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  • × year_i:[2010 TO 2020}
  • × theme_ss:"Social tagging"
  1. 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) 0.05 
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    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.
    LCSH
    Libraries and museums / Electronic information resources
    Subject
    Libraries and museums / Electronic information resources
  2. Feinberg, M.: Expressive bibliography : personal collections in public space (2011) 0.04 
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    Abstract
    This paper examines collections of citations that individual users contribute to social tagging systems such as Delicious and LibraryThing. I characterize these personal collections, furnished with various forms of metadata and arranged for Web display, as a means of communication, where a particular sensibility molds guiding principles for resource selection, description, and categorization. Using several analytic frameworks from museum studies, I present three brief case studies that interrogate both the substance and the means of expression achieved in such collections, which I term "expressive bibliographies." In considering these case studies, I explore how an explicit rhetorical perspective might inform purposeful design of expressive bibliography.
  3. Huang, C.; Fu, T.; Chen, H.: Text-based video content classification for online video-sharing sites (2010) 0.02 
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    Abstract
    With the emergence of Web 2.0, sharing personal content, communicating ideas, and interacting with other online users in Web 2.0 communities have become daily routines for online users. User-generated data from Web 2.0 sites provide rich personal information (e.g., personal preferences and interests) and can be utilized to obtain insight about cyber communities and their social networks. Many studies have focused on leveraging user-generated information to analyze blogs and forums, but few studies have applied this approach to video-sharing Web sites. In this study, we propose a text-based framework for video content classification of online-video sharing Web sites. Different types of user-generated data (e.g., titles, descriptions, and comments) were used as proxies for online videos, and three types of text features (lexical, syntactic, and content-specific features) were extracted. Three feature-based classification techniques (C4.5, Naïve Bayes, and Support Vector Machine) were used to classify videos. To evaluate the proposed framework, user-generated data from candidate videos, which were identified by searching user-given keywords on YouTube, were first collected. Then, a subset of the collected data was randomly selected and manually tagged by users as our experiment data. The experimental results showed that the proposed approach was able to classify online videos based on users' interests with accuracy rates up to 87.2%, and all three types of text features contributed to discriminating videos. Support Vector Machine outperformed C4.5 and Naïve Bayes techniques in our experiments. In addition, our case study further demonstrated that accurate video-classification results are very useful for identifying implicit cyber communities on video-sharing Web sites.
  4. Xu, C.; Ma, B.; Chen, X.; Ma, F.: Social tagging in the scholarly world (2013) 0.02 
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    Abstract
    The number of research studies on social tagging has increased rapidly in the past years, but few of them highlight the characteristics and research trends in social tagging. A set of 862 academic documents relating to social tagging and published from 2005 to 2011 was thus examined using bibliometric analysis as well as the social network analysis technique. The results show that social tagging, as a research area, develops rapidly and attracts an increasing number of new entrants. There are no key authors, publication sources, or research groups that dominate the research domain of social tagging. Research on social tagging appears to focus mainly on the following three aspects: (a) components and functions of social tagging (e.g., tags, tagging objects, and tagging network), (b) taggers' behaviors and interface design, and (c) tags' organization and usage in social tagging. The trend suggest that more researchers turn to the latter two integrated with human computer interface and information retrieval, although the first aspect is the fundamental one in social tagging. Also, more studies relating to social tagging pay attention to multimedia tagging objects and not only text tagging. Previous research on social tagging was limited to a few subject domains such as information science and computer science. As an interdisciplinary research area, social tagging is anticipated to attract more researchers from different disciplines. More practical applications, especially in high-tech companies, is an encouraging research trend in social tagging.
  5. Seeman, D.: Naming names : the ethics of identification in digital library metadata (2012) 0.01 
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    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.
  6. Lee, Y.Y.; Yang, S.Q.: Folksonomies as subject access : a survey of tagging in library online catalogs and discovery layers (2012) 0.01 
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    Abstract
    This paper describes a survey on how system vendors and libraries handled tagging in OPACs and discovery layers. Tags are user added subject metadata, also called folksonomies. This survey also investigated user behavior when they face the possibility to tag. The findings indicate that legacy/classic systems have no tagging capability. About 47% of the discovery tools provide tagging function. About 49% of the libraries that have a system with tagging capability have turned the tagging function on in their OPACs and discovery tools. Only 40% of the libraries that turned tagging on actually utilized user added subject metadata as access point to collections. Academic library users are less active in tagging than public library users.
    Source
    Beyond libraries - subject metadata in the digital environment and semantic web. IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn
  7. Kipp, M.E.; Beak, J.; Choi, I.: Motivations and intentions of flickr users in enriching flick records for Library of Congress photos (2017) 0.01 
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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.
  8. Rafferty, P.: Tagging (2018) 0.01 
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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.
