Datasets:
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stringclasses 2
values | topic
stringclasses 4
values | content
stringlengths 3
507
| toxic
int64 0
1
| toxic_one_hot
sequencelengths 2
2
| toxic_type
int64 0
2
| toxic_type_one_hot
sequencelengths 2
2
| expression
int64 0
3
| expression_one_hot
sequencelengths 3
3
| target
sequencelengths 5
5
| length
int64 5
507
|
|---|---|---|---|---|---|---|---|---|---|---|
zhihu
|
region
|
ๅฐฑๅญไฝ ็ๅไบฌๆทๅฃๆๅฐฑๆ่งไฝ ๆฏๆ้ซ็บงไบไธช้ถ็บง๏ผๆๆฏๆฒณๅไบบ๐
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 31 |
tieba
|
race
|
ๆ่ซๅคงๆ๏ผไบบไบบๆ่ดฃ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
1,
0
] | 9 |
tieba
|
race
|
ๅฅฝไน
้ฝๆฒกๆ่ง่ฟ้ฃไนๅนฒๅ็็ฝไบบ็ญ็บงไบ๏ผไธไธช้ปไน่ฒ้ฝๆฒกๆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 26 |
zhihu
|
race
|
ๆ่งๅพไธญๅฝๅฅณๆงๅชๅคๅผๅพๆน่ฏ็ๆฏไธญๅฝ็ทๆง๏ผไฝ ไปฌ็ไธ็ๅบ่ฝจ็ๅฅณไบบ็่ๅ
ฌไธ็ๅฐฑๅพ่ฝฏๅผฑ๏ผ่ไปฅๅๅจ็คพไผไธๆทท็็ทไบบ็่ๅฉๆๆฒกๅ็ฐ่ฐๆขๅบ่ฝจ๏ผไธญๅฝ็ทไบบๅฆๆ่ฝๅ้ปไบบๆ็ฉๆฏๆ็ทๆงไธๆ ทๆดๅ๏ผ้ฃไธญๅฝๅฐฑๆฒกๆๅชๅค็่ฏดๆณใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
0
] | 96 |
tieba
|
gender
|
ๅผๅซ่
่ฑช๏ผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 5 |
tieba
|
gender
|
ไบๅฎๅฐฑๆฏ่ฟๆ ท๏ผๅพๅคๅฅณไบบๅคฉๅคฉ่ขซๅฎถๆด๏ผ่ขซๆๅพ้ผป้่ธ่ฟไปไนไผผ็๏ผๅฐๅคๆฑๆจ่ชๅทฑ็ไธๅนธ๏ผไฝๅฐฑๆฏไธ็ฆปๅฉ๏ผๅ่ฟๆฅ่ขซ็ท็ๆงๅจๆๅฟๅจ็ๆฏ็็ๆฏๅคฉๅฐฑๅ็งไธๆปก่ฏด็ท็ไธๅฅฝๅจไธๅจ้น็ฆปๅฉ่ฟๅฏน็ท็ไธๆผๅฎถๅบญๆดๅใ่ฟๅฐฑๆฏ?
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
0,
0
] | 94 |
zhihu
|
race
|
้ฃๅฒไธๆฏๅฉๅญ้ฝไธๅฆ๐ค
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 13 |
zhihu
|
race
|
ไผฐ่ฎกๅทฒ็ปๆไบ้ๆดฒๆ้จ่ฝ็็ฌฌ36ๅท็ๅฆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
1,
0
] | 18 |
tieba
|
gender
|
ๅฏนๅทๅ
ฅๅบงไบ๏ผ่ถๅฃถๅด็ ด้ฒไบ๏ผๆณๅฐ็ๅคไบๅฟ่ไธๅฅฝ็้ฝๆฅๆ่ฟๆฅ็ง้ข้ฒ้
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
0,
0
] | 32 |
zhihu
|
region
|
๐
็ฌๆญป๏ผ่ฝ็ปๆ็ๅ
ธ็ปฟๅกๅ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 15 |
zhihu
|
race
|
ๆไธญๅฝไบบ๏ผไฝ ๅๆฌข้ปไบบ้บป็ฆไฝ ่ตฐ๐ ๐ ๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
1,
0
] | 26 |
zhihu
|
region
|
