naming names : the ethics of identification in digital library metadata (2012) 0.02
    0.016172327 = product of:
      0.043126207 = sum of:
        0.020873476 = weight(_text_:retrieval in 416) [ClassicSimilarity], result of:
          0.020873476 = score(doc=416,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.16710453 = fieldWeight in 416, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=416)
        0.0167351 = weight(_text_:of in 416) [ClassicSimilarity], result of:
          0.0167351 = score(doc=416,freq=18.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.25915858 = fieldWeight in 416, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=416)
        0.0055176322 = product of:
          0.0110352645 = sum of:
            0.0110352645 = weight(_text_:on in 416) [ClassicSimilarity], result of:
              0.0110352645 = score(doc=416,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.121501654 = fieldWeight in 416, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=416)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    In many digital libraries, visual objects are published and metadata attached to allow for search and retrieval. For visual objects in which people appear, names are often added to the metadata so that digital library users can search for people appearing in these objects. Although this seems straightforward, there are ethical implications of adding names to metadata for visual objects. This paper explores the impact of this action and discusses relevant ethical issues it raises. It asserts that an individual's right to privacy and control over personal information must be weighed against the benefit of the object to society and the professional ethic to authentically represent a resource through its metadata. Context and an understanding of the major ethical issues will inform the practical decision of whether to keep objects online and add metadata to them, but items should generally be published unless there are clear ethical violations or a community relationship is in jeopardy.
    Content
    Beitrag aus einem Themenheft zu den Proceedings of the 2nd Milwaukee Conference on Ethics in Information Organization, June 15-16, 2012, School of Information Studies, University of Wisconsin-Milwaukee. Hope A. Olson, Conference Chair. Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_5_c.pdf.
  2. Social tagging in a linked data environment. Edited by Diane Rasmussen Pennington and Louise F. Spiteri. London, UK: Facet Publishing, 2018. 240 pp. £74.95 (paperback). (ISBN 9781783303380) (2019) 0.02
    0.016006988 = product of:
      0.0426853 = sum of:
        0.021389665 = weight(_text_:use in 101) [ClassicSimilarity], result of:
          0.021389665 = score(doc=101,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.1691581 = fieldWeight in 101, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0390625 = fieldNorm(doc=101)
        0.015778005 = weight(_text_:of in 101) [ClassicSimilarity], result of:
          0.015778005 = score(doc=101,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.24433708 = fieldWeight in 101, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=101)
        0.0055176322 = product of:
          0.0110352645 = sum of:
            0.0110352645 = weight(_text_:on in 101) [ClassicSimilarity], result of:
              0.0110352645 = score(doc=101,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.121501654 = fieldWeight in 101, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=101)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    Abstract
    Social tagging, hashtags, and geotags are used across a variety of platforms (Twitter, Facebook, Tumblr, WordPress, Instagram) in different countries and cultures. This book, representing researchers and practitioners across different information professions, explores how social tags can link content across a variety of environments. Most studies of social tagging have tended to focus on applications like library catalogs, blogs, and social bookmarking sites. This book, in setting out a theoretical background and the use of a series of case studies, explores the role of hashtags as a form of linked data?without the complex implementation of RDF and other Semantic Web technologies.
  3. Naderi, H.; Rumpler, B.: PERCIRS: a system to combine personalized and collaborative information retrieval (2010) 0.02
    0.015244558 = product of:
      0.040652156 = sum of:
        0.023615643 = weight(_text_:retrieval in 3960) [ClassicSimilarity], result of:
          0.023615643 = score(doc=3960,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.18905719 = fieldWeight in 3960, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.03125 = fieldNorm(doc=3960)
        0.012622404 = weight(_text_:of in 3960) [ClassicSimilarity], result of:
          0.012622404 = score(doc=3960,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.19546966 = fieldWeight in 3960, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=3960)
        0.004414106 = product of:
          0.008828212 = sum of:
            0.008828212 = weight(_text_:on in 3960) [ClassicSimilarity], result of:
              0.008828212 = score(doc=3960,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.097201325 = fieldWeight in 3960, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.03125 = fieldNorm(doc=3960)
          0.5 = coord(1/2)
      0.375 = coord(3/8)
    
