Description
Analyzing Persuasion Strategies of Debaters on Social Media - Dataset
This dataset contains 3,801 debaters from Reddit, their comment, and their persuasion effectiveness. The debates originate from the subreddit Chage my View and are extracted from the Webis CMV dataset (Al Khatib et al., 2020). The dataset consists of three files in JSON Lines (.jsonl) format.
Content of the Dataset
+-- Reddit Debaters
| +-- README.md # This information + file format description
| +-- debaters.jsonl # Minimal dataset with only the (source) comment text and persuasiveness
| +-- debaters-full.jsonl # All debater-level datapoints, computed an retrieved from Reddit
| +-- comments.jsonl # All comments and comment-level datapoints for each debater
Cite
@inproceedings{wiegmann:2022,
title = "Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task Learning",
author = "Wiegmann, Matti and Al-Khatib, Khalid and Khanna, Vishal and Stein, Benno",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
}
This dataset contains 3,801 debaters from Reddit, their comment, and their persuasion effectiveness. The debates originate from the subreddit Chage my View and are extracted from the Webis CMV dataset (Al Khatib et al., 2020). The dataset consists of three files in JSON Lines (.jsonl) format.
Content of the Dataset
+-- Reddit Debaters
| +-- README.md # This information + file format description
| +-- debaters.jsonl # Minimal dataset with only the (source) comment text and persuasiveness
| +-- debaters-full.jsonl # All debater-level datapoints, computed an retrieved from Reddit
| +-- comments.jsonl # All comments and comment-level datapoints for each debater
Cite
@inproceedings{wiegmann:2022,
title = "Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task Learning",
author = "Wiegmann, Matti and Al-Khatib, Khalid and Khanna, Vishal and Stein, Benno",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
}
| Date made available | 30-Aug-2022 |
|---|---|
| Publisher | ZENODO |
Research output
- 1 Conference contribution
-
Analyzing Persuasion Strategies of Debaters on Social Media
Wiegmann, M., Al Khatib, K., Khanna, V. & Stein, B., Oct-2022, Proceedings of the 29th International Conference on Computational Linguistics. International Committee on Computational Linguistics, p. 6897–6905 9 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile
Cite this
- DataSetCite