Meme Descriptions: I Can Has Cheezburger?
A Meme Descriptions (Cheezburger dataset) dataset of 252,284 meme descriptions and 117 images, collected by Wang and Wen via Cheezburger (2015). Each record contains meme image and text descriptions, popularity scores. The dataset is notable for its multimodal dataset for meme popularity prediction and generation. Intended for research into multimodal learning, meme generation, popularity prediction, and computational humor.
Cite this dataset at
meme-descriptions.echo.directory
Analytics
5.4
Flesch–Kincaid grade
US school grade level
4.5
Automated readability index
surelikegoodtellstoppeoplefacebookletmemeworkusecomestupidknowgirlplaywanttimelovedonnewguybadmemesrealgirlsactuallygaytrollinghotfunnyfriendsstayshitlifeinternetgettinglookleavesleeppostschoolphonemanblackjustindiegoingrightfat
Topic 0
Topic 1
Topic 2
Topic 3
Topic 4
Topic 5
Topic 6
Topic 7
Topic 8
Topic 9
Topic 10
Topic 11
Show all 248 topics
Topic 12
Topic 13
Topic 14
Topic 15
Topic 16
Topic 17
Topic 18
Topic 19
Topic 20
Topic 21
Topic 22
Topic 23
Topic 24
Topic 25
Topic 26
Topic 27
Topic 28
Topic 29
Topic 30
Topic 31
Topic 32
Topic 33
Topic 34
Topic 35
Topic 36
Topic 37
Topic 38
Topic 39
Topic 40
Topic 41
Topic 42
Topic 43
Topic 44
Topic 45
Topic 46
Topic 47
Topic 48
Topic 49
Topic 50
Topic 51
Topic 52
Topic 53
Topic 54
Topic 55
Topic 56
Topic 57
Topic 58
Topic 59
Topic 60
Topic 61
Topic 62
Topic 63
Topic 64
Topic 65
Topic 66
Topic 67
Topic 68
Topic 69
Topic 70
Topic 71
Topic 72
Topic 73
Topic 74
Topic 75
Topic 76
Topic 77
Topic 78
Topic 79
Topic 80
Topic 81
Topic 82
Topic 83
Topic 84
Topic 85
Topic 86
Topic 87
Topic 88
Topic 89
Topic 90
Topic 91
Topic 92
Topic 93
Topic 94
Topic 95
Topic 96
Topic 97
Topic 98
Topic 99
Topic 100
Topic 101
Topic 102
Topic 103
Topic 104
Topic 105
Topic 106
Topic 107
Topic 108
Topic 109
Topic 110
Topic 111
Topic 112
Topic 113
Topic 114
Topic 115
Topic 116
Topic 117
Topic 118
Topic 119
Topic 120
Topic 121
Topic 122
Topic 123
Topic 124
Topic 125
Topic 126
Topic 127
Topic 128
Topic 129
Topic 130
Topic 131
Topic 132
Topic 133
Topic 134
Topic 135
Topic 136
Topic 137
Topic 138
Topic 139
Topic 140
Topic 141
Topic 142
Topic 143
Topic 144
Topic 145
Topic 146
Topic 147
Topic 148
Topic 149
Topic 150
Topic 151
Topic 152
Topic 153
Topic 154
Topic 155
Topic 156
Topic 157
Topic 158
Topic 159
Topic 160
Topic 161
Topic 162
Topic 163
Topic 164
Topic 165
Topic 166
Topic 167
Topic 168
Topic 169
Topic 170
Topic 171
Topic 172
Topic 173
Topic 174
Topic 175
Topic 176
Topic 177
Topic 178
Topic 179
Topic 180
Topic 181
Topic 182
Topic 183
Topic 184
Topic 185
Topic 186
Topic 187
Topic 188
Topic 189
Topic 190
Topic 191
Topic 192
Topic 193
Topic 194
Topic 195
Topic 196
Topic 197
Topic 198
Topic 199
Topic 200
Topic 201
Topic 202
Topic 203
Topic 204
Topic 205
Topic 206
Topic 207
Topic 208
Topic 209
Topic 210
Topic 211
Topic 212
Topic 213
Topic 214
Topic 215
Topic 216
Topic 217
Topic 218
Topic 219
Topic 220
Topic 221
Topic 222
Topic 223
Topic 224
Topic 225
Topic 226
Topic 227
Topic 228
Topic 229
Topic 230
Topic 231
Topic 232
Topic 233
Topic 234
Topic 235
Topic 236
Topic 237
Topic 238
Topic 239
Topic 240
Topic 241
Topic 242
Topic 243
Topic 244
Topic 245
Topic 246
Topic 247
117
Images
Sampled: text metrics from 50K of 252.3K records; topic model from 20K.
