MultiLabeled Depression English 57000 Tweet negation words

Aug 21, 2026

A dataset of multi-labeled English tweet samples focused on negation-related wording in the context of depression. The file organizes a large collection of entries (about 57,000) into labeled records suitable for natural language processing tasks such as text classification, feature analysis, and model training. It supports studying how negation cues interact with depressive language signals, enabling controlled evaluation of labeling and predictive performance.

LanguageEnglish

CategoryResearch & Report

FormatXLSX

Pages1

Reading Time3 min

AccessFree to download

Dataset Overview

Labeling Scope

Negation Word Focus

Dataset Size and Usage

0 1 2 3 4 5 6 3 7 5 8 3 9 3 10 3 11 3 12 3 13 3 14 3 15 3 16 3 17 3 18 3 19 5 20 5 21 3 22 5 23 3 24 3 25 3 26 3 27 3 28 3 29 3 30 3 31 3 32 3 33 3 34 3 35 36 37 3 38 3 39 3 40 3 41 3 42 3 43 3 44 36 45 3 46 3 47 3 48 3 49 3 50 3 51 3 52 3 53 3 54 3 55 3 56 3 57 3 58 5 59 36 60 3 61 5 62 3 63 3 64 36 65 3 66 3 67 3 68 3 69 3 70 3 71 5 72 3 73 3 74 3 75 3 69 3 76 3 77 3 78 3 73 3 79 3 80 36 81 3 82 3 79 3 83 3 84 5 85 3 86 3 87 3 88 3 89 3 90 3 91 3 92 3 93 3 94 3 95 3 96 3 97 36 98 3 99 3 100 3 101 3 102 36 103 5 104 5 105 3 106 3 107 5 108 36 109 36 110 3 111 3 112 3 113 3 114 3 115 3 116 3 117 3 79 3 118 5 119 3 120 3 121 3 122 3 123 3 124 3 125 3 126 3 127 3 128 3 129 5 130 5 131 3 132 3 133 3 134 3 135 3 136 5 137 5 138 3 139 3 140 3 141 3 142 3 143 3 144 3 145 3 146 3 147 3 148 3 149 3 150 3 151 3 152 3 153 3 154 5 155 3 156 5 157 3 158 5 159 3 160 5 161 3 162 5 163 5 164 3 165 3 166 3 167 3 168 3 169 5 170 3 171 3 172 3 173 5 174 3 175 3 176 3 177 3 178 3 179 5 180 3 181 3 182 3 183 3 184 3 185 3 186 3 187 5 188 3 189 3 190 3 191 5 192 3 193 5 194 5 195 3 196 3 79 3 197 5 198 3 199 3 200 3 201 5 202 5 203 3 204 3 205 3 206 3 207 5 208 3 209 3 210 5 211 5 212 3 213 5 214 3 215 36 216 3 200 3 217 3 218 3 219 3 220 3 221 5 222 36 223 3 224 3 225 3 226 3 227 3 228 3 229 36 79 3 230 3 231 3 232 3 233 3 234 36 235 5 236 3 237 3 238 3 239 3 240 3 241 36 242 5 243 5 244 3 245 3 246 36 247 3 79 3 248 3 249 36 250 3 251 5 252 3 253 36 254 3 255 3 256 3 257 3 258 3 259 3 260 3 261 36 262 3 263 3 264 36 265 36 266 3 267 3 268 3 269 3 270 3 271 5 272 3 273 36 274 3 275 3 276 3 79 3 277 3 278 3 279 3 280 3 281 3 282 3 283 3 284 3 285 3 286 3 287 3 288 3 289 3 290 3 291 3 292 5 293 3 294 3 295 3 296 3 297 3 298 3 299 3 300 3 301 3 302 3 303 3 304 3 305 5 306 3 307 3 308 36 309 3 310 3 311 3 312 36 313 3 314 5 315 3 316 3 317 3 318 3 319 3 320 36 321 3 322 3 