ๆไธๆฏๆฒณๅไบบ๏ผไฝๆฏๆฌก็ๅฐๆไบบ้ปๅๅฑฑไน่งๅพๆถๅฟ๏ผไธไปถๆๆถๆๆฎด็ๆฎ้ๅไบๆกไปถ่ฝไธ็ญๆๅๅ ไบๅๅคฉ๏ผๅคฉๅคฉ่ฝ็ๅฐ้ชๅๅฑฑ็๏ผ้ฃไธชๅฐๆนๆฒกๆ่ฟ็งไบ๏ผๆฐ้ปไธๅคงๅ ๏ผ้ชไบบ็ฎไปไนๆฌไบ๏ผๆๆฌไบ่ชๅทฑๅปๅถๆญข็ฏ็ฝช๏ผ่ไธๆฏๅฃๅจใๆๆ่งๅฐๅ้ป้ ๆ็็คพไผๅฑๅฎณ่ฟๅคงไบ่ฟไธชๆกไปถๆฌ่บซ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 119 |
tieba
|
gender
|
ๅๆ่ฒ็จๅบฆ่่้ซๅ๏ผๆๅกไธๅ ๆฏ่่ๆๅใ้ฝๅญฆ็ๆฏๆๅกไธไธๆฏๅง
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
0,
1
] | 30 |
tieba
|
lgbt
|
ๅฅฝๅนธ็ฆ๏ผๅ็ฟปๅฟๅ็ฟปๅฟ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 10 |
tieba
|
gender
|
็ชๅคด่ๅๅๅๅๅ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 8 |
zhihu
|
race
|
ไฝ ไปฌไนๅฏไปฅๆไธไธช่ท้ปๅฅณไบคๅพ่ฟ็็ท็็ๅๅๅใๅ
ฌๅนณๅใ๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
1,
0
] | 30 |
tieba
|
gender
|
ไธ่ฆๅบ็ๆฏๅฏนๅฅนไปฌๆๅฅฝ็ไฟๆค
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 13 |
tieba
|
gender
|
่ฏดๆไธไธ๏ผๆๅชๅ
ณ็ฑ่ชๅทฑ่บซ่พน็ๅฅณๆง๏ผๆฏๅฆ่ๅฉๅฅณๅฟ็ญ๏ผๅซ็ๅฅณไบบๅ
ณๆ้ธไบใv
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 35 |
zhihu
|
region
|
ๆ็ฐๅจๅจๆฏไธๆกๅฐๅ้ปๅ็ญไธ้ข้ฝ่ฝ็่งๆตๆฑไบบ๏ผ้ปๅฑฑไธ๏ผๅฑฑ่ฅฟ๏ผๅนฟไธ๏ผๆนๅ๏ผไธๅ๏ผ้ฝๆฏๆตๆฑไบบ๏ผๆๆฏ็็็่งฃไธไบ๏ผๆตๆฑไบบๆฏไธๆฏ้คไบ่ชๅทฑ่ฐ้ฝ็ไธ่ตทๅ๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
1,
0,
0,
0
] | 73 |
zhihu
|
region
|
ไธไธๅฎโฆโฆๅ ไธบๅพๅคไบบไผ็ฑๅฑๅไน๏ผ่ฎจๅไนๅ็ใ ๆฏๅฆ่ฏดๆ่ตทๅฐๆนพไฝ ่ฝๆณๅฐๅจๆฐไผฆ๏ผๅถๅๅงใๆๆฒณๅ99%ๆฏไบ็ๅฟใใใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 55 |
zhihu
|
region
|
่ฟไธช้ฎ้ขไธๆไบบๆไบบๅจๅธฆ่ๅฅ๏ผ้ฃไธชๅซๅกๅฎๅธ
็ท็๏ผๅ
ๅผๆณจๆไธไธ๏ผไปๅจๆๆจ็ฆป้ด๏ผๅ
่ฃ
ๆไธๅไบบๅจๆฒณๅไธบไปไน่ขซๅฐๅ้ป็้ฎ้ขไธ้ชๆฒณๅไบบ๏ผ็ถๅ็งไฟกๅๅคไป็ๆฒณๅไบบๅผๅง้ชไบบ๏ผ็ถๅๆไธคไธชไบบๅฏน้ช็่ฎฐๅฝๆชๅๆฒณๅไบบ้ชไธๅไบบ็็ๆฎตๆพๅจไธๅไบบไธบไปไน่ขซ้ป็้ฎ้ขไธๅธๅผไธๅไบบๆฅ้ชๆฒณๅไบบ๏ผๆๆจไธคไธชๅฐๅบ็ๅ
ณ็ณป
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 135 |
zhihu
|
region
|
๐
็ๅฐไฝ ่ฟ่ฏ่ฎบ๏ผๆ็็ๅฟไธไฝไบ๏ผๆๆไธช็ฉๅพๅพๅฅฝ็ๅไบ๏ผๆไธ็ดไปฅไธบไปๆฏ้ป้พๆฑ็๏ผไปๆ ๅฅ็ไธๆฌกๆฌกๅ่ฏๆ๏ผไปๆฏๅๆ็
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 58 |
zhihu
|
region
|
ๆฏๅฆ่ฏดๅฐ็ฅไนไธๅคง็พ้ฃ่ๆผ ๏ผๅไบฌไบบ็ดๆฅๆฟ่ฎค๏ผ่ฟ่ท็้ช๏ผๆทฑๅณๅคๆฅไบบๅฃๅค๏ผๅฝๅฑๆๅทฎ๏ผไนไธ่ฏดไปไนใๅฏ็ฌๆญๅทไบบ้ฃไธช่ทณ๏ผไฝ ่ฏดๆไปฌ่ๆผ ๆฏๅ ไธบไฝ ๅไธ่ตทๅทดๆๅทดๆ๐ข
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
1,
0,
0,
0
] | 75 |
zhihu
|
race
|
