Preliminary Results of a Scientometric Analysis of the German Information Retrieval Community 2020-2023
Philipp Schaer, Svetlana Myshkina, J\"uri Keller

TL;DR
This paper presents a scientometric analysis of the German Information Retrieval community from 2020 to 2023, focusing on both information science and computer science sub-fields, with a publicly available dataset.
Contribution
It provides the first comprehensive scientometric study of the German IR community across sub-fields, including data collection, analysis, and a mapping use case.
Findings
Data set of 401 IR-related publications released publicly
Analysis at institutional and researcher levels conducted
Demonstration of a mapping use case
Abstract
The German Information Retrieval community is located in two different sub-fields: Information and computer science. There are no current studies that investigate these communities on a scientometric level. Available studies only focus on the information scientific part of the community. We generated a data set of 401 recent IR-related publications extracted from six core IR conferences from a mainly computer scientific background. We analyze this data set at the institutional and researcher level. The data set is publicly released, and we also demonstrate a mapping use case.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsLibraries and Information Services · Research Data Management Practices · Scientific Research and Philosophical Inquiry
MethodsFocus