    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.
    Source
    Journal of documentation. 66(2010) no.4, S.532-562
  4. Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012) 0.01
    0.013808267 = product of:
      0.05523307 = sum of:
        0.036299463 = weight(_text_:use in 2732) [ClassicSimilarity], result of:
          0.036299463 = score(doc=2732,freq=4.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.2870708 = fieldWeight in 2732, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.046875 = fieldNorm(doc=2732)
        0.018933605 = weight(_text_:of in 2732) [ClassicSimilarity], result of:
          0.018933605 = score(doc=2732,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.2932045 = fieldWeight in 2732, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=2732)
      0.25 = coord(2/8)
    
    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.
  5. Spiteri, L.F.: Incorporating facets into social tagging applications : an analysis of current trends (2010) 0.01
    0.013343668 = product of:
      0.05337467 = sum of:
        0.029945528 = weight(_text_:use in 3561) [ClassicSimilarity], result of:
          0.029945528 = score(doc=3561,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 3561, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3561)
        0.02342914 = weight(_text_:of in 3561) [ClassicSimilarity], result of:
          0.02342914 = score(doc=3561,freq=18.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.36282203 = fieldWeight in 3561, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3561)
      0.25 = coord(2/8)
    
    Abstract
    An increasingly difficult challenge in social tagging applications is negotiating the number of existing tags. This article examines the use of facets to facilitate the efficient organization and browsing of tags into manageable and distinct categories. Current and proposed methodologies for the application of facets in social tagging applications are evaluated. Results of this analysis indicate that these methodologies provide insufficient guidelines for the choice, evaluation, and maintenance of the facets. Suggestions are made to guide the design of a more rigorous methodology for the application of facets to social tagging applications.
  6. Vaidya, P.; Harinarayana, N.S.: ¬The comparative and analytical study of LibraryThing tags with Library of Congress Subject Headings (2016) 0.01
    0.012955112 = product of:
      0.05182045 = sum of:
        0.035423465 = weight(_text_:retrieval in 2492) [ClassicSimilarity], result of:
          0.035423465 = score(doc=2492,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.2835858 = fieldWeight in 2492, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=2492)
        0.016396983 = weight(_text_:of in 2492) [ClassicSimilarity], result of:
          0.016396983 = score(doc=2492,freq=12.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.25392252 = fieldWeight in 2492, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=2492)
      0.25 = coord(2/8)
    
    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.
  7. Knautz, K.; Stock, W.G.: Collective indexing of emotions in videos (2011) 0.01
    0.012781119 = product of:
      0.051124476 = sum of:
        0.029519552 = weight(_text_:retrieval in 295) [ClassicSimilarity], result of:
          0.029519552 = score(doc=295,freq=4.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.23632148 = fieldWeight in 295, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=295)
        0.021604925 = weight(_text_:of in 295) [ClassicSimilarity], result of:
          0.021604925 = score(doc=295,freq=30.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.33457235 = fieldWeight in 295, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=295)
      0.25 = coord(2/8)
    
    Abstract
    Purpose - The object of this empirical research study is emotion, as depicted and aroused in videos. This paper seeks to answer the questions: Are users able to index such emotions consistently? Are the users' votes usable for emotional video retrieval? Design/methodology/approach - The authors worked with a controlled vocabulary for nine basic emotions (love, happiness, fun, surprise, desire, sadness, anger, disgust and fear), a slide control for adjusting the emotions' intensity, and the approach of broad folksonomies. Different users tagged the same videos. The test persons had the task of indexing the emotions of 20 videos (reprocessed clips from YouTube). The authors distinguished between emotions which were depicted in the video and those that were evoked in the user. Data were received from 776 participants and a total of 279,360 slide control values were analyzed. Findings - The consistency of the users' votes is very high; the tag distributions for the particular videos' emotions are stable. The final shape of the distributions will be reached by the tagging activities of only very few users (less than 100). By applying the approach of power tags it is possible to separate the pivotal emotions of every document - if indeed there is any feeling at all. Originality/value - This paper is one of the first steps in the new research area of emotional information retrieval (EmIR). To the authors' knowledge, it is the first research project into the collective indexing of emotions in videos.
    Source
    Journal of documentation. 67(2011) no.6, S.975-994
  8. Bundza, M.: ¬The choice is yours! : researchers assign subject metadata to their own materials in institutional repositories (2014) 0.01
    0.010868087 = product of:
      0.04347235 = sum of:
        0.029945528 = weight(_text_:use in 1968) [ClassicSimilarity], result of:
          0.029945528 = score(doc=1968,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 1968, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1968)
        0.013526822 = weight(_text_:of in 1968) [ClassicSimilarity], result of:
          0.013526822 = score(doc=1968,freq=6.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.20947541 = fieldWeight in 1968, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1968)
      0.25 = coord(2/8)
    
