Tobias Siebenlist

Applying social bookmarking data to evaluate journal usage

Web 2.0 technologies are finding their way into academics: specialized social bookmarking services allow researchers to store and share scientific literature online. By bookmarking and tagging articles, academic prosumers generate new information about resources, i.e. usage statistics and content description of scientific journals. Given the lack of global download statistics, the authors propose the application of social bookmarking data to journal evaluation. For a set of 45 physics journals all 13,608 bookmarks from CiteULike, Connotea and BibSonomy to documents published between 2004 and 2008 were analyzed. This article explores bookmarking data in STM and examines in how far it can be used to describe the perception of periodicals by the readership. Four basic indicators are defined, which analyze different aspects of usage: Usage Ratio, Usage Diffusion, Article Usage Intensity and Journal Usage Intensity. Tags are analyzed to describe a reader-specific view on journal content.

MEMOSE: search engine for emotions in multimedia documents

The MEMOSE (Media Emotion Search) system is a specialized search engine for fundamental emotions in all kinds of emotional-laden documents. We apply a controlled vocabulary for basic emotions, a slide control to adjust the intensities of the emotions and the approach of broad folksonomies. The paper describes the indexing and the retrieval tool of MEMOSE and results from its evaluation.

Finding emotional-laden resources on the World Wide Web

Some content in multimedia resources can depict or evoke certain emotions in users. The aim of Emotional Information Retrieval (EmIR) and of our research is to identify knowledge about emotional-laden documents and to use these findings in a new kind of World Wide Web information service that allows users to search and browse by emotion. Our prototype, called Media EMOtion SEarch (MEMOSE), is largely based on the results of research regarding emotive music pieces, images and videos. In order to index both evoked and depicted emotions in these three media types and to make them searchable, we work with a controlled vocabulary, slide controls to adjust the emotions’ intensities, and broad folksonomies to identify and separate the correct resource-specific emotions. This separation of so-called power tags is based on a tag distribution which follows either an inverse power law (only one emotion was recognized) or an inverse-logistical shape (two or three emotions were recognized). Both distributions are well known in information science. MEMOSE consists of a tool for tagging basic emotions with the help of slide controls, a processing device to separate power tags, a retrieval component consisting of a search interface (for any topic in combination with one or more emotions) and a results screen. The latter shows two separately ranked lists of items for each media type (depicted and felt emotions), displaying thumbnails of resources, ranked by the mean values of intensity. In the evaluation of the MEMOSE prototype, study participants described our EmIR system as an enjoyable Web 2.0 service.

Cross-metric compatability and inconsistencies of altmetrics

Metrics like the number of tweets or Mendeley readers are currently discussed as an alternative to evaluate research. These alternative metrics (altmetrics) still need to be evaluated in order to fully understand their meaning, their benefits and limitations. While several preceding studies concentrate on correlations of altmetrics with classical measures like citations, this study aims at investigating metric-compatibility within altmetrics. For this purpose, 5000 journal articles from six disciplines have been analyzed regarding their metrics with the help of the aggregators PlumX and Altmetric.com. For this set, the highest numbers of events have been recognized regarding Mendeley readers, followed by Twitter and Facebook mentions. Thereby variations considering the aggregators could be observed. Intra-correlations between the metrics across one aggregator have been calculated, as well as inter-correlations for the corresponding metrics across the aggregators. For both aggregators, low to medium intra-correlations could be calculated which shows the diversity of the different metrics. Regarding inter-correlations, PlumX and Altmetric.com are highly consistent concerning Mendeley readers (

Maturity and usability of open data in North Rhine-Westphalia

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Chapter 15. The critical role of the cold-start problem and incentive systems in emotional Web 2.0 services

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Anaphora Resolution: Analysing the Impact on Mean Average Precision and Detecting Limitations of Automated Approaches

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