---
dataset_info:
  features:
   - name: unique_ID
     dtype: large_string
   - name: ID
     dtype: large_string
   - name: text_ID
     dtype: int64
   - name: subcorpus
     dtype: large_string
   - name: author
     dtype: large_string
   - name: date
     dtype: timestamp[ms]
   - name: Text
     dtype: large_string
   - name: text_tokenised
     dtype: large_string
   - name: token_count
     dtype: int64
   - name: similar_IDs
     list: string
   - name: annotation_prompt
     dtype: large_string
   - name: annotation_model
     dtype: large_string
   - name: annotation_temperature
     dtype: float64
   - name: annotation_top_p
     dtype: float64
   - name: annotation_max_model_len
     dtype: int64
   - name: synthetic_labels
     list:
     - name: Aspekt
       dtype: string
     - name: Sentimentbegriff
       dtype: string
     - name: Valenz
       dtype: string
     - name: Erregung
       dtype: string
   - name: messages
     list:
     - name: role
       dtype: string
     - name: content
       dtype: string
  splits:
  - name: train
    num_bytes: 28892954
    num_examples: 3934
  - name: test
    num_bytes: 3434382
    num_examples: 463
  - name: dev
    num_bytes: 1751377
    num_examples: 232
  download_size: 12609414
  dataset_size: 35883436
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
  - split: dev
    path: data/dev-*
language:
- de
size_categories:
- 1K<n<10K
---

# AfD-CCC
A corpus of short texts and parliamentary speech transcripts by the German political party "Alternative für Deutschland" (AfD) addressing the topic of climate change (CC). The collection process and some exemplary usecases of the corpus are outlined in the associated paper and master's thesis. All data sources are clearly demarked in the following section.

## Data Sources
**Documents are taken from the original repository at [github.com/discourse-lab/afd-ccc](https://github.com/discourse-lab/afd-ccc/).**
> Manfred Stede and Ronja Memminger. 2025. [AfD-CCC: Analyzing the Climate Change Discourse of a German Right-wing Political Party.](https://aclanthology.org/2025.nlp4pi-1.14/) In Proceedings of the Fourth Workshop on NLP for Positive Impact (NLP4PI), pages 163–174, Vienna, Austria. Association for Computational Linguistics.

- German Parliament speeches (2017-2022): Extracted from [OpenDiscourse](https://dataverse.harvard.edu/citation?persistentId=doi:10.7910/DVN/FIKIBO              ) (Richter et al., 2020)
- German Parliament speeches (2022-2025): Retrieved from Government records via the [DIP API](https://dip.bundestag.de).
- European Parliament speeches (2014-2024): Extracted from the [ParlLawSpeech](https://parllawspeech.org/) dataset, Version 1.0 (Schwabach et al., 2025)
- Telegram messages (2019-2025): Scraped from public channels using [FROG](https://journals.sagepub.com/doi/10.1177/20501579241244973              ) (Priming & Fröschl, 2024)
- Press releases (2017-2021): Extracted from press releases made available by Schaefer et al. (2023)
- ~~Tweets (2017-2022): From Lasser et al. (2022). Due to Twitter privacy regulations, only tweet IDs can be given.~~ (Excluded due to missing documents.)

## Corpus Statistics

| **Text Domain**    | **Texts** | **Tokens**  | **Annotated texts** | **Total # synthetic labels**  |
| :------------- | ----: | ------: | ------: | ------: |
| German Parl.   | 2,284 | 220,894 | 2,197   | 12,332  |
| European Parl. | 668   | 48,025  | 659     | 3,017   |
| Press releases | 911   | 85,356  | 896     | 5,012   |
| ~~Twitter~~    | ~~1,880~~ | ~~54,592~~ | - | -      |
| Telegram       | 766   | 41,487  | 748     | 3,297   |
| **Total**      | **4,629** | **395,762** | **4,500** | **23,658** |