Datasets:

Sub-tasks:
fact-checking
Languages:
Danish
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
stance-detection
License:
File size: 7,115 Bytes
860dff5
 
4b32d07
860dff5
 
c497f85
860dff5
c497f85
860dff5
 
 
 
 
 
 
 
1075212
860dff5
1075212
356c1be
860dff5
1075212
 
 
 
860dff5
 
676b713
860dff5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
676b713
860dff5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
31d778b
860dff5
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
paperswithcode_id: dast
pretty_name: DAST
extra_gated_prompt: 'Warning: the data in this repository contains harmful content
  (misinformative claims).'
tags:
- stance-detection
---

# Dataset Card for "dkstance / DAST"

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [https://stromberg.ai/publication/jointrumourstanceandveracity/](https://stromberg.ai/publication/jointrumourstanceandveracity/)
- **Repository:** [https://figshare.com/articles/dataset/Danish_stance-annotated_Reddit_dataset/8217137](https://figshare.com/articles/dataset/Danish_stance-annotated_Reddit_dataset/8217137)
- **Paper:** [https://aclanthology.org/W19-6122/](https://aclanthology.org/W19-6122/)
- **Point of Contact:** [Leon Derczynski](https://github.com/leondz)
- **Size of downloaded dataset files:** 
- **Size of the generated dataset:** 
- **Total amount of disk used:** 

### Dataset Summary

This is an SDQC stance-annotated Reddit dataset for the Danish language generated within a thesis project. The dataset consists of over 5000 comments structured as comment trees and linked to 33 source posts.

The dataset is applicable for supervised stance classification and rumour veracity prediction.

### Supported Tasks and Leaderboards

* Stance prediction

### Languages



## Dataset Structure

### Data Instances

#### DAST / dkstance

- **Size of downloaded dataset files:** 4.72 MiB
- **Size of the generated dataset:** 3.69 MiB
- **Total amount of disk used:**  8.41 MiB

An example of 'train' looks as follows.

```
{
  'id': '1', 
  'native_id': 'ebwjq5z', 
  'text': 'Med de udfordringer som daginstitutionerne har med normeringer, og økonomi i det hele taget, synes jeg det er en vanvittig beslutning at prioritere skattebetalt vegansk kost i daginstitutionerne. Brug dog pengene på noget mere personale, og lad folk selv betale for deres individuelle kostønsker.', 
  'parent_id': 'a6o3us', 
  'parent_text': 'Mai Mercado om mad i daginstitutioner: Sund kost rimer ikke på veganer-mad', 
  'parent_stance': 0, 
  'source_id': 'a6o3us', 
  'source_text': 'Mai Mercado om mad i daginstitutioner: Sund kost rimer ikke på veganer-mad', 
  'source_stance': 0
}
```


### Data Fields

- `id`: a `string` feature.
- `native_id`: a `string` feature representing the native ID of the entry.
- `text`: a `string` of the comment text in which stance is annotated.
- `parent_id`: the `native_id` of this comment's parent.
- `parent_text`: a `string` of the parent comment's text.
- `parent_stance`: the label of the stance in the comment towards its parent comment.

```
                            0: "Supporting",
                            1: "Denying",
                            2: "Querying",
                            3: "Commenting",
```

- `source_id`: the `native_id` of this comment's source / post.
- `source_text`: a `string` of the source / post text.
- `source_stance`: the label of the stance in the comment towards the original source post.

```
                            0: "Supporting",
                            1: "Denying",
                            2: "Querying",
                            3: "Commenting",
```

### Data Splits

|  name   |size|
|---------|----:|
|train|3122|
|validation|1066|
|test|1060|

These splits are specified after the original reserach was reported. The splits add an extra level of rigour, in that no source posts' comment tree is spread over more than one partition.

## Dataset Creation

### Curation Rationale

Comments around rumourous claims to enable rumour and stance analysis in Danish

### Source Data

#### Initial Data Collection and Normalization

The data is from Reddit posts that relate to one of a specific set of news stories; these stories are enumerated in the paper. 

#### Who are the source language producers?

Danish-speaking Twitter users.

### Annotations

#### Annotation process

There was multi-user annotation process mediated through a purpose-built interface for annotating stance in Reddit threads.

#### Who are the annotators?

* Age: 20-30.
* Gender: male.
* Race/ethnicity: white northern European.
* Native language: Danish.
* Socioeconomic status: higher education student.

### Personal and Sensitive Information

The data was public at the time of collection. User names are not preserved.

## Considerations for Using the Data

### Social Impact of Dataset

There's a risk of user-deleted content being in this data. The data has NOT been vetted for any content, so there's a risk of harmful text.

### Discussion of Biases

The source of the text has a strong demographic bias, being mostly young white men who are vocal their opinions. This constrains both the styles of language and discussion contained in the data, as well as the topics discussed and viewpoints held.

### Other Known Limitations

The above limitations apply.

## Additional Information

### Dataset Curators

The dataset is curated by the paper's authors.

### Licensing Information

The authors distribute this data under Creative Commons attribution license, CC-BY 4.0. 
An NLP data statement is included in the paper describing the work, [https://aclanthology.org/W19-6122.pdf](https://aclanthology.org/W19-6122.pdf)

### Citation Information

```
@inproceedings{lillie-etal-2019-joint,
    title = "Joint Rumour Stance and Veracity Prediction",
    author = "Lillie, Anders Edelbo  and
      Middelboe, Emil Refsgaard  and
      Derczynski, Leon",
    booktitle = "Proceedings of the 22nd Nordic Conference on Computational Linguistics",
    month = sep # "{--}" # oct,
    year = "2019",
    address = "Turku, Finland",
    publisher = {Link{\"o}ping University Electronic Press},
    url = "https://aclanthology.org/W19-6122",
    pages = "208--221",
}
```


### Contributions

Author-added dataset [@leondz](https://github.com/leondz)