    Abstract
    The Digital Commons platform for institutional repositories provides a three-tiered taxonomy of academic disciplines for each item submitted to the repository. Since faculty and departmental administrators across campuses are encouraged to submit materials to the institutional repository themselves, they must also assign disciplines or subject categories for their own work. The expandable drop-down menu of about 1,000 categories is easy to use, and facilitates the growth of the institutional repository and access to the materials through the Internet.
  9. Stuart, E.: Flickr: organizing and tagging images online (2019) 0.01
    0.010247533 = product of:
      0.040990133 = sum of:
        0.029945528 = weight(_text_:use in 5233) [ClassicSimilarity], result of:
          0.029945528 = score(doc=5233,freq=2.0), product of:
            0.12644777 = queryWeight, product of:
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.041294612 = queryNorm
            0.23682132 = fieldWeight in 5233, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0620887 = idf(docFreq=5623, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5233)
        0.011044604 = weight(_text_:of in 5233) [ClassicSimilarity], result of:
          0.011044604 = score(doc=5233,freq=4.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.17103596 = fieldWeight in 5233, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5233)
      0.25 = coord(2/8)
    
    Abstract
    Flickr was launched when digital cameras first began to outsell analog cameras, and people were drawn to the site for the opportunities it offered them to store, organize, and share their images, as well as for the connections that could be made with other like-minded people. This article examines the links between Flickr's success and how images are organized within the site, as well as the types of people and organizations that use Flickr and their motivations for doing so. Factors that have contributed to Flickr's demise in popularity will be explored, and the article finishes with some suggestions for how Flickr could develop in the future, along with some conclusions for image organization.
    Series
    Reviews of concepts in knowledge organization
  10. Matthews, B.; Jones, C.; Puzon, B.; Moon, J.; Tudhope, D.; Golub, K.; Nielsen, M.L.: ¬An evaluation of enhancing social tagging with a knowledge organization system (2010) 0.01
    0.010246642 = product of:
      0.040986568 = sum of:
        0.020873476 = weight(_text_:retrieval in 4171) [ClassicSimilarity], result of:
          0.020873476 = score(doc=4171,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.16710453 = fieldWeight in 4171, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4171)
        0.02011309 = weight(_text_:of in 4171) [ClassicSimilarity], result of:
          0.02011309 = score(doc=4171,freq=26.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.31146988 = fieldWeight in 4171, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4171)
      0.25 = coord(2/8)
    
    Abstract
    Purpose - Traditional subject indexing and classification are considered infeasible in many digital collections. This paper seeks to investigate ways of enhancing social tagging via knowledge organization systems, with a view to improving the quality of tags for increased information discovery and retrieval performance. Design/methodology/approach - Enhanced tagging interfaces were developed for exemplar online repositories, and trials were undertaken with author and reader groups to evaluate the effectiveness of tagging augmented with control vocabulary for subject indexing of papers in online repositories. Findings - The results showed that using a knowledge organisation system to augment tagging does appear to increase the effectiveness of non-specialist users (that is, without information science training) in subject indexing. Research limitations/implications - While limited by the size and scope of the trials undertaken, these results do point to the usefulness of a mixed approach in supporting the subject indexing of online resources. Originality/value - The value of this work is as a guide to future developments in the practical support for resource indexing in online repositories.
    Footnote
    Beitrag in einem Special Issue: Content architecture: exploiting and managing diverse resources: proceedings of the first national conference of the United Kingdom chapter of the International Society for Knowedge Organization (ISKO)
  11. Huang, H.; Jörgensen, C.: Characterizing user tagging and Co-occurring metadata in general and specialized metadata collections (2013) 0.01
    0.008908112 = product of:
      0.035632446 = sum of:
        0.020873476 = weight(_text_:retrieval in 1046) [ClassicSimilarity], result of:
          0.020873476 = score(doc=1046,freq=2.0), product of:
            0.124912694 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.041294612 = queryNorm
            0.16710453 = fieldWeight in 1046, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1046)
        0.014758972 = weight(_text_:of in 1046) [ClassicSimilarity], result of:
          0.014758972 = score(doc=1046,freq=14.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.22855641 = fieldWeight in 1046, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1046)
      0.25 = coord(2/8)
    
