Die vielen Gesichter von GESIS


Nina Smirnova is a research associate at the department Knowledge Technologies for the Social Sciences (KTS) in team Information & Data Retrieval. She graduated from the University of Bonn with a Master's degree in Applied Linguistics. Her spheres of interest lie in the fields of computational linguistics and data science. She is strongly interested and have an expertise in Natural Language Processing, more specifically in Information Extraction and Classification, and Machine Learning.



Biesenbender, Kristin, Nina Smirnova, Philipp Mayr, and Isabella Peters. 2024. "The Emergence of Preprints: Comparing Publishing Behaviour in the Global South and the Global North." Online Information Review online first. doi:

Mir, Aasif Ahmad, Nina Smirnova, Jeyshankar Ramalingam, and Philipp Mayr. 2024. "The rise of Indo-German collaborative research: 1990-2022." Global Knowledge, Memory and Communication online first. doi:

Smirnova, Nina, and Philipp Mayr. 2023. "A comprehensive analysis of acknowledgement texts in Web of Science: a case study on four scientific domains." Scientometrics 128 (1): 709–734. doi:

Smirnova, Nina, and Philipp Mayr. 2023. "Embedding models for supervised automatic extraction and classification of named entities in scientific acknowledgements." Scientometrics online first. doi:

Beitrag im Sammelwerk

Smirnova, Nina, and Philipp Mayr. 2022. "Evaluation of Embedding Models for Automatic Extraction and Classification of Acknowledged Entities in Scientific Documents." In Proceedings of the 3rd Workshop on Extraction and Evaluation of Knowledge Entities from Scientific Documents (EEKE 2022) , edited by Chengzhi Zhang, Philipp Mayr, Wei Lu, and Yi Zhang, 48-55. Aachen: CEUR.


Culbert, Jack, Nina Smirnova, and Philipp Mayr-Schlegel. 2024. Indo-German Literature Dataset. doi:

Smirnova, Nina. 2024. Multilingual classification model to detect texts from the political science domain.

Smirnova, Nina. 2023. English classification model to detect texts from the political science domain.

Smirnova, Nina. 2023. English NER model for extraction of named entities from scientific acknowledgement texts using Flair Embeddings.


Smirnova, Nina. 2024. "Filtering metadata with AI methods - the use of BASE in the FID Political Science ." 112th BiblioCon2024 , 2024-06-06.

Smirnova, Nina. 2023. "Evaluation of unsupervised approaches for named entity recognition in scientific publications." ISSI – the International Society for Informetrics and Scientometrics, 8th ISSI Doctoral Forum , Indiana University in Bloomington, Bloomington, IN, 2023-07-02.

Beitrag nicht auf Konferenz

Smirnova, Nina. 2023. "Embedding Models for Supervised Automatic Extraction and Classification of Named Entities in Scientific Acknowledgements." NLP-2023, Warsaw University of Technology, Warsaw , 2023-10-11.