  9. Li, D.; Ding, Y.; Sugimoto, C.; He, B.; Tang, J.; Yan, E.; Lin, N.; Qin, Z.; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model (2011) 0.00 
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    Abstract
    The presence of social networks in complex systems has made networks and community structure a focal point of study in many domains. Previous studies have focused on the structural emergence and growth of communities and on the topics displayed within the network. However, few scholars have closely examined the relationship between the thematic and structural properties of networks. Therefore, this article proposes the Tagger Tag Resource-Latent Dirichlet Allocation-Community model (TTR-LDA-Community model), which combines the Latent Dirichlet Allocation (LDA) model with the Girvan-Newman community detection algorithm through an inference mechanism. Using social tagging data from Delicious, this article demonstrates the clustering of active taggers into communities, the topic distributions within communities, and the ranking of taggers, tags, and resources within these communities. The data analysis evaluates patterns in community structure and topical affiliations diachronically. The article evaluates the effectiveness of community detection and the inference mechanism embedded in the model and finds that the TTR-LDA-Community model outperforms other traditional models in tag prediction. This has implications for scholars in domains interested in community detection, profiling, and recommender systems.
  10. Rafferty, P.; Murphy, H.: Is there nothing outside the tags? : towards a poststructuralist analysis of social tagging (2015) 0.00 
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    Abstract
    Purpose The purpose of the research is to explore relationships between social tagging and key poststructuralist principles; to devise and construct an analytical framework through which key poststructuralist principles are converted into workable research questions and applied to analyse Librarything tags, and to assess the validity of performing such an analysis. The research hypothesis is that tagging represents an imperfect analogy for the poststructuralist project Design/methodology/approach Tags from LibraryThing and from a library OPAC were compared and constrasted with Library of Congress Subject Headings (LCSH) and publishers' descriptions. Research questions derived from poststructuralism, asked whether tags destabilise meaning, whether and how far the death of the author is expressed in tags, and whether tags deconstruct LCSH. Findings Tags can temporarily destabilise meaning by obfuscating the structure of a word. Meaning is destabilised, perhaps only momentarily, and then it is recreated; it might resemble the original meaning, or it may not, however any attempt to make tags useful or functional necessarily imposes some form of structure. The analysis indicates that in tagging, the author, if not dead, is ignored. Authoritative interpretations are not pervasively mimicked in the tags. In relation to LCSH, tagging decentres the dominant view, but neither exposes nor judges it. Nor does tagging achieve the final stage of the deconstructive process, showing the dominant view to be a constructed reality. Originality/value This is one of very few studies to have attempted a critical theoretical approach to social tagging. It offers a novel methodological approach to undertaking analysis based on poststructuralist theory.
  11. Bundza, M.: ¬The choice is yours! : researchers assign subject metadata to their own materials in institutional repositories (2014) 0.00 
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    Footnote
    Contribution in a special issue "Beyond libraries: Subject metadata in the digital environment and Semantic Web" - Enthält Beiträge der gleichnamigen IFLA Satellite Post-Conference, 17-18 August 2012, Tallinn.
  12. Fox, M.J.: Communities of practice, gender and social tagging (2012) 0.00 
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    Abstract
    Social or collaborative tagging enables users to organize and label resources on the web. Libraries and other information environments hope that tagging can complement professional subject access with user-created terms. But who are the taggers, and does their language represent that of the user population? Some language theorists believe that inherent variables, such as gender or race, can be responsible for language use, whereas other researchers endorse more multiply-influenced practice-based approaches, where interactions with others affect language use more than a single variable. To explore whether linguistic variation in tagging is influenced more by gender or context, in this exploratory study, I will analyze the content and quantity of tags used on LibraryThing. This study seeks to dismantle stereotypical views of women's language use and to suggest a community of practice-based approach to analyzing social tags.
  13. Knautz, K.; Stock, W.G.: Collective indexing of emotions in videos (2011) 0.00 
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    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.
  14. 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.
  15. Chae, G.; Park, J.; Park, J.; Yeo, W.S.; Shi, C.: Linking and clustering artworks using social tags : revitalizing crowd-sourced information on cultural collections (2016) 0.00 
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    Abstract
    Social tagging is one of the most popular methods for collecting crowd-sourced information in galleries, libraries, archives, and museums (GLAMs). However, when the number of social tags grows rapidly, using them becomes problematic and, as a result, they are often left as simply big data that cannot be used for practical purposes. To revitalize the use of this crowd-sourced information, we propose using social tags to link and cluster artworks based on an experimental study using an online collection at the Gyeonggi Museum of Modern Art (GMoMA). We view social tagging as a folksonomy, where artworks are classified by keywords of the crowd's various interpretations and one artwork can belong to several different categories simultaneously. To leverage this strength of social tags, we used a clustering method called "link communities" to detect overlapping communities in a network of artworks constructed by computing similarities between all artwork pairs. We used this framework to identify semantic relationships and clusters of similar artworks. By comparing the clustering results with curators' manual classification results, we demonstrated the potential of social tagging data for automatically clustering artworks in a way that reflects the dynamic perspectives of crowds.
  16. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.00 
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    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
  17. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.00 
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    Date
    25.12.2012 15:22:37
  18. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.00 
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    Date
    21. 4.2016 11:23:22
  19. Qin, C.; Liu, Y.; Mou, J.; Chen, J.: User adoption of a hybrid social tagging approach in an online knowledge community (2019) 0.00 
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    Date
    20. 1.2015 18:30:22

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