    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
  12. 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
    0.008900973 = product of:
      0.035603892 = sum of:
        0.024135707 = weight(_text_:of in 3421) [ClassicSimilarity], result of:
          0.024135707 = score(doc=3421,freq=26.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.37376386 = fieldWeight in 3421, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=3421)
        0.011468184 = product of:
          0.022936368 = sum of:
            0.022936368 = weight(_text_:on in 3421) [ClassicSimilarity], result of:
              0.022936368 = score(doc=3421,freq=6.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.25253648 = fieldWeight in 3421, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3421)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    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
  13. Choi, Y.: ¬A complete assessment of tagging quality : a consolidated methodology (2015) 0.01
    0.008555349 = product of:
      0.034221396 = sum of:
        0.027600236 = weight(_text_:of in 1730) [ClassicSimilarity], result of:
          0.027600236 = score(doc=1730,freq=34.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.4274153 = fieldWeight in 1730, product of:
              5.8309517 = tf(freq=34.0), with freq of:
                34.0 = termFreq=34.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=1730)
        0.006621159 = product of:
          0.013242318 = sum of:
            0.013242318 = weight(_text_:on in 1730) [ClassicSimilarity], result of:
              0.013242318 = score(doc=1730,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.14580199 = fieldWeight in 1730, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.046875 = fieldNorm(doc=1730)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    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.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.4, S.798-817
  14. Choi, Y.: ¬A Practical application of FRBR for organizing information in digital environments (2012) 0.01
    0.008485682 = product of:
      0.03394273 = sum of:
        0.021604925 = weight(_text_:of in 319) [ClassicSimilarity], result of:
          0.021604925 = score(doc=319,freq=30.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.33457235 = fieldWeight in 319, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=319)
        0.012337802 = product of:
          0.024675604 = sum of:
            0.024675604 = weight(_text_:on in 319) [ClassicSimilarity], result of:
              0.024675604 = score(doc=319,freq=10.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.271686 = fieldWeight in 319, product of:
                  3.1622777 = tf(freq=10.0), with freq of:
                    10.0 = termFreq=10.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=319)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    Abstract
    This study employs the FRBR (Functional Requirements for Bibliographic Records) conceptual model to provide in-depth investigation on the characteristics of social tags by analyzing the bibliographic attributes of tags that are not limited to subject properties. FRBR describes four different levels of entities (i.e., Work, Expression, Manifestation, and Item), which provide a distinguishing understanding of each entity in the bibliographic universe. In this research, since the scope of data analysis focuses on tags assigned to web documents, consideration on Manifestation and Item has been excluded. Accordingly, only the attributes of Work and Expression entity were investigated in order to map the attributes of tags to attributes defined in those entities. The content analysis on tag attributes was conducted on a total of 113 web documents regarding 11 attribute categories defined by FRBR. The findings identified essential bibliographic attributes of tags and tagging behaviors by subject. The findings showed that concerning specific subject areas, taggers exhibited different tagging behaviors representing distinctive features and tendencies. These results have led to the conclusion that there should be an increased awareness of diverse user needs by subject in terms of the practical implications of metadata generation.
    Content
    This paper is derived from the author's doctoral dissertation "Usefulness of Social Tagging in Organizing and Providing Access An Analysis of Indexing Consistency and Quality." The author is deeply grateful to her dissertation committee-Dr. Linda C. Smith chairperson, Drs. Allen Renear, Miles Efron and John Unsworth. Vgl.: http://www.ergon-verlag.de/isko_ko/downloads/ko_39_2012_4_a.pdf.
  15. Watters, C.; Nizam, N.: Knowledge organization on the Web : the emergent role of social classification (2012) 0.01
    0.008253391 = product of:
      0.033013564 = sum of:
        0.022089208 = weight(_text_:of in 828) [ClassicSimilarity], result of:
          0.022089208 = score(doc=828,freq=16.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.34207192 = fieldWeight in 828, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0546875 = fieldNorm(doc=828)
        0.010924355 = product of:
          0.02184871 = sum of:
            0.02184871 = weight(_text_:on in 828) [ClassicSimilarity], result of:
              0.02184871 = score(doc=828,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.24056101 = fieldWeight in 828, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=828)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    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
  16. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.01
    0.007906867 = product of:
      0.03162747 = sum of:
        0.017640345 = weight(_text_:of in 2891) [ClassicSimilarity], result of:
          0.017640345 = score(doc=2891,freq=20.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.27317715 = fieldWeight in 2891, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2891)
        0.013987125 = product of:
          0.02797425 = sum of:
            0.02797425 = weight(_text_:22 in 2891) [ClassicSimilarity], result of:
              0.02797425 = score(doc=2891,freq=2.0), product of:
                0.1446067 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.041294612 = queryNorm
                0.19345059 = fieldWeight in 2891, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2891)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    Abstract
    The purpose of this study was to examine user tags that describe digitized archival collections in the field of humanities. A collection of 8,310 tags from a digital portal (Nineteenth-Century Electronic Scholarship, NINES) was analyzed to find out what attributes of primary historical resources users described with tags. Tags were categorized to identify which tags describe the content of the resource, the resource itself, and subjective aspects (e.g., usage or emotion). The study's findings revealed that over half were content-related; tags representing opinion, usage context, or self-reference, however, reflected only a small percentage. The study further found that terms related to genre or physical format of a resource were frequently used in describing primary archival resources. It was also learned that nontextual resources had lower numbers of content-related tags and higher numbers of document-related tags than textual resources and bibliographic materials; moreover, textual resources tended to have more user-context-related tags than other resources. These findings help explain users' tagging behavior and resource interpretation in primary resources in the humanities. Such information provided through tags helps information professionals decide to what extent indexing archival and cultural resources should be done for resource description and discovery, and understand users' terminology.
