Search (102 results, page 1 of 6)

  • × theme_ss:"Social tagging"
  1. Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008) 0.04 
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    Abstract
    The growing predominance of social semantics in the form of tagging presents the metadata community with both opportunities and challenges as for leveraging this new form of information content representation and for retrieval. One key challenge is the absence of contextual information associated with these tags. This paper presents an experiment working with Flickr tags as an example of utilizing social semantics sources for enriching subject metadata. The procedure included four steps: 1) Collecting a sample of Flickr tags, 2) Calculating cooccurrences between tags through mutual information, 3) Tracing contextual information of tag pairs via Google search results, 4) Applying natural language processing and machine learning techniques to extract semantic relations between tags. The experiment helped us to build a context sentence collection from the Google search results, which was then processed by natural language processing and machine learning algorithms. This new approach achieved a reasonably good rate of accuracy in assigning semantic relations to tag pairs. This paper also explores the implications of this approach for using social semantics to enrich subject metadata.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  2. Naderi, H.; Rumpler, B.: PERCIRS: a system to combine personalized and collaborative information retrieval (2010) 0.03 
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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.
  3. Yi, K.: ¬A semantic similarity approach to predicting Library of Congress subject headings for social tags (2010) 0.03 
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    Abstract
    Social tagging or collaborative tagging has become a new trend in the organization, management, and discovery of digital information. The rapid growth of shared information mostly controlled by social tags poses a new challenge for social tag-based information organization and retrieval. A plausible approach for this challenge is linking social tags to a controlled vocabulary. As an introductory step for this approach, this study investigates ways of predicting relevant subject headings for resources from social tags assigned to the resources. The prediction of subject headings was measured by five different similarity measures: tf-idf, cosine-based similarity (CoS), Jaccard similarity (or Jaccard coefficient; JS), Mutual information (MI), and information radius (IRad). Their results were compared to those by professionals. The results show that a CoS measure based on top five social tags was most effective. Inclusions of more social tags only aggravate the performance. The performance of JS is comparable to the performance of CoS while tf-idf is comparable with up to 70% less than the best performance. MI and IRad have inferior performance compared to the other methods. This study demonstrates the application of the similarity measuring techniques to the prediction of correct Library of Congress subject headings.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.8, S.1658-1672
  4. 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.
    Source
    Journal of the American Society for Information Science and Technology. 61(2010) no.5, S.891-906
  5. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.01 
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    Abstract
    A new collaborative approach in information organization and sharing has recently arisen, known as collaborative tagging or social indexing. A key element of collaborative tagging is the concept of collective intelligence (CI), which is a shared intelligence among all participants. This research investigates the phenomenon of social tagging in the context of CI with the aim to serve as a stepping-stone towards the mining of truly valuable social tags for web resources. This study focuses on assessing and evaluating the degree of CI embedded in social tagging over time in terms of two-parameter values, number of participants, and top frequency ranking window. Five different metrics were adopted and utilized for assessing the similarity between ranking lists: overlapList, overlapRank, Footrule, Fagin's measure, and the Inverse Rank measure. The result of this study demonstrates that a substantial degree of CI is most likely to be achieved when somewhere between the first 200 and 400 people have participated in tagging, and that a target degree of CI can be projected by controlling the two factors along with the selection of a similarity metric. The study also tests some experimental conditions for detecting social tags with high CI degree. The results of this study can be applicable to the study of filtering social tags based on CI; filtered social tags may be utilized for the metadata creation of tagged resources and possibly for the retrieval of tagged resources.
