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cimt-thematic-categorization-dataset

January 17, 2022 (corpus version 1.0)

About

This directory contains a dataset for thematic categorization of transport-related public participation contributions. The dataset is part of the CIMT PartEval Corpus and is further described in the publication "A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification", to be published in Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022).

This work is based on research in the project CIMT/Partizipationsnutzen, which is funded by the Federal Ministry of Education and Research as part of its Social-Ecological Research funding priority, funding no. 01UU1904. (for more information, visit https://www.cimt-hhu.de/en/)

Content

Each of the folders (one per public participation process) contains the coded dataset and the corresponding terms of use. The dataset csv-files contain one entry per document with the following information.

document_id: document id

title: title of contribution

text: content of contribution

url: original url of document

categories: binary coding (1 if category applies, 0 else)

Categorization Scheme

-- modes of transport --

main categories:

  • non-motorized transport
  • motorized transport

sub-category of non-motorized transport

  • cycling
  • walking
  • scooters

sub-category of motorized transport

  • public transport (local)
  • public transport (long-distance)
  • commercial transport

-- specifications --

  • moving traffic
  • stationary traffic (parking)
  • new services
  • inter- and multimodality

More detailed information can be found in the paper.

Citation

If you use the dataset, please cite the following paper:

Julia Romberg, Laura Mark, and Tobias Escher. 2022. A Corpus of German Citizen Contributions in Mobility Planning: Supporting Evaluation Through Multidimensional Classification. In Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022), Marseille, France. European Language Resources Association (ELRA).

License

The annotated data corpus is available under the Creative Commons CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0/).

Contact Person

Julia Romberg, [email protected], https://www.cimt-hhu.de/en/team/romberg/