File size: 17,269 Bytes
1e05a11 95bd71e 1e05a11 95bd71e 461c99a 014fb2f 28cc847 2ae7b4b a12a206 3482581 d4ea85e d6b9dbe ee3e2ad 27f38c8 23041dc 9787ace 77a6a8e 769fa74 c814137 95bd71e 461c99a 95bd71e 461c99a 014fb2f 28cc847 2ae7b4b a12a206 3482581 d4ea85e d6b9dbe ee3e2ad 27f38c8 23041dc 9787ace 77a6a8e 769fa74 c814137 1e05a11 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 |
---
language:
- af
- ar
- de
- en
- es
- ha
- hi
- id
- ig
- jv
- mr
- pcm
- pt
- ro
- ru
- rw
- su
- sv
- sw
- tt
- uk
- vmw
- xh
- yo
- zh
- zu
license: cc-by-4.0
configs:
- config_name: afr
data_files:
- split: train
path: afr/train-*
- split: dev
path: afr/dev-*
- split: test
path: afr/test-*
- config_name: arq
data_files:
- split: train
path: arq/train-*
- split: dev
path: arq/dev-*
- split: test
path: arq/test-*
- config_name: ary
data_files:
- split: train
path: ary/train-*
- split: dev
path: ary/dev-*
- split: test
path: ary/test-*
- config_name: chn
data_files:
- split: train
path: chn/train-*
- split: dev
path: chn/dev-*
- split: test
path: chn/test-*
- config_name: deu
data_files:
- split: train
path: deu/train-*
- split: dev
path: deu/dev-*
- split: test
path: deu/test-*
- config_name: eng
data_files:
- split: train
path: eng/train-*
- split: dev
path: eng/dev-*
- split: test
path: eng/test-*
- config_name: esp
data_files:
- split: train
path: esp/train-*
- split: dev
path: esp/dev-*
- split: test
path: esp/test-*
- config_name: hau
data_files:
- split: train
path: hau/train-*
- split: dev
path: hau/dev-*
- split: test
path: hau/test-*
- config_name: hin
data_files:
- split: train
path: hin/train-*
- split: dev
path: hin/dev-*
- split: test
path: hin/test-*
- config_name: ibo
data_files:
- split: train
path: ibo/train-*
- split: dev
path: ibo/dev-*
- split: test
path: ibo/test-*
- config_name: ind
data_files:
- split: dev
path: ind/dev-*
- split: test
path: ind/test-*
- config_name: jav
data_files:
- split: dev
path: jav/dev-*
- split: test
path: jav/test-*
- config_name: kin
data_files:
- split: train
path: kin/train-*
- split: dev
path: kin/dev-*
- split: test
path: kin/test-*
- config_name: mar
data_files:
- split: train
path: mar/train-*
- split: dev
path: mar/dev-*
- split: test
path: mar/test-*
- config_name: pcm
data_files:
- split: train
path: pcm/train-*
- split: dev
path: pcm/dev-*
- split: test
path: pcm/test-*
- config_name: ptbr
data_files:
- split: train
path: ptbr/train-*
- split: dev
path: ptbr/dev-*
- split: test
path: ptbr/test-*
dataset_info:
- config_name: afr
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 257404
num_examples: 1222
- name: dev
num_bytes: 37574
num_examples: 196
- name: test
num_bytes: 443868
num_examples: 2130
download_size: 185339
dataset_size: 738846
- config_name: arq
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 189788
num_examples: 901
- name: dev
num_bytes: 38340
num_examples: 200
- name: test
num_bytes: 375933
num_examples: 1804
download_size: 180591
dataset_size: 604061
- config_name: ary
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 338711
num_examples: 1608
- name: dev
num_bytes: 102370
num_examples: 534
- name: test
num_bytes: 338423
num_examples: 1624
download_size: 267222
dataset_size: 779504
- config_name: chn
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 556515
num_examples: 2642
- name: dev
num_bytes: 76681
num_examples: 400
- name: test
num_bytes: 1101127
num_examples: 5284
download_size: 789776
dataset_size: 1734323
- config_name: deu
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 548300
num_examples: 2603
- name: dev
num_bytes: 76681
num_examples: 400
- name: test
num_bytes: 1085289
num_examples: 5208
download_size: 894088
dataset_size: 1710270
- config_name: eng
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 583056
num_examples: 2768
- name: dev
num_bytes: 44475
num_examples: 232
- name: test
num_bytes: 1153224
num_examples: 5534
download_size: 402232
dataset_size: 1780755