    Date
    25.12.2012 15:22:37
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.12, S.2488-2502
  6. Peters, I.; Schumann, L.; Terliesner, J.: Folksonomy-basiertes Information Retrieval unter der Lupe (2012) 0.01 
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    Abstract
    Social Tagging ist eine weitverbreitete Methode, um nutzergenerierte Inhalte in Webdiensten zu indexieren. Dieser Artikel fasst die aktuelle Forschung zu Folksonomies und Effektivität von Tags in Retrievalsystemen zusammen. Es wurde ein TREC-ähnlicher Retrievaltest mit Tags und Ressourcen aus dem Social Bookmarking-Dienst delicious durchgeführt, welcher in Recall- und Precisionwerten für ausschließlich Tag-basierte Suchen resultierte. Außerdem wurden Tags in verschiedenen Stufen bereinigt und auf ihre Retrieval-Effektivität getestet. Testergebnisse zeigen, dass Retrieval in Folksonomies am besten mit kurzen Anfragen funktioniert. Hierbei sind die Recallwerte hoch, die Precisionwerte jedoch eher niedrig. Die Suchfunktion "power tags only" liefert verbesserte Precisionwerte.
    Source
    Information - Wissenschaft und Praxis. 63(2012) H.4, S.273-280
  7. Heckner, M.: Tagging, rating, posting : studying forms of user contribution for web-based information management and information retrieval (2009) 0.01 
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    Abstract
    Die Entstehung von Social Software ermöglicht es Nutzern, in großem Umfang im Netz zu publizieren. Bisher liegen aber nur wenige empirische Befunde zu funktionalen Eigenschaften sowie Qualitätsaspekten von Nutzerbeiträgen im Kontext von Informationsmanagement und Information Retrieval vor. Diese Arbeit diskutiert grundlegende Partizipationsformen, präsentiert empirische Studien über Social Tagging, Blogbeiträge sowie Relevanzbeurteilungen und entwickelt Design und Implementierung einer "sozialen" Informationsarchitektur für ein partizipatives Onlinehilfesystem.
    Content
    The Web of User Contribution - Foundations and Principles of the Social Web - Social Tagging - Rating and Filtering of Digital Resources Empirical Analysisof User Contributions - The Functional and Linguistic Structure of Tags - A Comparative Analysis of Tags for Different Digital Resource Types - Exploring Relevance Assessments in Social IR Systems - Exploring User Contribution Within a Higher Education Scenario - Summary of Empirical Results and Implications for Designing Social Information Systems User Contribution for a Participative Information System - Social Information Architecture for an Online Help System
    RSWK
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
    Subject
    World Wide Web 2.0 / Benutzer / Online-Publizieren / Information Retrieval / Soziale Software / Hilfesystem
  8. Peters, I.: Folksonomies : indexing and retrieval in Web 2.0 (2009) 0.01 
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    Abstract
    Kollaborative Informationsdienste im Web 2.0 werden von den Internetnutzern nicht nur dazu genutzt, digitale Informationsressourcen zu produzieren, sondern auch, um sie inhaltlich mit eigenen Schlagworten, sog. Tags, zu erschließen. Dabei müssen die Nutzer nicht wie bei Bibliothekskatalogen auf Regeln achten. Die Menge an nutzergenerierten Tags innerhalb eines Kollaborativen Informationsdienstes wird als Folksonomy bezeichnet. Die Folksonomies dienen den Nutzern zum Wiederauffinden eigener Ressourcen und für die Recherche nach fremden Ressourcen. Das Buch beschäftigt sich mit Kollaborativen Informationsdiensten, Folksonomies als Methode der Wissensrepräsentation und als Werkzeug des Information Retrievals.
