Sven Buechel

670 total citations
16 papers, 276 citations indexed

About

Sven Buechel is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Social Psychology. According to data from OpenAlex, Sven Buechel has authored 16 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 5 papers in Experimental and Cognitive Psychology and 4 papers in Social Psychology. Recurrent topics in Sven Buechel's work include Sentiment Analysis and Opinion Mining (9 papers), Topic Modeling (8 papers) and Advanced Text Analysis Techniques (4 papers). Sven Buechel is often cited by papers focused on Sentiment Analysis and Opinion Mining (9 papers), Topic Modeling (8 papers) and Advanced Text Analysis Techniques (4 papers). Sven Buechel collaborates with scholars based in Germany, Austria and France. Sven Buechel's co-authors include Udo Hahn, João Sedoc, Lyle Ungar, Anneke Buffone, Orphée De Clercq, Peter Walgenbach, Alexandra Balahur and Stefan Schulz and has published in prestigious journals such as Cognitive Science, Language Resources and Evaluation and arXiv (Cornell University).

In The Last Decade

Sven Buechel

16 papers receiving 252 citations

Peers

Sven Buechel

AI

SP

ECP

MB

SPS

Ethel Ong Philippines

Jeroen Geertzen Netherlands

Luca Soldaini United States

Anil Bandhakavi United Kingdom

Ivan Smirnov Russia

Ivandré Paraboni Brazil

Salvador Climent Spain

Tim Van de Cruys France

Niyati Chhaya United States

Matej Martinc Slovenia

Ethel Ong Philippines

Sven Buechel

118 ×0.5

AI

57 ×0.6

SP

23 ×0.4

ECP

8 ×0.5

MB

16 ×1.1

SPS

Citations per year, relative to Sven Buechel Sven Buechel (= 1×) peers Ethel Ong

Countries citing papers authored by Sven Buechel

Since Specialization

Citations

This map shows the geographic impact of Sven Buechel'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 Sven Buechel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sven Buechel more than expected).

Fields of papers citing papers by Sven Buechel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sven Buechel. 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 Sven Buechel. The network helps show where Sven Buechel may publish in the future.

Co-authorship network of co-authors of Sven Buechel

This figure shows the co-authorship network connecting the top 25 collaborators of Sven Buechel. A scholar is included among the top collaborators of Sven Buechel 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 Sven Buechel. Sven Buechel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

1.

Clercq, Orphée De, et al.. (2021). WASSA 2021 Shared Task: Predicting Empathy and Emotion in Reaction to News Stories.. Ghent University Academic Bibliography (Ghent University). 92–104. 14 indexed citations

2.

Buechel, Sven, et al.. (2018). Sharing Copies of Synthetic Clinical Corpora without Physical Distribution — A Case Study to Get Around IPRs and Privacy Constraints Featuring the German JSYNCC Corpus. Language Resources and Evaluation. 11 indexed citations

3.

Buechel, Sven & Udo Hahn. (2018). Representation Mapping: A Novel Approach to Generate High-Quality Multi-Lingual Emotion Lexicons. Language Resources and Evaluation. 1 indexed citations

4.

Buechel, Sven, et al.. (2018). Towards a Metric for Paraphrastic Modification.. DH. 457–459. 1 indexed citations

5.

Buechel, Sven, et al.. (2018). Inducing Affective Lexical Semantics in Historical Language.. arXiv (Cornell University). 1 indexed citations

6.

Buechel, Sven, et al.. (2018). JeSemE: Interleaving Semantics and Emotions in a Web Service for the Exploration of Language Change Phenomena. International Conference on Computational Linguistics. 10–14. 2 indexed citations

7.

Buechel, Sven, et al.. (2018). A Corpus of Corporate Annual and Social Responsibility Reports: 280 Million Tokens of Balanced Organizational Writing. 10 indexed citations

8.

Buechel, Sven & Udo Hahn. (2018). Word Emotion Induction for Multiple Languages as a Deep Multi-Task Learning Problem. 1907–1918. 13 indexed citations

9.

Buechel, Sven, et al.. (2018). Modeling Empathy and Distress in Reaction to News Stories. 4758–4765. 52 indexed citations

10.

Buechel, Sven & Udo Hahn. (2017). A Flexible Mapping Scheme for Discrete and Dimensional Emotion Representations.. Cognitive Science. 4 indexed citations

11.

Buechel, Sven, et al.. (2017). The Course of Emotion in Three Centuries of German Text-A Methodological Framework.. DH. 1 indexed citations

12.

Buechel, Sven & Udo Hahn. (2017). EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysis. 578–585. 112 indexed citations

13.

Buechel, Sven & Udo Hahn. (2017). Readers vs. Writers vs. Texts: Coping with Different Perspectives of Text Understanding in Emotion Annotation. 1–12. 33 indexed citations

14.

Buechel, Sven, et al.. (2016). Feelings from the Past—Adapting Affective Lexicons for Historical Emotion Analysis. International Conference on Computational Linguistics. 54–61. 12 indexed citations

15.

Buechel, Sven, et al.. (2016). Do Enterprises Have Emotions?. 147–153. 5 indexed citations

16.

Schulz, Stefan, et al.. (2015). JuFiT: A Configurable Rule Engine for Filtering and Generating New Multilingual Umls Terms.. PubMed. 2015. 604–10. 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.

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