ๆดๆฅ็ผไบๆๅฏไปฅๅนฒ็ช๏ผไฝๆฏไธไผๅนฒๆ่ฟ้ปไบบ็ทๅ็ๅฅณไบบ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
1,
0
] | 24 |
zhihu
|
region
|
ไปไนๅซๆฌๅฐไบบๅนฒ็ๅไบๅ
จ่ตๅฐๅคๅฐไบบๅคดไธ๏ผๆณๅถ่็ฎ้็ฏ็ฝช็ๅบๆฌ้ฝๆฏ่ๅๅฎๅพฝ็๏ผ่บซ่พนไฝๅกๆ็นๅไบ้ฝๆฏๅคๅฐไบบๅนฒ็๏ผๅด่ฏญๅบๆฌๅฐไบบๅฐฑๆๅฐๆๅนฒๅไบ็ไบบ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 68 |
zhihu
|
region
|
Xgๆไบ่ๅนดไบบไนๆฏ้ๆจฃใไธๆข่ไพ่ฉณ็ดฐ่ชช๏ผๆ่ขซ้้ฒๅฐ้ปๅฑใ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 28 |
zhihu
|
lgbt
|
่ฏ่ฏดๅๆฅไฝ ๅ่ฝๆฟๅๆงๆๆไนๆ ทๅข๏ผ๏ผๆๆฌไบๅฐฑๅผๆญปไปไปฌๅใๅ ๅไธไธช๏ผๆ
ขๆ
ขๆฅใๅๆญฃๅฏนไบไฝ ่ฟ็งไปฅๅผบๅๅผฑ็๏ผไนๅฐฑ่ฟไบๆฌไบ่ฟ็งๅฟ่ธไบใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
1,
0,
0,
0,
0
] | 61 |
tieba
|
gender
|
่ฟไธๆฏ50w๏ผ๏ผ๏ผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 9 |
zhihu
|
region
|
่พฝๅฎๅคง่ฟ็๏ผไธ็ดๆณๅคงๅฌๅคฉๅปๅๆ้ฟ็ฝๅฑฑ็
็
๏ผๆๅๅคง้ชๅฐๅฑฑ็ๆ่ง
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 30 |
zhihu
|
race
|
ๆฅๆฌๅฅณไบบ่ดคไธ่ดคๆ ๆไธๅคชๅจไน๏ผๅๆญฃไธญๅฝๅฅณไบบๅทฒ็ป่ท่ดคๅฆป่ฏๆฏไธๆฒพ่พนไบใๅฐๅบฆๅฅณไบบ็ปไธ็ปๅซๅฆๆ ๆ่ฐ๏ผๅๆญฃไธญๅฝ่ฟ่พนๅฝฉ็คผ่ฆ็ป๏ผๅซๅฆไนไธๆฏ็ทไบบ็ใ็พๅฝๅฅณไบบ้็ถๅงไนๆฏๅฐไบๅฟ๏ผๅๆญฃไธญๅฝๅฅณไบบไธไป
ไธๆนๅง๏ผ่ฟ่ฆๆฑๅญฉๅญ่ทๅฅนไปฌๅงใ็ฉๆฏๆๅฅณไบบ่ดไธ่ดๆดไนไธๆฏๆๅ
ณๅฟ็๏ผๅๆญฃไธญๅฝๅฅณไบบไธๅคช่ดๆดไบใไฟ็ฝๆฏไนๅ
ๅ
ฐๅฅณไบบๆผไธๆผไบฎไนๅฐฑ้ฃไนๅไบๅฟ๏ผๅๆญฃไธญๅฝๅฅณไบบๅทฒ็ป้ ็็พ้ขใๅๅฆๅๆไธ็็ฌฌไธไบใ้ๆดฒๅฅณไบบ่บซๆๅฅฝไธๅฅฝๆๆฏๆฒกๆณจๆ่ฟ๏ผๅๆญฃไธญๅฝๅฅณไบบๅฐฑ็ฎ่บซๆไธๅฅฝไนๆฏโไปๅฅณโใ๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
0,
0
] | 211 |
tieba
|
race
|
ไธ่ฝๅผๅธๆฏๅฏน็
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 7 |
tieba
|
race
|
้ๆดฒ้ปไบบๆบๅ70๏ผ่ขซๅญฆ่
ๅฝ็ฑปไธบๆบ้ๆฐดๅนณใ็พๅฝ้ปไบบๆทท่กๅฟๆบๅ85๏ผไธญ้ๆทท่กๅฟๆบๅๅบ่ฏฅๅพๅพๅจ90ๅทฆๅณ๏ผๅฆฅๅฆฅ็็ญ้ๅๆฐ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 56 |
zhihu
|
race
|
ๅๆฌข้ปไบบ่ฏทๅปไฝ ็ทไบบๅฝๅฎถ๏ผ่ตๅจไธญๅฝๅฐฑไธ่ฆๆชๅซไบบ้ชไบ๏ผๅจๆ้ฝๆฏๅบ่ฏฅ็
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
0
] | 32 |
tieba
|
gender
|
ไฝ ไธไผๆฏๆๅฐๆฅไฝ ๅฆปๅญๅไฝ ๅผบๅฅธ็ฝชๅง๏ผไฝ ๆพๅฟ่ฟ้กน็ฝชๅๅพ้พๅ่ฏ็๏ผๅฅณ็ไธๅๅฐฑไผๅไบฒ็ฆป่ขซไบบๅฒ็ฌ๏ผๅฅณ็่ฟๆไนๅจๅฎถ้ๅไธๅป๏ผ่ฟไธๅฆ็ดๆฅๅ็ฆปๅฉ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
0,
0
] | 64 |
tieba
|
race
|
่ฟ่ฏด่ฏดไนไธๅ๏ผ้ปๅนๅฅฝ็็
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 12 |
