README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
languages:
  - 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
licenses:
  - gpl-3-0
multilinguality:
  - multilingual
size_categories:
  - n<1K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - sentiment-classification

Dataset Card for SentiWS

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation 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} }