    Date
    21. 4.2016 11:23:22
    Source
    Journal of the Association for Information Science and Technology. 67(2016) no.5, S.1089-1104
  17. Nov, O.; Naaman, M.; Ye, C.: Analysis of participation in an online photo-sharing community : a multidimensional perspective (2010) 0.01
    0.007788932 = product of:
      0.031155728 = sum of:
        0.017640345 = weight(_text_:of in 3424) [ClassicSimilarity], result of:
          0.017640345 = score(doc=3424,freq=20.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.27317715 = fieldWeight in 3424, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3424)
        0.013515383 = product of:
          0.027030766 = sum of:
            0.027030766 = weight(_text_:on in 3424) [ClassicSimilarity], result of:
              0.027030766 = score(doc=3424,freq=12.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.29761705 = fieldWeight in 3424, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3424)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    Abstract
    In recent years we have witnessed a significant growth of social-computing communities - online services in which users share information in various forms. As content contributions from participants are critical to the viability of these communities, it is important to understand what drives users to participate and share information with others in such settings. We extend previous literature on user contribution by studying the factors that are associated with various forms of participation in a large online photo-sharing community. Using survey and system data, we examine four different forms of participation and consider the differences between these forms. We build on theories of motivation to examine the relationship between users' participation and their motivations with respect to their tenure in the community. Amongst our findings, we identify individual motivations (both extrinsic and intrinsic) that underpin user participation, and their effects on different forms of information sharing; we show that tenure in the community does affect participation, but that this effect depends on the type of participation activity. Finally, we demonstrate that tenure in the community has a weak moderating effect on a number of motivations with regard to their effect on participation. Directions for future research, as well as implications for theory and practice, are discussed.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.3, S.555-566
  18. Rorissa, A.: ¬A comparative study of Flickr tags and index terms in a general image collection (2010) 0.01
    0.0076072896 = product of:
      0.030429158 = sum of:
        0.02087234 = weight(_text_:of in 4100) [ClassicSimilarity], result of:
          0.02087234 = score(doc=4100,freq=28.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.32322758 = fieldWeight in 4100, product of:
              5.2915025 = tf(freq=28.0), with freq of:
                28.0 = termFreq=28.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4100)
        0.00955682 = product of:
          0.01911364 = sum of:
            0.01911364 = weight(_text_:on in 4100) [ClassicSimilarity], result of:
              0.01911364 = score(doc=4100,freq=6.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.21044704 = fieldWeight in 4100, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4100)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    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
  19. Stvilia, B.; Jörgensen, C.: Member activities and quality of tags in a collection of historical photographs in Flickr (2010) 0.01
    0.007458293 = product of:
      0.029833172 = sum of:
        0.02431554 = weight(_text_:of in 4117) [ClassicSimilarity], result of:
          0.02431554 = score(doc=4117,freq=38.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.37654874 = fieldWeight in 4117, product of:
              6.164414 = tf(freq=38.0), with freq of:
                38.0 = termFreq=38.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4117)
        0.0055176322 = product of:
          0.0110352645 = sum of:
            0.0110352645 = weight(_text_:on in 4117) [ClassicSimilarity], result of:
              0.0110352645 = score(doc=4117,freq=2.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.121501654 = fieldWeight in 4117, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4117)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    Abstract
    To enable and guide effective metadata creation it is essential to understand the structure and patterns of the activities of the community around the photographs, resources used, and scale and quality of the socially created metadata relative to the metadata and knowledge already encoded in existing knowledge organization systems. This article presents an analysis of Flickr member discussions around the photographs of the Library of Congress photostream in Flickr. The article also reports on an analysis of the intrinsic and relational quality of the photostream tags relative to two knowledge organization systems: the Thesaurus for Graphic Materials (TGM) and the Library of Congress Subject Headings (LCSH). Thirty seven percent of the original tag set and 15.3% of the preprocessed set (after the removal of tags with fewer than three characters and URLs) were invalid or misspelled terms. Nouns, named entity terms, and complex terms constituted approximately 77% of the preprocessed set. More than a half of the photostream tags were not found in the TGM and LCSH, and more than a quarter of those terms were regular nouns and noun phrases. This suggests that these terms could be complimentary to more traditional methods of indexing using controlled vocabularies.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.12, S.2477-2489
  20. Wei, W.; Ram, S.: Utilizing sozial bookmarking tag space for Web content discovery : a social network analysis approach (2010) 0.01
    0.006793595 = product of:
      0.02717438 = sum of:
        0.02093189 = weight(_text_:of in 1) [ClassicSimilarity], result of:
          0.02093189 = score(doc=1,freq=44.0), product of:
            0.06457475 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.041294612 = queryNorm
            0.3241498 = fieldWeight in 1, product of:
              6.6332498 = tf(freq=44.0), with freq of:
                44.0 = termFreq=44.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.03125 = fieldNorm(doc=1)
        0.0062424885 = product of:
          0.012484977 = sum of:
            0.012484977 = weight(_text_:on in 1) [ClassicSimilarity], result of:
              0.012484977 = score(doc=1,freq=4.0), product of:
                0.090823986 = queryWeight, product of:
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.041294612 = queryNorm
                0.13746344 = fieldWeight in 1, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  2.199415 = idf(docFreq=13325, maxDocs=44218)
                  0.03125 = fieldNorm(doc=1)
          0.5 = coord(1/2)
      0.25 = coord(2/8)
    
