Dataset Open Access
Same Side Stance Classification Resampled Datasets
Gregor Wiedemann;
Erik Körner;
Ahmad Dawar Hakimi;
Gerhard Heyer;
Martin Potthast
The resampled datasets for the Same Side Stance Classification problem used in the EMNLP'21 paper "On Classifying whether Two Texts are on the Same Side of an Argument".
The data is based on the publicly available S3C training datasets.
The data format is JSONlines.
Python Load Example: (for every single task split)
import pandas as pd
df_cross_dev = pd.read_json("cross_dev.jsonl", lines=True)For details on how the data was compiled, please refer to our code.
Files
(252.9 MB)
| Name | Size | |
|---|---|---|
|
experiment1.zip
md5:4074f6d0fbf2b2b78b70a1a1f696aaba |
109.6 MB | Download |
|
experiment2.zip
md5:b53c3b98b3a6985beeb03cf4211db3a7 |
143.2 MB | Download |
62
11
views
downloads
| All versions | This version | |
|---|---|---|
| Views | 62 | 62 |
| Downloads | 11 | 11 |
| Data volume | 1.4 GB | 1.4 GB |
| Unique views | 44 | 44 |
| Unique downloads | 8 | 8 |
Indexed in
- Publication date:
- September 9, 2021
- DOI:
-
- Keyword(s):
- Same Side Stance Classification Computational Argumentation
- Related identifiers:
- Derived from
- 10.5281/zenodo.4382352 (Dataset)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International