zhihu
|
region
|
่ตท็ ๅจๅฏไธฝ่ฟไปถไบๆ
ไธ๏ผๆฏ่ฟๅ ไธชๅไธปๅฐๅฏไธฝๅพฎๅไธ็่จๅ ่พฑ้ชๆฒณๅไบบ็๏ผๅฐๅค่นญ็ญๅบฆ๏ผๆ้ฝๆ็่ฟไบไบบๆฏไธๆฏๆ็
ๅ๏ผไฝ ้ชไปไปๅฐฑๆชๅฑ๏ผ่ฏดไฝ ็ฝๆดไป๏ผไฝ ไธ้ชไป้ฉฌไธๅฐฑ่ทๅฐ่ฏ้ขไธ็ปง็ปญๅฐๅ้ป๏ผๆๅป่ฟ่ฅฟๅฎ๏ผๆฏไธๅบง็พไธฝ็ๅๅธ๏ผๆๅๅพๅ้๏ผไฝๅๅคๆไธญๅ่ฏดๅ้่ฅฟ๏ผ้ปๅธๆ
้ๆฏ่ฅฟๅฎ็ญ็ญๅธธ่ฏๆง้่ฏฏ็่จ่ฎบ๏ผ่ฟไธ่ฎฉไบบ่ฏดๆด้ณๆฏๅไธๆๅค้ฝ๏ผไธๆฏๆด้ณๆฏๅค้ฝไผๅฝฑๅ่ฅฟๅฎไปไนๅ๏ผๆ ่ฏญ๐ฒ๐ฒ๐ฒ๐ฒ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 183 |
tieba
|
lgbt
|
ไธ่ดๅฎถๅบญ่ดฃไปป็ๆฒกๆๅๅพๅค๏ผๅ ไธบ่ฟ็งๅพๅฟซๅฐฑ็ฆปไบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 22 |
zhihu
|
region
|
ๆฑ่ฅฟไธบไปไนๆฏ็ฌฌไธๅทๅไบบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 11 |
tieba
|
gender
|
ๆฅผไธปๅ๏ผๆ่ฎฐๅพ่ฟๆฏๆไฝๆฎไฟกๅฅณๅ็ๅ
ณไบ็ทๆง็ๆกไปถๅง๏ผๆน็ๅฅฝ๏ผ่ฟๆ๏ผๆจ็ๅธๅญ้้ขๆๆก็ฎ๐ถ๏ผ่ตถ็ดง็ฝฎ้กถ็พ่พฑ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
0,
0
] | 49 |
tieba
|
race
|
ๅชๆ่ตๆฌๅฎถๆ่ฝๅ
ฅ็นๅคชๆๅฝ็นๅคชไบบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 15 |
zhihu
|
region
|
้จๅๅฐๅบ็ฉทๅง๏ผๆ่ฏด็ไธๅผๅ่ฟไธ็น
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
1,
0,
0,
0
] | 16 |
zhihu
|
region
|
๐ถๅ
ๅผ๏ผไปฅๅๆๅฐฑ่ทไฝ ๆททไบ๏ผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 18 |
zhihu
|
region
|
็ปๅฏนๆฏ 7ๅนดๅๆๅฐฑ้่ง่ฟๆๅฝๅค็ป็ปๅธฆ้ขๆไบไบบๅคงๅ้ปๅฎๅพฝ็ ็ป็ป็ๅคดๆฏไธชไธญๅฝ้็็พๅฝไบบ ๅฝๆถไปไฝๅจไธๆตท ๅฏนไธญๅฝๆๅไบๅฆๆๆ ไธญๆๅพๅฅฝ่ฟๆๅค่ฏไปไน็ ไปไปฌๅ่ฃ
ไธๆตทไบบ้ปๅฎๅพฝไบบ ๅธฆๅจ็็็ฝไธไธๆตทไบบ้ปๅฎๅพฝไบบ ๅๆฅ้ปๅฎๅฎๅพฝๅ้ๆฉ้ปๆฒณๅ ๅๅ ๆฏๅ ไธบไปไปฌ่ฎคไธบๆฒณๅๆฏๅๅคไธญๅฟ่ตทๆบ็ญ็ญ ๅ
ถๅฎๆ่ฟๆณ่ฏดๆดๅค ไฝๆฏๆไธ่ฝ ๆๅพๆ ๆๅช่ฝ่ฏด่ฟไนๅค
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 159 |
tieba
|
gender
|
็ฐๅฎไธญๅข๏ผ่ชๅคไปฅๆฅๅชไธช้ป็ฒพ็ตๅธฆๅคดๅฒๆ ผๆ ผๅทซ็๏ผๅฐฑ็ฎๆไนๆๅฐใ้ๅฐ็ๅญๅฑๆบไบๅ่ๆฏ้ป็ฒพ็ต็ปๅธธไพ้ไบๆ ผๆ ผๅทซ๏ผ้ ๅฐฑไบๅ้ข้ป็ฒพ็ตไธๅ็ไฝณ่ฏ๏ผ่่็ฒพ็ตๅจๅ็บฟ้ๅฝ็ฉถ็ซๆฏ่ฐๆกๅจๆ ผๆ ผๅทซๅ้ขๅๅฒๅทฒ็ปๅ่ฏๆไปฌ็ญๆกไบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 96 |
tieba
|
gender
|
ๅบ่ฏฅๅค็งๆฎ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 5 |
tieba
|
gender
|
ๆ185๏ผไฝ่ฟๅนๅๆฏ้ฒจbee
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
0,
0
] | 14 |
zhihu
|
race
|
ๅฅน่ชๅทฑไธไนๆฏไธไธชๅไผๅๅฎ ็ๅฐไธ๏ผๆฎไฟก็ทๆไปไนไธๅฅฝ๏ผ้พ้ๅคฉๅคฉ่ทไธชๅ