323 3 324 3 325 3 326 5 327 5 328 3 329 3 330 3 331 5 332 5 333 5 334 3 335 3 336 5 337 3 338 3 339 36 340 3 341 5 342 3 343 3 344 36 345 3 346 3 347 36 348 5 349 5 350 3 351 5 352 3 351 5 353 3 354 5 355 5 356 3 357 5 358 5 359 3 360 3 361 3 362 3 363 3 364 3 365 3 366 3 367 3 368 3 369 3 370 3 371 3 372 36 373 3 374 3 375 3 376 3 377 3 378 3 379 3 380 5 381 3 382 5 383 3 384 5 385 3 386 3 387 5 388 3 389 3 390 3 391 3 392 36 393 3 394 36 395 3 396 3 397 3 398 3 399 3 400 3 401 3 402 3 403 3 404 3 405 3 406 3 407 3 408 3 409 5 410 3 411 3 79 3 412 3 413 36 414 5 415 3 416 3 417 3 418 3 419 5 420 3 421 36 422 3 423 3 424 3 425 3 426 3 427 3 428 36 429 3 430 3 431 3 432 36 433 3 434 3 435 3 436 36 437 3 438 5 439 3 440 3 441 3 442 3 443 3 444 3 445 3 446 3 447 3 448 3 449 3 450 3 451 3 452 3 453 3 454 5 455 3 456 3 457 5 458 3 459 3 460 3 461 3 462 3 463 36 464 3 465 3 466 3 467 3 468 3 469 3 470 5 471 36 472 3 473 3 474 5 475 5 476 3 477 36 478 3 479 3 480 3 481 3 482 3 483 3 484 3 485 36 486 5 487 3 488 3 489 3 490 3 491 3 13 3 492 3 493 36 494 3 495 3 496 3 497 3 498 5 499 3 500 3 501 3 502 3 503 3 504 3 505 3 506 3 507 3 508 5 509 3 510 3 511 5 512 3 513 3 514 5 515 5 516 3 517 3 518 3 519 3 520 3 521 3 522 36 523 5 524 3 525 36 526 3 527 3 79 3 528 5 529 3 530 36 531 5 532 3 533 5 534 3 535 3 536 3 537 5 538 3 539 3 540 3 541 3 542 3 543 3 544 3 545 5 79 3 546 36 547 3 548 5 549 5 550 5 551 5 552 5 553 36 554 3 555 5 556 36 557 5 558 36 559 5 560 5 561 5 562 5 563 5 564 5 565 5 566 5 567 3 568 5 569 5 570 36 571 36 572 36 573 5 574 36 575 5 576 5 577 5 578 36 579 5 580 5 581 5 582 5 583 5 584 3 585 3 586 5 587 36 588 3 589 5 590 5 591 3 592 3 593 3 477 36 477 36 594 5 595 3 596 5 597 3 598 3 599 5 600 5 601 5 602 5 603 3 604 5 605 36 606 36 607 5 608 5 609 3 610 5 611 36 612 5 613 36 614 3 615 5 616 5 617 5 618 5 619 3 620 5 621 5 622 3 623 5 624 5 625 5 626 5 627 5 628 5 629 3 630 5 631 3 632 3 633 5 634 5 635 3 636 5 637 5 638 3 639 3 640 3 641 3 642 3 643 3 644 36 645 5 646 3 647 5 648 3 649 5 650 3 576 5 651 5 652 5 653 36 654 5 655 5 656 3 657 5 658 5 659 5 660 5 661 5 662

FAQs

What does the dataset focus on?

It focuses on English tweet text related to depression, specifically the role of negation wording.

How is the dataset organized?

It is organized into multi-labeled entries so each tweet record can be used for supervised NLP tasks.

What tasks can the dataset support?

It can support text classification, feature analysis of negation cues, and training or evaluation of NLP models.

Aug 21, 2026

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