    Footnote
    Zugl.: Düsseldorf, Univ., Diss., 2009 u.d.T.: Peters, Isabella: Folksonomies in Wissensrepräsentation und Information Retrieval Rez. in: IWP - Information Wissenschaft & Praxis, 61(2010) Heft 8, S.469-470 (U. Spree): "... Nachdem sich die Rezensentin durch 418 Seiten Text hindurch gelesen hat, bleibt sie unentschieden, wie der auffällige Einsatz langer Zitate (im Durchschnitt drei Zitate, die länger als vier kleingedruckte Zeilen sind, pro Seite) zu bewerten ist, zumal die Zitate nicht selten rein illustrativen Charakter haben bzw. Isabella Peters noch einmal zitiert, was sie bereits in eigenen Worten ausgedrückt hat. Redundanz und Verlängerung der Lesezeit halten sich hier die Waage mit der Möglichkeit, dass sich die Leserin einen unmittelbaren Eindruck von Sprache und Duktus der zitierten Literatur verschaffen kann. Eindeutig unschön ist das Beenden eines Gedankens oder einer Argumentation durch ein Zitat (z. B. S. 170). Im deutschen Original entstehen auf diese Weise die für deutsche wissenschaftliche Qualifikationsarbeiten typischen denglischen Texte. Für alle, die sich für Wissensrepräsentation, Information Retrieval und kollaborative Informationsdienste interessieren, ist "Folksonomies : Indexing and Retrieval in Web 2.0" trotz der angeführten kleinen Mängel zur Lektüre und Anschaffung - wegen seines beinahe enzyklopädischen Charakters auch als Nachschlage- oder Referenzwerk geeignet - unbedingt zu empfehlen. Abschließend möchte ich mich in einem Punkt der Produktinfo von de Gruyter uneingeschränkt anschließen: ein "Grundlagenwerk für Folksonomies".
    RSWK
    Information Retrieval
    Series
    Knowledge and information : studies in information science
    Subject
    Information Retrieval
  9. 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) 0.01 
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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
  10. Bentley, C.M.; Labelle, P.R.: ¬A comparison of social tagging designs and user participation (2008) 0.01 
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    Abstract
    Social tagging empowers users to categorize content in a personally meaningful way while harnessing their potential to contribute to a collaborative construction of knowledge (Vander Wal, 2007). In addition, social tagging systems offer innovative filtering mechanisms that facilitate resource discovery and browsing (Mathes, 2004). As a result, social tags may support online communication, informal or intended learning as well as the development of online communities. The purpose of this mixed methods study is to examine how undergraduate students participate in social tagging activities in order to learn about their motivations, behaviours and practices. A better understanding of their knowledge, habits and interactions with such systems will help practitioners and developers identify important factors when designing enhancements. In the first phase of the study, students enrolled at a Canadian university completed 103 questionnaires. Quantitative results focusing on general familiarity with social tagging, frequently used Web 2.0 sites, and the purpose for engaging in social tagging activities were compiled. Eight questionnaire respondents participated in follow-up semi-structured interviews that further explored tagging practices by situating questionnaire responses within concrete experiences using popular websites such as YouTube, Facebook, Del.icio.us, and Flickr. Preliminary results of this study echo findings found in the growing literature concerning social tagging from the fields of computer science (Sen et al., 2006) and information science (Golder & Huberman, 2006; Macgregor & McCulloch, 2006). Generally, two classes of social taggers emerge: those who focus on tagging for individual purposes, and those who view tagging as a way to share or communicate meaning to others. Heavy del.icio.us users, for example, were often focused on simply organizing their own content, and seemed to be conscientiously maintaining their own personally relevant categorizations while, in many cases, placing little importance on the tags of others. Conversely, users tagging items primarily to share content preferred to use specific terms to optimize retrieval and discovery by others. Our findings should inform practitioners of how interaction design can be tailored for different tagging systems applications, and how these findings are positioned within the current debate surrounding social tagging among the resource discovery community. We also hope to direct future research in the field to place a greater importance on exploring the benefits of tagging as a socially-driven endeavour rather than uniquely as a means of managing information.
    Source
    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  11. Tennis, J.T.: Measured time : imposing a temporal metric to classificatory structures 0.01 
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    Abstract
    Describes three units of time helpful for understanding and evaluating classificatory structures: long time (versions and states of classification schemes), short time (the act of indexing as repeated ritual or form), and micro-time (where stages of the interpretation process of indexing are separated out and inventoried). Concludes with a short discussion of how time and the impermanence of classification also conjures up an artistic conceptualization of indexing, and briefly uses that to question the seemingly dominant understanding of classification practice as outcome of scientific management and assembly line thought.