ซๅฉไธๆ ทๆจๅคฉๆจๅฐๆชๅผๆงๆๅฅฝ๏ผไธญๅฝไบบ่ฎฒ็ฉถๅคฉ่กๅฅๅๅญไปฅ่ชๅผบไธๆฏ๏ผๆฎ้ไบบไน่ฆไธๆญ่ชๅผบ๏ผ่ไธๆฏๅๆไบ็พคไฝไธๆ ทไธๅณๅดๆดๅชๅค๏ผ้ๅ็งๆไธปไน๏ผๆ่
ๆงๅซไธปไนใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
0
] | 102 |
tieba
|
race
|
ๆ่ฟๆบ็ญ้นๅ๏ผๆฏไธๆฏๆพๆๅ็ๅๅ ไฝฟๅพไธไบๅๆๆๆญง่ง็ๅคไบ่ตทๆฅ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 30 |
zhihu
|
region
|
่ฟๆฏไบๅฎๅง๏ผ่ฏๆฎๆๆ็๏ผๆๆจๅคฉ็ๅฐ็ๆฏๆฐๅพไธ่กๅง
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 27 |
zhihu
|
region
|
ๅ ไธบๆๅคช่ฎค็ไบ~~ๆๆฏ็็ๆๅคๅ
ฐ็ปใๅฃ็ปใไฝ็ป(ไฝ็ปไธๆฏๅ็้ฃ็ง็ไธๆ็)๏ผ่ฎค่ฎค็็็่ฏปไบไธ้จๅ๏ผๆฏๆฒกๆ่ฏปๅฎ็๏ผ็ถๅๆๅ็ฐๆๅฎๅจๆฏ่ฏปไธไธๅป๏ผไฝ็ป่ฟ่ฝ็็นไบบ็ๆๆไปไน็๏ผ่ๅไธค่
ๅฎๅจๆฏ๏ผๆไธๅฅฝ่ฏด่ดฌไฝๅฎไปฌ็่ฏ๏ผไฝๆฏ็็ๆฏ๏ผๅฎๅ
จๆฅๅไธ่ฝ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 115 |
tieba
|
lgbt
|
่ฝไธ่ฝๅๅคๅ๏ผ็ฌๆญปไบ๏ผๆฒก่ง่ฟ่ฟไนๅด็กฌๅฐ่็fw๏ผๆฏไธๆฏๅพ
ไผ่ฟ่ฆ่ชๅทฑ็ฒพ็ฅ่ๅฉไธๆ่ฏดๆไธๅฑไบๅไฝ ่ฏด่ฏๅ
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 49 |
zhihu
|
race
|
ๆ่ซ็ๆฏไปไน๐ค
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 7 |
zhihu
|
region
|
ๆฝฎๆฑ็ซ้
ๅคชๅ
ป็ไบๅง
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 9 |
tieba
|
gender
|
็ๆฐ้ป่ฐ่ฏดๅไธ็ๅทฅๅคงๅญฆ็ๅญฆ็ๆฒกๆๅบๅฃฐไบ๏ผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 20 |
tieba
|
gender
|
ๆฏ็ทๆๅฎไนๅฎ ๅฅณไบบ็็ทไบบไธบ็๏ผไปไนๅซๅๆฌขๅฝ็ใ
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 22 |
tieba
|
gender
|
ๆ่ฐโๅฅณ็ๆ็งๅผบ๏ผ็ท็็็งๅผบโ็ๅปๆฟๅฐ่ฑกๆฏๅๅบๆฅ็๏ผๆๅฐฑ็นๅซ็ๅ็็ง
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
0,
1,
0,
0
] | 34 |
zhihu
|
region
|
ไพ็ถๆๆญง่งใๆๆฏๆฒณๅ็๏ผ2019ๅนดๅปๅไบฌๅฝไฟๅฎๆฃๅญฆ่ดน๏ผไบบๅฎถ่ฏด๏ผไฝ ๆฏๆฒณๅไบบ๏ผ๏ผๆๅฎถๆฏๆฒณๅๅ้จ้ขๅฐ็๏ผๆไปฅ่ฏด่ฏๆฅ่ฟๆฒณๅๅฃ้ณ๏ผๆ่ฏดไธๆฏ๏ผไฝๆฏๆไปไนๅ
ณ็ณปๅขใๅ
ฌๅธไบบไบๅฏนๆ่ฏด๏ผๆฉไบๅนดๅช่ฆๆฏๆฒณๅ็๏ผ้ฝไธ่ฆใๆๅนด้พไนไธๅคง๏ผๆไผฐ่ฎกๅฐฑๆฏๆฉๆๅธฆๅคด้ปๆฒณๅ็๏ผ็ถๅๆ
ขๆ
ขๅฝขๆๅบๆ่ฎค็ฅไบ๏ผๅ
ถๅฎ้ฝๆฏ็ฉบ็ฉดๆฅ้ฃใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 3 |
[
0,
0,
1
] |
[
0,
1,
0,
0,
0
] | 138 |
tieba
|
lgbt
|
ๅง้่ฟๅ ไธชๅๅๆ นๆฌๆฒกไปไน่ฝๅ๏ผๅๅ่ฟๅพ้ ๅๆงๆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
1,
0,
0,
0,
0
] | 23 |
tieba
|
lgbt
|
็ปไบๅฏไปฅ่ฏด่ฏไบ๏ผ่ฟ็ญ็บง้ๅถ๏ผ่ฟไฝ ไปฌๅซ็โ็ช่
ฐโๆฏไธๆฏๅฐฑๆฏ้ช้ชๅงๅง่ฏด่ฆๅปไบบๅฎถๅญฆๆ กๅ ตไบบๅฎถ็้ฃไธช?
