---
_id: '6944'
article_type: original
author:
- first_name: Christoph
  full_name: Weisser, Christoph
  id: '264138'
  last_name: Weisser
  orcid: 0000-0003-0616-1027
  orcid_put_code_url: https://api.orcid.org/v2.0/0000-0003-0616-1027/work/216491994
- first_name: Christoph
  full_name: Gerloff, Christoph
  last_name: Gerloff
- first_name: Anton
  full_name: Thielmann, Anton
  last_name: Thielmann
- first_name: Benjamin
  full_name: Säfken, Benjamin
  last_name: Säfken
- first_name: Andre
  full_name: Python, Andre
  last_name: Python
- first_name: Thomas
  full_name: Kneib, Thomas
  last_name: Kneib
- first_name: Arik
  full_name: Reuter, Arik
  last_name: Reuter
citation:
  alphadin: '<span style="font-variant:small-caps;">Weisser, Christoph</span> ; <span
    style="font-variant:small-caps;">Gerloff, Christoph</span> ; <span style="font-variant:small-caps;">Thielmann,
    Anton</span> ; <span style="font-variant:small-caps;">Säfken, Benjamin</span>
    ; <span style="font-variant:small-caps;">Python, Andre</span> ; <span style="font-variant:small-caps;">Kneib,
    Thomas</span> ; <span style="font-variant:small-caps;">Reuter, Arik</span>: Pseudo-Document
    Simulation Method for Topic Model Evaluation on Short and Sparse Text Using Twitter
    Data. In: <i>Computational Statistics</i> Bd. 38, Springer (2023), Nr. 4, S. 647–674'
  ama: Weisser C, Gerloff C, Thielmann A, et al. Pseudo-Document Simulation Method
    for Topic Model Evaluation on Short and Sparse Text Using Twitter Data. <i>Computational
    Statistics</i>. 2023;38(4):647-674. doi:<a href="https://doi.org/10.1007/s00180-022-01246-z">10.1007/s00180-022-01246-z</a>
  apa: Weisser, C., Gerloff, C., Thielmann, A., Säfken, B., Python, A., Kneib, T.,
    &#38; Reuter, A. (2023). Pseudo-Document Simulation Method for Topic Model Evaluation
    on Short and Sparse Text Using Twitter Data. <i>Computational Statistics</i>,
    <i>38</i>(4), 647–674. <a href="https://doi.org/10.1007/s00180-022-01246-z">https://doi.org/10.1007/s00180-022-01246-z</a>
  bibtex: '@article{Weisser_Gerloff_Thielmann_Säfken_Python_Kneib_Reuter_2023, title={Pseudo-Document
    Simulation Method for Topic Model Evaluation on Short and Sparse Text Using Twitter
    Data}, volume={38}, DOI={<a href="https://doi.org/10.1007/s00180-022-01246-z">10.1007/s00180-022-01246-z</a>},
    number={4}, journal={Computational Statistics}, publisher={Springer}, author={Weisser,
    Christoph and Gerloff, Christoph and Thielmann, Anton and Säfken, Benjamin and
    Python, Andre and Kneib, Thomas and Reuter, Arik}, year={2023}, pages={647–674}
    }'
  chicago: 'Weisser, Christoph, Christoph Gerloff, Anton Thielmann, Benjamin Säfken,
    Andre Python, Thomas Kneib, and Arik Reuter. “Pseudo-Document Simulation Method
    for Topic Model Evaluation on Short and Sparse Text Using Twitter Data.” <i>Computational
    Statistics</i> 38, no. 4 (2023): 647–74. <a href="https://doi.org/10.1007/s00180-022-01246-z">https://doi.org/10.1007/s00180-022-01246-z</a>.'
  ieee: C. Weisser <i>et al.</i>, “Pseudo-Document Simulation Method for Topic Model
    Evaluation on Short and Sparse Text Using Twitter Data,” <i>Computational Statistics</i>,
    vol. 38, no. 4, pp. 647–674, 2023.
  mla: Weisser, Christoph, et al. “Pseudo-Document Simulation Method for Topic Model
    Evaluation on Short and Sparse Text Using Twitter Data.” <i>Computational Statistics</i>,
    vol. 38, no. 4, Springer, 2023, pp. 647–74, doi:<a href="https://doi.org/10.1007/s00180-022-01246-z">10.1007/s00180-022-01246-z</a>.
  short: C. Weisser, C. Gerloff, A. Thielmann, B. Säfken, A. Python, T. Kneib, A.
    Reuter, Computational Statistics 38 (2023) 647–674.
date_created: 2026-06-01T13:56:37Z
date_updated: 2026-06-02T12:19:56Z
doi: 10.1007/s00180-022-01246-z
intvolume: '        38'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
oa: '1'
page: 647-674
publication: Computational Statistics
publication_identifier:
  eissn:
  - 1613-9658
  issn:
  - 0943-4062
publication_status: published
publisher: Springer
quality_controlled: '1'
status: public
title: Pseudo-Document Simulation Method for Topic Model Evaluation on Short and Sparse
  Text Using Twitter Data
type: journal_article
user_id: '220548'
volume: 38
year: '2023'
...