  12. Trant, J.; Bearman, D.: Social terminology enhancement through vernacular engagement : exploring collaborative annotation to encourage interaction with museum collections (2005) 0.01 
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    Abstract
    From their earliest encounters with the Web, museums have seen an opportunity to move beyond uni-directional communication into an environment that engages their users and reflects a multiplicity of perspectives. Shedding the "Unassailable Voice" (Walsh 1997) in favor of many "Points of View" (Sledge 1995) has challenged traditional museum approaches to the creation and delivery of content. Novel approaches are required in order to develop and sustain user engagement (Durbin 2004). New models of exhibit creation that democratize the curatorial functions of object selection and interpretation offer one way of opening up the museum (Coldicutt and Streten 2005). Another is to use the museum as a forum and focus for community story-telling (Howard, Pratty et al. 2005). Unfortunately, museum collections remain relatively inaccessible even when 'made available' through searchable on-line databases. Museum documentation seldom satisfies the on-line access needs of the broad public, both because it is written using professional terminology and because it may not address what is important to - or remembered by - the museum visitor. For example, an exhibition now on-line at The Metropolitan Museum of Art acknowledges "Coco" Chanel only in the brief, textual introduction (The Metropolitan Museum of Art 2005a). All of the images of her delightful fashion designs are attributed to "Gabrielle Chanel" (The Metropolitan Museum of Art 2005a). Interfaces that organize collections along axes of time or place - such of that of the Timeline of Art History (The Metropolitan Museum of Art 2005e) - often fail to match users' world-views, despite the care that went into their structuring or their significant pedagogical utility. Critically, as professionals working with art museums we realize that when cataloguers and curators describe works of art, they usually do not include the "subject" of the image itself. Simply put, we rarely answer the question "What is it a picture of?" Unfortunately, visitors will often remember a work based on its visual characteristics, only to find that Web-based searches for any of the things they recall do not produce results.
  13. Nov, O.; Naaman, M.; Ye, C.: Analysis of participation in an online photo-sharing community : a multidimensional perspective (2010) 0.01 
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    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
  14. Vaidya, P.; Harinarayana, N.S.: ¬The comparative and analytical study of LibraryThing tags with Library of Congress Subject Headings (2016) 0.01 
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    Abstract
    The internet in its Web 2.0 version has given an opportunity among users to be participative and the chance to enhance the existing system, which makes it dynamic and collaborative. The activity of social tagging among researchers to organize the digital resources is an interesting study among information professionals. The one way of organizing the resources for future retrieval through these user-generated terms makes an interesting analysis by comparing them with professionally created controlled vocabularies. Here in this study, an attempt has been made to compare Library of Congress Subject Headings (LCSH) terms with LibraryThing social tags. In this comparative analysis, the results show that social tags can be used to enhance the metadata for information retrieval. But still, the uncontrolled nature of social tags is a concern and creates uncertainty among researchers.
  15. Choi, N.; Joo, S.: Booklovers' world : an examination of factors affecting continued usage of social cataloging sites (2016) 0.01 
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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
  16. Peters, I.: Folksonomies und kollaborative Informationsdienste : eine Alternative zur Websuche? (2011) 0.01 
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    Abstract
    Folksonomies ermöglichen den Nutzern in Kollaborativen Informationsdiensten den Zugang zu verschiedenartigen Informationsressourcen. In welchen Fällen beide Bestandteile des Web 2.0 am besten für das Information Retrieval geeignet sind und wo sie die Websuche ggf. ersetzen können, wird in diesem Beitrag diskutiert. Dazu erfolgt eine detaillierte Betrachtung der Reichweite von Social-Bookmarking-Systemen und Sharing-Systemen sowie der Retrievaleffektivität von Folksonomies innerhalb von Kollaborativen Informationsdiensten.
