Publikationen

Hier finden Sie von Know-Center MitarbeiterInnen verfasste wissenschaftliche Publikationen

2015

Kraker Peter, Schlögl Christian, Jack Kris, Lindstaedt Stefanie

The Quest for Keeping an Overview: Knowledge Domain Visualizations based on Co-Readership Patterns

2015

Given the enormous amount of scientific knowledge that is produced each and every day, the need for better ways of gaining–and keeping–an overview of research fields is becoming more and more apparent. In a recent paper published in the Journal of Informetrics [1], we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating such overviews. First, we investigated the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we used co-readership patterns to map the field of educational technology. The resulting knowledge domain visualization, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
2015

Kraker Peter, Lindstaedt Stefanie , Schlögl C., Jack K.

Visualization of co-readership patterns from an online reference management system

Journal of Informetrics, Elsevier, NULL, 2015

Journal
In this paper, we analyze the adequacy and applicability of readership statistics recorded in social reference management systems for creating knowledge domain visualizations. First, we investigate the distribution of subject areas in user libraries of educational technology researchers on Mendeley. The results show that around 69% of the publications in an average user library can be attributed to a single subject area. Then, we use co-readership patterns to map the field of educational technology. The resulting visualization prototype, based on the most read publications in this field on Mendeley, reveals 13 topic areas of educational technology research. The visualization is a recent representation of the field: 80% of the publications included were published within ten years of data collection. The characteristics of the readers, however, introduce certain biases to the visualization. Knowledge domain visualizations based on readership statistics are therefore multifaceted and timely, but it is important that the characteristics of the underlying sample are made transparent.
2015

Kraker Peter, Schlögl C. , Jack K., Lindstaedt Stefanie

The Quest for Keeping an Overview: Knowledge Domain Visualizations based on Co-Readership Patterns

In: Science 2.0, IEEE Computer Society Special Technical Community on Social Networking E-Letter, vol. 3, no. 1, 2015

Journal
Given the enormous amount of scientific knowledgethat is produced each and every day, the need for better waysof gaining – and keeping – an overview of research fields isbecoming more and more apparent. In a recent paper publishedin the Journal of Informetrics [1], we analyze the adequacy andapplicability of readership statistics recorded in social referencemanagement systems for creating such overviews. First, weinvestigated the distribution of subject areas in user librariesof educational technology researchers on Mendeley. The resultsshow that around 69% of the publications in an average userlibrary can be attributed to a single subject area. Then, we usedco-readership patterns to map the field of educational technology.The resulting knowledge domain visualization, based on the mostread publications in this field on Mendeley, reveals 13 topicareas of educational technology research. The visualization isa recent representation of the field: 80% of the publicationsincluded were published within ten years of data collection. Thecharacteristics of the readers, however, introduce certain biasesto the visualization. Knowledge domain visualizations based onreadership statistics are therefore multifaceted and timely, but itis important that the characteristics of the underlying sample aremade transparent.
2013

Kraker Peter, Trattner Christoph, Jack Kris, Lindstaedt Stefanie , Schlgl Christian

Head Start: Improving Academic Literature Search with Overview Visualizations based on Readership Statistics

Web Science 2013, 2013

Konferenz
At the beginning of a scientific study, it is usually quite hardto get an overview of a research field. We aim to addressthis problem of classic literature search using web data. Inthis extended abstract, we present work-in-progress on aninteractive visualization of research fields based on readershipstatistics from the social reference management systemMendeley. To that end, we use library co-occurrences as ameasure of subject similarity. In a first evaluation, we findthat the visualization covers current research areas withineducational technology but presents a view that is biasedby the characteristics of readers. With our presentation, wehope to elicit feedback from the Websci’13 audience on (1)the usefulness of the prototype, and (2) how to overcomethe aforementioned biases using collaborative constructiontechniques.
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