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 46 |
tieba
|
lgbt
|
็ช็ชๆบๅฏ็ฑ็
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 6 |
zhihu
|
region
|
ๆฒณๅๆฌฒๅญๆ ๆณช
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 6 |
tieba
|
race
|
ๅๆฃ่ฏไธธ๐
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 5 |
tieba
|
race
|
็ฌๆญปๆไบๆบๅๆฏ็กฌไผคๅ
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 10 |
tieba
|
gender
|
่ดดๅงๅๅง๏ผไธๅ็ๅงๆไธๅ็ๆฐๅดใ่ไธ่ดดๅงไธ่ฌไธ็ซ็ๅงไฝ ไนๅทไธๅฐใ่ดดๅงๅ
ถๅฎๆฏๆๅฎนๆๆฅๅข็๏ผไฝๆฏๆ่งๅๅ็ทๆงๅฟๅ่พๅผฑใ้คไบไธชๅซ็ทๆงๅงๅค๏ผๅพ้พๅจๅซ็ๆถๅ็ทๅฅณ้ฎ้ขไธ็ทๆง็ๅๆ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 83 |
zhihu
|
race
|
่บซ่พนไธๅ ๆพ่ฟๅคๅฝ็ไปไนๆๅๅพๆๆพไบ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
1,
0
] | 17 |
zhihu
|
race
|
ๅซๅฌไป็๏ผไปๅจๅฑ่จ่ธๅฌ๏ผไธบไบ็ฑๆ
๏ผๅป็พๅฅฝ็้ๆดฒๅคง่ๅๅง
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
1,
0
] | 27 |
zhihu
|
race
|
่ฏๅฎไธ่ฝๆฅๅ๏ผๆๆณ่ฟๆฏ็ทๆงๅฏน่ชๅทฑ็งๆ็ไฟๆคๆชๆฝๅง๏ผๅฆๆๆฅๅๅๅไบบ่ฐ่ฟๆ็ฑ็ๅฅณไบบ๏ผๅฐฑไธๅฎ็จๅบฆไธ็ญไบๆฅๅ้ป้ปๆทท่ก๏ผ่ฆไธไบๅ ๅๅนด็้ปๅญๅญๅฐฑๅพ็ญ็ปใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
0
] | 70 |
tieba
|
gender
|
ๆ่ฐข็ๅคชๆฉไบๅง๏ผๅคๅธๆ่็ฐ็ๆฌงๆๆญปไนๅ็ฅ้ไบบ้ดๆฏๆๆธฉๅบฆ็ใ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 29 |
zhihu
|
race
|
ไฝ ่ฟๅฟๅๆๅพๆไปฌไธๅคชๅฅฝๅๆฅๅ๐๐๐
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 26 |
tieba
|
gender
|
็ทไบบ็ๆๅฉๅพไธๅฐ็ปดๆค้่ง๏ผๅฅณไบบ่ขซๆฏๅ๏ผ้ฝๆฏๅ ไธบ่ฟไบไผชๅๅญไปฌไฝๅบๆฅ็
| 1 |
[
0,
1
] | 1 |
[
1,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 33 |
zhihu
|
race
|
+1ไฝๅฆๆๅงๅจ่ฟฝๆฑ็็ฑ่ท้ปไบบไธ่ตทๅ้ๆดฒ๏ผๆๆๅฟๅบ้็ฅ็ฆไปไปฌไฟฉ????็ๅจๅฝๅ
ไธ่ฎจ้ช่ฎ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 42 |
zhihu
|
race
|
ๆฏๆๆญฃไนๅฅๅ๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
0,
1
] | 10 |
tieba
|
lgbt
|
ๅคๅฐ่ฟๅพๆฏไฝ ไปฌtxlๅๅฎณ๏ผๆ็ฅไนไธไธๅคๅถๆฅ่ฟไธ็ฒ่ดดๅฐฑๆๆญฃๅธธไบบ็ๆบๅๅฆๅฎไบ๏ผๅฐฑ้ฃไธคไธช่ต็ๆ็ซ ่ฐไฟก่ฐๆๆบๅๆ้ฎ้ข
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
1,
0,
0,
0,
0
] | 54 |
zhihu
|
race
|
ๆบๆญฃๅธธ็๏ผไธๆฌกๆไธช้่ฎฟ๏ผไธไธช็ฝไบบๅฅณๅซไบไธญๅฝไบบ๏ผไนๆฏ่ขซๅฅน็ๅๅญ่ธขๆใๅฝไฝ ้ๆฉไบๅผ็ฑป๏ผๅฐฑ่ฆๆ่ขซๆๆฅ็่งๆใไธ่ฟ๏ผๅฅๆช็ๆฏ๏ผๅจถไบ้ปไบบ๏ผ็ฝไบบๆ่
่ถๅไบบ็็ทๆงๅๆฏๅพๅฐ่งไปไปฌ่ขซๆๆฅโฆโฆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
0
] | 86 |
tieba
|
gender
|
่ฟๆณข่ชๆ็ไบ๏ผไธบๅฅๆฒกๆ้ฃไธช่ฏ่ฎบๅบ็้ฃๅ ไธชๅฅณๆไปฌๅธฆ่ตฐใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
0,
0
] | 26 |
tieba
|
lgbt
|
่ฟๆ ท็ๅ่ฎพ๏ผ็ฐๅฎไธญๅนถไธๅญๅจๆๆ็ซฏ็ฝ่ง
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 18 |
tieba
|
lgbt
|
ๅงไธปๆฏ้ๅบ็ๅ๏ผไฝ ไปฌ้ฃๅฟไน็ฎๆฏ้็พๅบไบๅง
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
1,
0,
0,
0
] | 20 |
tieba
|
lgbt
|
็ๆฅๅๆงๆๅช็ฅ้ๆฑก่ไปไบบไบ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
1,
0,
0,
0,
0
] | 13 |
zhihu
|
race
|
ๅจๅฎถ้ช้ป้ฌผๅบ้จๆฆๅฟตๅผๆดไผๅพท๏ผ๐ค
