Datasets:
File size: 1,735 Bytes
297188b 802a691 297188b 802a691 297188b 802a691 297188b 802a691 297188b 802a691 297188b 56185d3 297188b 56185d3 | 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 | ---
dataset_info:
features:
- name: data_id
dtype: string
- name: text
dtype: string
- name: exact
dtype: string
- name: group
dtype: string
- name: ternary
dtype: string
- name: binary
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 14338723
num_examples: 31318
- name: val
num_bytes: 1545579
num_examples: 3355
- name: test
num_bytes: 3285868
num_examples: 7282
download_size: 4686461
dataset_size: 19170170
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
- split: test
path: data/test-*
license: mit
task_categories:
- text-classification
language:
- ru
size_categories:
- 10K<n<100K
---
This is a derivative dataset from `psytechlab/presuisidal_antisuisidal_dataset-master` that used in the paper experiments "The methodology of constructing the large-scale dataset for detecting presuicidal and anti-suicidal signals in social media texts in Russian".
The preprocessing list:
* removed all classes that have less than 100 examples
* the `re.sub("[^А-Яа-я ]+", "", x)` has been applied to all texts
* all multilabel text was removed
The dataset has all class granularity levels:
* exact - the full class name with upper group and specialization
* group - the group class only (applicable to a presuisidal part)
* ternary - presuisidal, antisuisidal and irrelevant
* binary - relevant and irrelevant
In the paper experiments the presuisidal and antisuisidal parts share the irrelevant texts. The texts from presuisidal part are not marked as irrelevant for antisuisidal dataset and vice versa, only natural `irrelevant` texts are used. |