This map shows the geographic impact of Roman Klinger's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Roman Klinger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roman Klinger more than expected).
This network shows the impact of papers produced by Roman Klinger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Roman Klinger. The network helps show where Roman Klinger may publish in the future.
Co-authorship network of co-authors of Roman Klinger
This figure shows the co-authorship network connecting the top 25 collaborators of Roman Klinger.
A scholar is included among the top collaborators of Roman Klinger based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Roman Klinger. Roman Klinger is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Klinger, Roman, et al.. (2021). Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detection. arXiv (Cornell University). 171–180.2 indexed citations
Klinger, Roman, et al.. (2020). GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception. arXiv (Cornell University). 1554–1566.11 indexed citations
8.
Barnes, Jeremy, Roman Klinger, & Sabine Schulte im Walde. (2018). Projecting Embeddings for Domain Adaption: Joint Modeling of Sentiment Analysis in Diverse Domains. arXiv (Cornell University). 818–830.6 indexed citations
9.
Klinger, Roman, et al.. (2018). An Analysis of Annotated Corpora for Emotion Classification in Text. International Conference on Computational Linguistics. 2104–2119.79 indexed citations
10.
Padó, Sebastian, et al.. (2017). Prototypical Emotion Developments in Adventures, Romances, and Mystery Stories.. DH.2 indexed citations
11.
Sänger, Mario, et al.. (2016). SCARE ― The Sentiment Corpus of App Reviews with Fine-grained Annotations in German.. Language Resources and Evaluation. 1114–1121.4 indexed citations
12.
Klinger, Roman, et al.. (2016). Automatic Emotion Detection for Quantitative Literary Studies.. DH. 826–828.1 indexed citations
Klinger, Roman & Philipp Cimiano. (2013). Bi-directional Inter-dependencies of Subjective Expressions and Targets and their Value for a Joint Model. PUB – Publications at Bielefeld University (Bielefeld University). 848–854.18 indexed citations
15.
Klinger, Roman, et al.. (2012). Improving Distantly Supervised Extraction of Drug-Drug and Protein-Protein Interactions. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).15 indexed citations
16.
Thomas, Philippe, Illés Solt, Roman Klinger, & Ulf Leser. (2011). Learning Protein Protein Interaction Extraction using Distant Supervision. Publikationen an der Universität Bielefeld (Universität Bielefeld). 25–32.4 indexed citations
17.
Gurulingappa, Harsha, Roman Klinger, Martin Hofmann‐Apitius, & Juliane Fluck. (2010). An Empirical Evaluation of Resources for the Identification of Diseases and Adverse Effects in Biomedical Literature. PUB – Publications at Bielefeld University (Bielefeld University).20 indexed citations
18.
Gurulingappa, Harsha, B. G. Müller, Roman Klinger, et al.. (2010). Prior Art Search in Chemistry Patents Based On Semantic Concepts and Co-Citation Analysis.. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft).6 indexed citations
19.
Klinger, Roman & Christoph M. Friedrich. (2009). Feature Subset Selection in Conditional Random Fields for Named Entity Recognition. PUB – Publications at Bielefeld University (Bielefeld University). 185–191.10 indexed citations
20.
Klinger, Roman & Christoph M. Friedrich. (2009). User's Choice of Precision and Recall in Named Entity Recognition. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 192–196.4 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.