Record
- Catalog key
meme-descriptions- Authors
- Wang, William Yang; Wen, Miaomiao
- Year
- 2015
- Source paper
- I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions
- DOI / arXiv
- 10.3115/v1/n15-1039
- License
- Academic use (see UCSB) (LicenseRef-Research-Only)
- Records
- 252,284
- Text corpus
- meme description text
- Languages
- en
- Collected
- 2015 (2010s)
Provenance
- Originally published at
- https://sites.cs.ucsb.edu/~william/software.html link checked
- Hosted copy
- Mirrored on echo.directory on 2026-10-09, 47.6 MB across 130 files. Checksums in MANIFEST.json.
Citations
I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions
William Yang Wang, Miao-Miao Wen
Journal Article · North American Chapter of the Association for Computational Linguistics · 2015
39
citations
cited
1
influential citations
3% of all citations
Cited by
- On the Origins of Memes by Means of Fringe Web Communities
Savvas Zannettou, T. Caulfield et al. · ACM/SIGCOMM Internet Measurement Conference · 2018 · cited 313× - Do Androids Laugh at Electric Sheep? Humor “Understanding” Benchmarks from The New Yorker Caption Contest
Jack Hessel, Ana Marasović et al. · Annual Meeting of the Association for Computational Linguistics · 2022 · cited 157× - The evolution of political memes: Detecting and characterizing internet memes with multi-modal deep learning
David M. Beskow, Sumeet Kumar et al. · Information Processing & Management · 2020 · cited 134× - Understanding image virality
Arturo Deza, Devi Parikh · Computer Vision and Pattern Recognition · 2015 · cited 104× - MemeCap: A Dataset for Captioning and Interpreting Memes
Eunjeong Hwang, V. Shwartz · Conference on Empirical Methods in Natural Language Processing · 2023 · cited 81×
Show all 10
- We are Humor Beings: Understanding and Predicting Visual Humor
Arjun Chandrasekaran, Ashwin K. Vijayakumar et al. · Computer Vision and Pattern Recognition · 2015 · cited 67× - A Dataset for Troll Classification of TamilMemes
Shardul Suryawanshi, Bharathi Raja Chakravarthi et al. · WILDRE · 2020 · cited 66× - “My Way of Telling a Story”: Persona based Grounded Story Generation
Shrimai Prabhumoye, Khyathi Raghavi Chandu et al. · Proceedings of the Second Workshop on Storytelling · 2019 · cited 37× - MemeCraft: Contextual and Stance-Driven Multimodal Meme Generation
Han Wang, Roy Ka-Wei Lee · The Web Conference · 2024 · cited 27× - Meme Classification Using Textual and Visual Features
E. S. Smitha, S. Sendhilkumar et al. · 2018 · cited 20×
Citation data from Semantic Scholar, retrieved 2026-10-19.
How to cite
BibTeX
@misc{echo2026,
title = {ECHO: Exploratory Compendium of Humanity Online},
author = {Switzer, Braden and Zafarani, Reza},
year = {2026},
url = {https://echo.directory},
note = {Syracuse University}
}
@inproceedings{wang2015cheezburger,
title = {I Can Has Cheezburger? A Nonparanormal Approach to Combining Textual and Visual Information for Predicting and Generating Popular Meme Descriptions},
author = {Wang, William Yang and Wen, Miaomiao},
booktitle = {NAACL HLT},
year = {2015}
} APA
Switzer, B., & Zafarani, R. (2026). ECHO: Exploratory Compendium of Humanity Online [Data repository]. Syracuse University. https://echo.directory
Wang, W. Y., & Wen, M. (2015). Meme Descriptions: I Can Has Cheezburger? [Data set]. https://doi.org/10.3115/v1/n15-1039
MLA
Switzer, Braden, and Reza Zafarani. ECHO: Exploratory Compendium of Humanity Online. Syracuse University, 2026, echo.directory.
Wang, William Yang, and Miaomiao Wen. Meme Descriptions: I Can Has Cheezburger? 2015, doi.org/10.3115/v1/n15-1039.