Datasets:

Modalities:
Image
Text
Formats:
parquet
ArXiv:
Libraries:
Datasets
pandas
License:
File size: 4,737 Bytes
42002c2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
bc81b34
 
7315cbe
bc81b34
 
 
 
 
 
 
 
 
 
 
 
7315cbe
bc81b34
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7315cbe
 
 
bc81b34
 
 
 
 
 
 
 
7315cbe
bc81b34
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: cc-by-nc-sa-4.0
dataset_info:
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: image
    dtype: image
  - name: img_path
    dtype: string
  - name: prop_label
    dtype:
      class_label:
        names:
          '0': not_propaganda
          '1': propaganda
  - name: hate_label
    dtype:
      class_label:
        names:
          '0': not-hateful
          '1': hateful
  - name: hate_fine_grained_label
    dtype:
      class_label:
        names:
          '0': sarcasm
          '1': humor
          '2': inciting_violence
          '3': mocking
          '4': other
          '5': exclusion
          '6': dehumanizing
          '7': contempt
          '8': inferiority
          '9': slurs
  splits:
  - name: train
    num_bytes: 156541594.307
    num_examples: 2143
  - name: dev
    num_bytes: 21725452.0
    num_examples: 312
  - name: test
    num_bytes: 45373687.0
    num_examples: 606
  download_size: 221704545
  dataset_size: 223640733.307
---
# Prop2Hate-Meme

This repository presents the first *Arabic* **Prop2Hate-Meme** dataset which explore the intersection of propaganda and hate in memes using a multi-agent LLM-based framework. We extend an existing propagandistic meme dataset by annotating it with fine- and coarse-grained hate speech labels, and provide baseline experiments to support future research.

![License](https://img.shields.io/badge/license-CC--BY--NC--SA-blue) [![Paper](https://img.shields.io/badge/Paper-Download%20PDF-green)](https://arxiv.org/pdf/2409.07246)

**Table of contents:**
  * [Dataset](#dataset)
  * [Licensing](#licensing)
  * [Citation](#citation)

---
## Dataset
We adopted the ArMeme dataset for both fine- and coarse-grained hatefulness categorization. We preserved the original train, development, and test splits. While ArMeme was initially annotated with four labels, for this study we retained only the memes labeled as propaganda and not_propaganda. These were subsequently re-annotated with hatefulness categories. The data distribution is provided below.


---

### 📊 Dataset Statistics

#### 🏋️‍♂️ **Train Split**

**`prop_label`**

* `propaganda`: **603**
* `not_propaganda`: **1540**

**`hate_label`**

* `not-hateful`: **1930**
* `hateful`: **213**

**`hate_fine_grained_label`**

* `sarcasm`: **105**
* `humor`: **1815**
* `inciting violence`: **13**
* `mocking`: **133**
* `other`: **10**
* `exclusion`: **6**
* `dehumanizing`: **12**
* `contempt`: **38**
* `inferiority`: **4**
* `slurs`: **7**

---

#### 🧪 **Dev Split**

**`prop_label`**

* `not_propaganda`: **224**
* `propaganda`: **88**

**`hate_label`**

* `not-hateful`: **281**
* `hateful`: **31**

**`hate_fine_grained_label`**

* `humor`: **260**
* `sarcasm`: **19**
* `mocking`: **19**
* `contempt`: **7**
* `other`: **1**
* `dehumanizing`: **2**
* `inferiority`: **1**
* `slurs`: **1**
* `inciting violence`: **2**

---

#### 🧾 **Dev-Test Split (`dev_test`)**

**`prop_label`**

* `not_propaganda`: **436**
* `propaganda`: **170**

**`hate_label`**

* `not-hateful`: **452**
* `hateful`: **154**

**`hate_fine_grained_label`**

* `humor`: **334**
* `sarcasm`: **118**
* `inciting violence`: **12**
* `slurs`: **29**
* `other`: **20**
* `mocking`: **49**
* `contempt`: **25**
* `inferiority`: **14**
* `dehumanizing`: **2**
* `exclusion`: **3**

---

## Experimental Scripts
Please find the experimental scripts here: [https://github.com/firojalam/propaganda-and-hateful-memes.git](https://github.com/firojalam/propaganda-and-hateful-memes.git)


## Licensing

This dataset is licensed under CC BY-NC-SA 4.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/

## Citation
If you use our dataset in a scientific publication, we would appreciate using the following citations:

[![Paper](https://img.shields.io/badge/Paper-Download%20PDF-green)](https://arxiv.org/pdf/2409.07246)

```
@inproceedings{alam2024propaganda,
  title={Propaganda to Hate: A Multimodal Analysis of Arabic Memes with Multi-agent LLMs},
  author={Alam, Firoj and Biswas, Md Rafiul and Shah, Uzair and Zaghouani, Wajdi and Mikros, Georgios},
  booktitle={International Conference on Web Information Systems Engineering},
  pages={380--390},
  year={2024},
  organization={Springer}
}

@inproceedings{alam2024armeme,
  title={{ArMeme}: Propagandistic Content in Arabic Memes},
  author={Alam, Firoj and Hasnat, Abul and Ahmed, Fatema and Hasan, Md Arid and Hasanain, Maram},
  booktitle={Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP)},
  year={2024},
  address={Miami, Florida},
  month={November 12--16},
  publisher={Association for Computational Linguistics},
}
```