Datasets:
metadata
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- af
- an
- ar
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- eo
- es
- et
- eu
- fa
- fi
- fo
- fr
- fy
- ga
- gd
- gl
- gu
- he
- hi
- hr
- ht
- hu
- hy
- ia
- id
- io
- is
- it
- ja
- ka
- km
- kn
- ko
- ku
- ky
- la
- lb
- lt
- lv
- mk
- mr
- ms
- mt
- nl
- nn
- 'no'
- pl
- pt
- rm
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- sw
- ta
- te
- th
- tk
- tl
- tr
- uk
- ur
- uz
- vi
- vo
- wa
- yi
- zh
- zhw
license:
- gpl-3.0
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: SentiWS
configs:
- 'no'
- af
- an
- ar
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- eo
- es
- et
- eu
- fa
- fi
- fo
- fr
- fy
- ga
- gd
- gl
- gu
- he
- hi
- hr
- ht
- hu
- hy
- ia
- id
- io
- is
- it
- ja
- ka
- km
- kn
- ko
- ku
- ky
- la
- lb
- lt
- lv
- mk
- mr
- ms
- mt
- nl
- nn
- pl
- pt
- rm
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- sw
- ta
- te
- th
- tk
- tl
- tr
- uk
- ur
- uz
- vi
- vo
- wa
- yi
- zh
- zhw
dataset_info:
- config_name: af
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 2299
download_size: 0
dataset_size: 45954
- config_name: an
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 97
download_size: 0
dataset_size: 1832
- config_name: ar
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 2794
download_size: 0
dataset_size: 58707
- config_name: az
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 1979
download_size: 0
dataset_size: 40044
- config_name: be
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 1526
download_size: 0
dataset_size: 41915
- config_name: bg
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 2847
download_size: 0
dataset_size: 78779
- config_name: bn
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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download_size: 0
dataset_size: 70928
- config_name: br
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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num_examples: 184
download_size: 0
dataset_size: 3234
- config_name: bs
features:
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dtype: string
- name: sentiment
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class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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download_size: 0
dataset_size: 39890
- config_name: ca
features:
- name: word
dtype: string
- name: sentiment
dtype:
class_label:
names:
'0': negative
'1': positive
splits:
- name: train
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download_size: 0
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- config_name: cs
features:
- name: word
dtype: string
- name: sentiment
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'1': positive
splits:
- name: train
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- config_name: cy
features:
- name: word
dtype: string
- name: sentiment
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'1': positive
splits:
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- config_name: da
features:
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dtype: string
- name: sentiment
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'1': positive
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- config_name: de
features:
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dtype: string
- name: sentiment
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'1': positive
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- config_name: el
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- name: sentiment
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'1': positive
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- config_name: eo
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- config_name: es
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dtype: string
- name: sentiment
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'1': positive
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- config_name: et
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- config_name: eu
features:
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'1': positive
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- config_name: fa
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- config_name: fi
features:
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dtype: string
- name: sentiment
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'1': positive
splits:
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- config_name: fo
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'1': positive
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- config_name: fr
features:
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dtype: string
- name: sentiment
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- config_name: fy
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- config_name: ga
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- name: sentiment
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- config_name: gd
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- config_name: gl
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- config_name: gu
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- config_name: he
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- config_name: hi
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- config_name: hr
features:
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- config_name: ht
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- config_name: ia
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- config_name: id
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- config_name: ka
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- config_name: kn
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- config_name: ko
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- config_name: ku
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- config_name: ky
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- config_name: la
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- config_name: lb
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- config_name: nn
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- config_name: pl
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- config_name: rm
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Dataset Card for SentiWS
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://sites.google.com/site/datascienceslab/projects/multilingualsentiment
- Repository: https://www.kaggle.com/rtatman/sentiment-lexicons-for-81-languages
- Paper: [Needs More Information]
- Leaderboard: [Needs More Information]
- Point of Contact: [Needs More Information]
Dataset Summary
This dataset add sentiment lexicons for 81 languages generated via graph propagation based on a knowledge graph--a graphical representation of real-world entities and the links between them
Supported Tasks and Leaderboards
Sentiment-Classification
Languages
Afrikaans Aragonese Arabic Azerbaijani Belarusian Bulgarian Bengali Breton Bosnian Catalan; Valencian Czech Welsh Danish German Greek, Modern Esperanto Spanish; Castilian Estonian Basque Persian Finnish Faroese French Western Frisian Irish Scottish Gaelic; Gaelic Galician Gujarati Hebrew (modern) Hindi Croatian Haitian; Haitian Creole Hungarian Armenian Interlingua Indonesian Ido Icelandic Italian Japanese Georgian Khmer Kannada Korean Kurdish Kirghiz, Kyrgyz Latin Luxembourgish, Letzeburgesch Lithuanian Latvian Macedonian Marathi (Marāṭhī) Malay Maltese Dutch Norwegian Nynorsk Norwegian Polish Portuguese Romansh Romanian, Moldavian, Moldovan Russian Slovak Slovene Albanian Serbian Swedish Swahili Tamil Telugu Thai Turkmen Tagalog Turkish Ukrainian Urdu Uzbek Vietnamese Volapük Walloon Yiddish Chinese Zhoa
Dataset Structure
Data Instances
{
"word":"die",
"sentiment": 0, #"negative"
}
Data Fields
- word: one word as a string,
- sentiment-score: the sentiment classification of the word as a string either negative (0) or positive (1)
Data Splits
[Needs More Information]
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
[Needs More Information]
Considerations for Using the Data
Social Impact of Dataset
[Needs More Information]
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
[Needs More Information]
Licensing Information
GNU General Public License v3
Citation Information
@inproceedings{inproceedings, author = {Chen, Yanqing and Skiena, Steven}, year = {2014}, month = {06}, pages = {383-389}, title = {Building Sentiment Lexicons for All Major Languages}, volume = {2}, journal = {52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference}, doi = {10.3115/v1/P14-2063} }
Contributions
Thanks to @KMFODA for adding this dataset.