- config_name: esp
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 420441
num_examples: 1996
- name: dev
num_bytes: 70547
num_examples: 368
- name: test
num_bytes: 706438
num_examples: 3390
download_size: 216719
dataset_size: 1197426
- config_name: hau
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 451826
num_examples: 2145
- name: dev
num_bytes: 136493
num_examples: 712
- name: test
num_bytes: 450120
num_examples: 2160
download_size: 258761
dataset_size: 1038439
- config_name: hin
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 538400
num_examples: 2556
- name: dev
num_bytes: 38340
num_examples: 200
- name: test
num_bytes: 420945
num_examples: 2020
download_size: 377557
dataset_size: 997685
- config_name: ibo
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 606648
num_examples: 2880
- name: dev
num_bytes: 183653
num_examples: 958
- name: test
num_bytes: 601827
num_examples: 2888
download_size: 266394
dataset_size: 1392128
- config_name: ind
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: dev
num_bytes: 29905
num_examples: 156
- name: test
num_bytes: 177339
num_examples: 851
download_size: 77485
dataset_size: 207244
- config_name: jav
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: dev
num_bytes: 28947
num_examples: 151
- name: test
num_bytes: 174421
num_examples: 837
download_size: 83743
dataset_size: 203368
- config_name: kin
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 516283
num_examples: 2451
- name: dev
num_bytes: 156047
num_examples: 814
- name: test
num_bytes: 513053
num_examples: 2462
download_size: 430821
dataset_size: 1185383
- config_name: mar
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 508699
num_examples: 2415
- name: dev
num_bytes: 38340
num_examples: 200
- name: test
num_bytes: 416777
num_examples: 2000
download_size: 348097
dataset_size: 963816
- config_name: pcm
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 785272
num_examples: 3728
- name: dev
num_bytes: 237713
num_examples: 1240
- name: test
num_bytes: 779374
num_examples: 3740
download_size: 574462
dataset_size: 1802359
- config_name: ptbr
features:
- name: id
dtype: string
- name: text
dtype: string
- name: anger
dtype: int64
- name: disgust
dtype: int64
- name: fear
dtype: int64
- name: joy
dtype: int64
- name: sadness
dtype: int64
- name: surprise
dtype: int64
- name: emotions
list: string
splits:
- name: train
num_bytes: 468888
num_examples: 2226
- name: dev
num_bytes: 76681
num_examples: 400
- name: test
num_bytes: 927747
num_examples: 4452
download_size: 455209
dataset_size: 1473316
---
# BRIGHTER Emotion Categories Dataset
This dataset contains the emotion categories data from the BRIGHTER paper: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages.
## Dataset Description
The BRIGHTER Emotion Categories dataset is a comprehensive multi-language, multi-label emotion classification dataset with separate configurations for each language. It represents one of the largest human-annotated emotion datasets across multiple languages.
- **Total languages**: 28 languages
- **Total examples**: 139595
- **Splits**: train, dev, test
## About BRIGHTER
BRIGHTER addresses the gap in human-annotated textual emotion recognition datasets for low-resource languages. While most existing emotion datasets focus on English, BRIGHTER covers multiple languages, including many low-resource ones. The dataset was created by selecting text from various sources and having annotators label six categorical emotions: anger, disgust, fear, joy, sadness, and surprise.
The dataset contains text in the following languages: Afrikaans, Algerian Arabic, Moroccan Arabic, Mandarin Chinese, German, English, Spanish (Ecuador, Colombia, Mexico), Hausa, Hindi, Igbo, Indonesian, Javanese, Kinyarwanda, Marathi, Nigerian Pidgin, Portuguese (Brazil), Portuguese (Mozambique), Romanian, Russian, Sundanese, Swahili, Swedish, Tatar, Ukrainian, Makhuwa, Xhosa, Yoruba, and Zulu.