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 18 |
zhihu
|
race
|
้ปไบไปฃ็ๆฏ้ป๏ผๅทๆธกๆฅไธญๅฝ๏ผ่ฟไธชๅ็ญ้ฝ่ฆๅญฆไฝ ็ข้ป็ๆฅๅฟๅไธๆขๆ้ขๅ็ญ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 33 |
tieba
|
race
|
ไธบไปไน่ฆ็ฎกๅ๏ผ่ฟๆฏไบบๅฎถ็งไบๅง๏ผๆฑๆไบๅๅ่ฏดไฝ ่ฟไธคๅผ ๅพ?้ฝ็ๅฐๅฅฝไน
็่ดดไบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 35 |
zhihu
|
lgbt
|
่ฏด็ๅพๅฏนใไฝๆฏๅๅฑ็ไนไธ่ฝ่ฆๅๅฐฟ็ๅผบ่ก่ฎคๅๅง๏ผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 23 |
tieba
|
lgbt
|
ไฝ ่ฟๆชๆ่พ่บซไบก๏ผไฝ ไธ่ฏๅคไน
ไบ๏ผ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
0,
1
] | 15 |
tieba
|
race
|
ไธๆตทๆฑๅฎถ่ง
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 5 |
tieba
|
gender
|
ๅฝๆถ้ฃไธชๆธ
ๅ่
ๅ้ข็็ๆงไนๅ่ฝฌไบ๏ผๆไปฅๅซๅปไฟกๅฐไฝๆ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 25 |
zhihu
|
race
|
็ปๅธธๅฌ็ท็ๅๅฎถ่ทชๆ่กฃๆฟ๏ผๅฐฑ่ฏดโๆญฃๅธธๅ๏ผ่ฟไธๆบๆญฃๅธธ็ๅ๏ผโ๏ผๆฒกๅฌ่ฏด่ฟๅฅณ็่ทช๏ผๅฆๆ่ทชๆ่กฃๆฟไบ๏ผๅฐฑโ่ฟๆฏๅจๅฎถๆดๅโ๏ผไปฅๅๅคไปฃไปปๆๆไปฃ้ฝๆฒกๆ่ฟๆ ท็ๅฆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
0,
0
] | 70 |
zhihu
|
region
|
ๅฏไปฅ่ฆๆฑๅญฆๆ กๅ่ฃ
็ตๆขฏ๏ผๅฏไปฅ่ฆๆฑๅญฆๆ กๅๅผ็ทๅฅณๅฎฟ่๏ผไธ่ฎฉไบบๅ็ตๆขฏๆฏไธชไปไน้ฌผโโ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 43 |
zhihu
|
region
|
ไนๅฏไปฅ่ฏด๏ผๅคงๅคๆฐไธญๅฝไบบ็ฅๅ
้ฝๆฏๅคๆฒณๅไบบใ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 20 |
zhihu
|
race
|
้็่ๅญๆฅไบ ๆๅฐฑๆฏ็งๆๅ
ไธชๆญง่งไบ๐ถๅธฝๅญๆ่ชๅทฑๅธฆๅฅฝ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
0,
1,
0
] | 30 |
zhihu
|
region
|
ๆฒณๅๆฐ็ๅๆไบบ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
1,
0,
0,
0
] | 7 |
zhihu
|
region
|
ๅๅๅๅๅๆๅทฒ็ปๅผๅง็ฌไบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 12 |
zhihu
|
race
|
ๅ ไธบ้ปไบบๅฅณๅญฉ่ท้ปไบบ็ทๅญฉ็ปๅฉ๏ผๅฅนไปฌไธ่ฆๅฝฉ็คผ๏ผ้ปไบบๅฅณๅญฉ่ทไธญๅฝ็ทๅญฉ็ปๅฉ๏ผๅฅนไปฌไนไธ่ฆๅฝฉ็คผ๏ผไธญๅฝๅฅณไบบ่ทไธญๅฝ็ทๅญฉ็ปๅฉ๏ผๅฅนไปฌ่ฆๅคง้ขๅฝฉ็คผ๏ผๅฉๅๅๆไธๆฒพ้ณๆฅๆฐด๏ผไธญๅฝๅฅณไบบๆพ้ปไบบ็ทไบบ๏ผๅฅนไปฌไธ่ฆไธๅๅฝฉ็คผ๏ผ่ฟๆฒก็ปๅฉไนๅฏไปฅ็ๅญฉๅญ๏ผๆ้ปไบบ็
ง้กพ็้ฃๅซไธไธช่ๆ๏ผๅคๅฝๅไบบ้ฝไบคๅฃ็งฐ่ต๐
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
1,
1,
0
] | 126 |
tieba
|
gender
|
ไบบ็ฑปไธญๆบๅๆ็ซฏ้ซ็้ๅธธๆฏ็บขไธธ่ง้่
๏ผไปไปฌๆทฑๅป่ฎค่ฏๅฐไบๆฏไบบๅธ่ก็ๆฌ่ฝๅ็ๅฝ็้ๆฌไฝๅบๅฑไปฃ็ ๏ผๆไปฅๆๆๆฏไบบๅฝๆ็นๆฎๅๆณๆฌฒ็ๅทฅๅ
ท๏ผๆ่
ๅนฒ่ๅฐฑๆฏ็ทๅใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
1,
0,
1,
0,
0
] | 71 |
tieba
|
race
|
ๅช่ฝๆชๅฅนๆฒกๆฅ้ปไบบๅงใ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 10 |
zhihu
|
race
|
ๆฏๅง๏ผไฝ ๅฎ่ทต่ฟ?่ฟๆ ทๆฅ่ฏดๆญชๆไปไผ ็ปๅฝๅฅณ๏ผๅฝๅฅณไผ ๆญๆ
ข?ไฝ ่ฐ็ ่ฟๅ?ๆพไบ1000ไธช็ท็ๅ1000ไธชๅฅณ็ไบ็ธไผ ๆญ?็ท็ๆพๅฅณไบบไธๅบ่ฆไนๅธ
๏ผ่ฆไนๅบ้ฑ๏ผ่ฆไนๅ
ถไปๆ๏ผๆๆๆฌ๏ผๅฅณ็ๆฒกๆไผ ๆญๆๆฌใไผ ๆญๅ็ๆฏไธๆ ท็ไฝๆถฒไบคๆข๏ผไฝ ๅชๆฅ็ๅฅณไผ ็ทไฝ๏ผ่ฟ่ฏดๆฃไธ่พๆป็
ๅๆญฃๅธธๅ่ฏๆดป็ๅพไน
ๅข๏ผไฝ ไนไฟก?ๅพๅคไธไบๅนดไนๅ
ๅฐฑๅพๆญป๏ผไปไนๆดป็ๅพ้ฟใ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 1 |
[
1,
0,
0
] |
[
0,
0,
1,
1,
1
] | 151 |
zhihu
|
race
|
ๅฅไนๅซ่ฏดไบๅคงๅฅ๏ผๅช่ฝๅๅไฝ ไธๅฅ:ๅฐๅฟๅคงๆฐๆฎๆ็!
