Daniel Wiechmann
- Artificial Intelligence top 10%
- Language and Linguistics top 5%
- Developmental and Educational Psychology top 10%
- Experimental and Cognitive Psychology
- Cognitive Neuroscience
- Co-authors
- Elma KerzYu QiaoArne LohmannNeal SniderMarkus StrohmaierT. Florian JaegerStella NeumannThorsten Hennig‐Thurau
- Topics
- Natural Language Processing Techniques (18 papers)Topic Modeling (10 papers)Text Readability and Simplification (9 papers)
- Partner nations
- GermanyNetherlandsAustria
In The Last Decade
Daniel Wiechmann
37 papers receiving 352 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 201
- Language and Linguistics 134
- Developmental and Educational Psychology 92
- Experimental and Cognitive Psychology 63
- Cognitive Neuroscience 49
Countries citing papers authored by Daniel Wiechmann
This map shows the geographic impact of Daniel Wiechmann'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 Daniel Wiechmann with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Wiechmann more than expected).
Fields of papers citing papers by Daniel Wiechmann
This network shows the impact of papers produced by Daniel Wiechmann. 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 Daniel Wiechmann. The network helps show where Daniel Wiechmann may publish in the future.
Co-authorship network of co-authors of Daniel Wiechmann
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Wiechmann. A scholar is included among the top collaborators of Daniel Wiechmann 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 Daniel Wiechmann. Daniel Wiechmann is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 24 | |
| 3 | 2 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | Automated Classification of Written Proficiency Levels on the CEFR-Scale through Complexity Contours and RNNs | 2 |
| 8 | 9 | |
| 9 | Language that Captivates the Audience : Predicting Affective Ratings of TED Talks in a Multi-Label Classification Task | 3 |
| 10 | 18 | |
| 11 | 20 | |
| 12 | A Language-Based Approach to Fake News Detection Through Interpretable Features and BRNN | 12 |
| 13 | Understanding the Dynamics of Second Language Writing through Keystroke Logging and Complexity Contours. | 2 |
| 14 | 2 | |
| 15 | 12 | |
| 16 | Tuning to Multiple Statistics: Second Language Processing of Multiword Sequences across Registers | 1 |
| 17 | Text Genre Classification Based on Linguistic Complexity Contours Using A Recurrent Neural Network. | 9 |
| 18 | 4 | |
| 19 | 8 | |
| 20 | 66 |
About Daniel Wiechmann
Daniel Wiechmann is a scholar working on Developmental and Educational Psychology, Artificial Intelligence and Language and Linguistics, having authored 37 papers that have together received 370 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (18 papers), Topic Modeling (10 papers) and Text Readability and Simplification (9 papers). The work is most often cited by research in Language and Linguistics (134 citations), Linguistics and Language (41 citations) and Developmental and Educational Psychology (92 citations). Daniel Wiechmann has collaborated with scholars based in Germany, Netherlands and Austria. Frequent co-authors include Elma Kerz, Yu Qiao, Arne Lohmann, Neal Snider, Markus Strohmaier, T. Florian Jaeger, Stella Neumann, Thorsten Hennig‐Thurau and Morten H. Christiansen. Their work appears in journals such as Cognitive Science, Language Learning and Studies in Second Language Acquisition.
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.