## Language Configurations
Each language is available as a separate configuration with the following statistics:
| Original Code | ISO Code | Train Examples | Dev Examples | Test Examples | Total |
|---------------|----------|---------------|-------------|--------------|-------|
| afr | af | 1222 | 196 | 2130 | 3548 |
| arq | ar | 901 | 200 | 1804 | 2905 |
| ary | ar | 1608 | 534 | 1624 | 3766 |
| chn | zh | 2642 | 400 | 5284 | 8326 |
| deu | de | 2603 | 400 | 5208 | 8211 |
| eng | en | 2768 | 232 | 5534 | 8534 |
| esp | es | 1996 | 368 | 3390 | 5754 |
| hau | ha | 2145 | 712 | 2160 | 5017 |
| hin | hi | 2556 | 200 | 2020 | 4776 |
| ibo | ig | 2880 | 958 | 2888 | 6726 |
| ind | id | 0 | 156 | 851 | 1007 |
| jav | jv | 0 | 151 | 837 | 988 |
| kin | rw | 2451 | 814 | 2462 | 5727 |
| mar | mr | 2415 | 200 | 2000 | 4615 |
| pcm | pcm | 3728 | 1240 | 3740 | 8708 |
| ptbr | pt | 2226 | 400 | 4452 | 7078 |
| ptmz | pt | 1546 | 514 | 1552 | 3612 |
| ron | ro | 1241 | 246 | 2238 | 3725 |
| rus | ru | 2679 | 398 | 2000 | 5077 |
| sun | su | 924 | 398 | 1852 | 3174 |
| swa | sw | 3307 | 1102 | 3312 | 7721 |
| swe | sv | 1187 | 400 | 2376 | 3963 |
| tat | tt | 1000 | 400 | 2000 | 3400 |
| ukr | uk | 2466 | 498 | 4468 | 7432 |
| vmw | vmw | 1551 | 516 | 1554 | 3621 |
| xho | xh | 0 | 682 | 1594 | 2276 |
| yor | yo | 2992 | 994 | 3000 | 6986 |
| zul | zu | 0 | 875 | 2047 | 2922 |
## Features
- **id**: Unique identifier for each example
- **text**: Text content to classify
- **anger**, **disgust**, **fear**, **joy**, **sadness**, **surprise**: Presence of emotion
- **emotions**: List of emotions present in the text
## Dataset Characteristics
This dataset provides binary labels for emotion presence, making it suitable for multi-label classification tasks. For regression tasks or fine-grained emotion analysis, please see the companion BRIGHTER-emotion-intensities dataset.
## Usage
```python
from datasets import load_dataset
# Load all data for a specific language
eng_dataset = load_dataset("YOUR_USERNAME/BRIGHTER-emotion-categories", "eng")
# Or load a specific split for a language
eng_train = load_dataset("YOUR_USERNAME/BRIGHTER-emotion-categories", "eng", split="train")
```
## Citation
If you use this dataset, please cite the following papers:
```
@misc{muhammad2025brighterbridginggaphumanannotated,
title={BRIGHTER: BRIdging the Gap in Human-Annotated Textual Emotion Recognition Datasets for 28 Languages},
author={Shamsuddeen Hassan Muhammad and Nedjma Ousidhoum and Idris Abdulmumin and Jan Philip Wahle and Terry Ruas and Meriem Beloucif and Christine de Kock and Nirmal Surange and Daniela Teodorescu and Ibrahim Said Ahmad and David Ifeoluwa Adelani and Alham Fikri Aji and Felermino D. M. A. Ali and Ilseyar Alimova and Vladimir Araujo and Nikolay Babakov and Naomi Baes and Ana-Maria Bucur and Andiswa Bukula and Guanqun Cao and Rodrigo Tufiño and Rendi Chevi and Chiamaka Ijeoma Chukwuneke and Alexandra Ciobotaru and Daryna Dementieva and Murja Sani Gadanya and Robert Geislinger and Bela Gipp and Oumaima Hourrane and Oana Ignat and Falalu Ibrahim Lawan and Rooweither Mabuya and Rahmad Mahendra and Vukosi Marivate and Andrew Piper and Alexander Panchenko and Charles Henrique Porto Ferreira and Vitaly Protasov and Samuel Rutunda and Manish Shrivastava and Aura Cristina Udrea and Lilian Diana Awuor Wanzare and Sophie Wu and Florian Valentin Wunderlich and Hanif Muhammad Zhafran and Tianhui Zhang and Yi Zhou and Saif M. Mohammad},
year={2025},
eprint={2502.11926},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2502.11926},
}
```
```
@misc{muhammad2025semeval2025task11bridging,
title={SemEval-2025 Task 11: Bridging the Gap in Text-Based Emotion Detection},
author={Shamsuddeen Hassan Muhammad and Nedjma Ousidhoum and Idris Abdulmumin and Seid Muhie Yimam and Jan Philip Wahle and Terry Ruas and Meriem Beloucif and Christine De Kock and Tadesse Destaw Belay and Ibrahim Said Ahmad and Nirmal Surange and Daniela Teodorescu and David Ifeoluwa Adelani and Alham Fikri Aji and Felermino Ali and Vladimir Araujo and Abinew Ali Ayele and Oana Ignat and Alexander Panchenko and Yi Zhou and Saif M. Mohammad},
year={2025},
eprint={2503.07269},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2503.07269},
}
```
## License
This dataset is licensed under CC-BY 4.0.
|