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 24 |
zhihu
|
region
|
(ใ๏ฟฃโณ๏ฟฃ)ใ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 7 |
tieba
|
gender
|
ๆ้ณๅฏ่ฝๆฏ่ง้ขๆจ่็้ฎ้ข๏ผ็ๅฐ็ๅคงๅคๆฐ่ง้ข่ฆไนๆฏๅๅฅณๆงๆธ
้็๏ผ่ฆไนๆฏๅทๅฅนไปฌ็ใๆปไน็ทๆง่ตท็ 55ๅผ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 48 |
tieba
|
lgbt
|
่พๅ๏ผๆข
ไบ็ๅฆ๏ผ็ฃๆฒกไปไนๅคงไธไบ็๏ผไธญๅฅๅ ็ไธบๆท๏ผ็ฟไปไน่ฆๆ
ๅฟๅข๏ผๆไธช็ฑ่ๅทฒๅ๏ผไธๆฌกๅฐฑไธ่ฏๅฆ
| 1 |
[
0,
1
] | 2 |
[
0,
1
] | 2 |
[
0,
1,
0
] |
[
0,
0,
0,
0,
1
] | 45 |
tieba
|
gender
|
็ไธๆฅๅไธช้ดๅฎๅฐฑๅฅฝไบ๏ผไธๆไธไธ๏ผๅฐฑๆไธไธใๆ็ๅฐฑๆฏไน้พๅไบๅไบบ
| 0 |
[
1,
0
] | 0 |
[
0,
0
] | 0 |
[
0,
0,
0
] |
[
0,
0,
0,
0,
0
] | 31 |
End of preview. Expand
in Data Studio
Facilitating Fine-grained Detection of Chinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmark
๐2024.9 Our related study, titled "Towards Comprehensive Detection of Chinese Harmful Meme", has been accepted to NeurIPS 2024! In this paper, we present ToxiCN_MM, the first Chinese harmful meme dataset. Here is the link: https://github.com/DUT-lujunyu/ToxiCN_MM. Welcome to star or fork it!
๐2024.9 Our related study, titled "PclGPT: A Large Language Model for Patronizing and Condescending Language Detection", has been accepted to EMNLP 2024! In this paper, we focus on a specific type of implicit toxicity, patronizing, and condescending language. link paper
๐2024.5 Our proposed dataset, ToxiCN, has been adopted by the international evaluation CLEF 2024: Multilingual Text Detoxification as the sole Chinese data source. Report
The paper has been accepted in ACL 2023 (main conference, long paper). Paper
โ ๏ธ Warning: The samples presented by this paper may be considered offensive or vulgar.
โ๏ธ Ethics Statement
The opinions and findings contained in the samples of our presented dataset should not be interpreted as representing the views expressed or implied by the authors. We acknowledge the risk of malicious actors attempting to reverse-engineer comments. We sincerely hope that users will employ the dataset responsibly and appropriately, avoiding misuse or abuse. We believe the benefits of our proposed resources outweigh the associated risks. All resources are intended solely for scientific research and are prohibited from commercial use.
๐ Monitor Toxic Frame
we introduce a hierarchical taxonomy Monitor Toxic Frame. Based on the taxonomy, the posts are progressively divided into diverse granularities as follows: (I) Whether Toxic, (II) Toxic Type (general offensive language or hate speech), (III) Targeted Group, (IV) Expression Category (explicitness, implicitness, or reporting).
๐ ToxiCN
We conduct a fine-grained annotation of posts crawled from Zhihu and Tieba, including both direct and indirect toxic samples. And ToxiCN dataset is presented, which has 12k comments containing Sexism, Racism, Regional Bias, Anti-LGBTQ, and Others. The dataset is presented in ToxiCN_1.0.csv. Here we simply describe each fine-grain label.
| Label | Description |
|---|---|
| toxic | Identify if a comment is toxic (1) or non-toxic (0). |
| toxic_type | non-toxic: 0, general offensive language: 1, hate speech: 2 |
| expression | non-hate: 0, explicit hate speech: 1, implicit hate speech: 2, reporting: 3 |
| target (a list) | LGBTQ: Index 0, Region: Index 1, Sexism: Index 2, Racism: Index 3, others: Index 4, non-hate: Index 5 |
๐ Insult Lexicon
See https://github.com/DUT-lujunyu/ToxiCN/tree/main/ToxiCN_ex/ToxiCN/lexicon
๐ Benchmark
We present a migratable benchmark of Toxic Knowledge Enhancement (TKE), enriching the text representation. The code is shown in modeling_bert.py, which is based on transformers 3.1.0.
โ๏ธ Licenses
This work is licensed under a Creative Commons Attribution- NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
Poster
Cite
If you want to use the resources, please cite the following paper:
@inproceedings{lu-etal-2023-facilitating,
title = "Facilitating Fine-grained Detection of {C}hinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmarks",
author = "Lu, Junyu and
Xu, Bo and
Zhang, Xiaokun and
Min, Changrong and
Yang, Liang and
Lin, Hongfei",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.898",
doi = "10.18653/v1/2023.acl-long.898",
pages = "16235--16250",
}
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