    Abstract
    Social bookmarking has gained popularity since the advent of Web 2.0. Keywords known as tags are created to annotate web content, and the resulting tag space composed of the tags, the resources, and the users arises as a new platform for web content discovery. Useful and interesting web resources can be located through searching and browsing based on tags, as well as following the user-user connections formed in the social bookmarking community. However, the effectiveness of tag-based search is limited due to the lack of explicitly represented semantics in the tag space. In addition, social connections between users are underused for web content discovery because of the inadequate social functions. In this research, we propose a comprehensive framework to reorganize the flat tag space into a hierarchical faceted model. We also studied the structure and properties of various networks emerging from the tag space for the purpose of more efficient web content discovery. The major research approach used in this research is social network analysis (SNA), together with methodologies employed in design science research. The contribution of our research includes: (i) a faceted model to categorize social bookmarking tags; (ii) a relationship ontology to represent the semantics of relationships between tags; (iii) heuristics to reorganize the flat tag space into a hierarchical faceted model using analysis of tag-tag co-occurrence networks; (iv) an implemented prototype system as proof-of-concept to validate the feasibility of the reorganization approach; (v) a set of evaluations of the social functions of the current networking features of social bookmarking and a series of recommendations as to how to improve the social functions to facilitate web content discovery.
    Content
    A Dissertation Submitted to the Faculty of the COMMITTEE ON BUSINESS ADMINISTRATION In Partial Fulfillment of the Requirements For the Degree of DOCTOR OF PHILOSOPHY WITH A MAJOR IN MANAGEMENT In the Graduate College THE UNIVERSITY OF ARIZONA. Vgl.: http://hdl.handle.net/10150/195123. Vgl. auch: https://www.semanticscholar.org/paper/Utilizing-social-bookmarking-tag-space-for-web-a-Ram-Wei/da9e7e5ee771008b741af7176d3f0d67128d1dca.

Languages

  • e 61
  • d 4
  • More… Less…

Types

  • a 63
  • el 2
  • m 2
  • s 1
  • More… Less…

Classifications