  17. Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014) 0.01 
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    Abstract
    Purpose - The purpose of this paper is to explore the potential of applying the Dewey Decimal Classification (DDC) as an established knowledge organization system (KOS) for enhancing social tagging, with the ultimate purpose of improving subject indexing and information retrieval. Design/methodology/approach - Over 11.000 Intute metadata records in politics were used. Totally, 28 politics students were each given four tasks, in which a total of 60 resources were tagged in two different configurations, one with uncontrolled social tags only and another with uncontrolled social tags as well as suggestions from a controlled vocabulary. The controlled vocabulary was DDC comprising also mappings from the Library of Congress Subject Headings. Findings - The results demonstrate the importance of controlled vocabulary suggestions for indexing and retrieval: to help produce ideas of which tags to use, to make it easier to find focus for the tagging, to ensure consistency and to increase the number of access points in retrieval. The value and usefulness of the suggestions proved to be dependent on the quality of the suggestions, both as to conceptual relevance to the user and as to appropriateness of the terminology. Originality/value - No research has investigated the enhancement of social tagging with suggestions from the DDC, an established KOS, in a user trial, comparing social tagging only and social tagging enhanced with the suggestions. This paper is a final reflection on all aspects of the study.
  18. Sun, A.; Bhowmick, S.S.; Nguyen, K.T.N.; Bai, G.: Tag-based social image retrieval : an empirical evaluation (2011) 0.01 
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    Abstract
    Tags associated with social images are valuable information source for superior image search and retrieval experiences. Although various heuristics are valuable to boost tag-based search for images, there is a lack of general framework to study the impact of these heuristics. Specifically, the task of ranking images matching a given tag query based on their associated tags in descending order of relevance has not been well studied. In this article, we take the first step to propose a generic, flexible, and extensible framework for this task and exploit it for a systematic and comprehensive empirical evaluation of various methods for ranking images. To this end, we identified five orthogonal dimensions to quantify the matching score between a tagged image and a tag query. These five dimensions are: (i) tag relatedness to measure the degree of effectiveness of a tag describing the tagged image; (ii) tag discrimination to quantify the degree of discrimination of a tag with respect to the entire tagged image collection; (iii) tag length normalization analogous to document length normalization in web search; (iv) tag-query matching model for the matching score computation between an image tag and a query tag; and (v) query model for tag query rewriting. For each dimension, we identify a few implementations and evaluate their impact on NUS-WIDE dataset, the largest human-annotated dataset consisting of more than 269K tagged images from Flickr. We evaluated 81 single-tag queries and 443 multi-tag queries over 288 search methods and systematically compare their performances using standard metrics including Precision at top-K, Mean Average Precision (MAP), Recall, and Normalized Discounted Cumulative Gain (NDCG).
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.12, S.2364-2381
  19. Knautz, K.; Stock, W.G.: Collective indexing of emotions in videos (2011) 0.01 
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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.
  20. Danowski, P.: Authority files and Web 2.0 : Wikipedia and the PND. An Example (2007) 0.01 
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    Abstract
    More and more users index everything on their own in the web 2.0. There are services for links, videos, pictures, books, encyclopaedic articles and scientific articles. All these services are library independent. But must that really be? Can't libraries help with their experience and tools to make user indexing better? On the experience of a project from German language Wikipedia together with the German person authority files (Personen Namen Datei - PND) located at German National Library (Deutsche Nationalbibliothek) I would like to show what is possible. How users can and will use the authority files, if we let them. We will take a look how the project worked and what we can learn for future projects. Conclusions - Authority files can have a role in the web 2.0 - there must be an open interface/ service for retrieval - everything that is indexed on the net with authority files can be easy integrated in a federated search - O'Reilly: You have to found ways that your data get more important that more it will be used
    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".

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