数据集:
senti_lex
任务:
文本分类计算机处理:
multilingual语言创建人:
expert-generated批注创建人:
expert-generated源数据集:
original许可:
gpl-3.0This 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
Sentiment-Classification
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
{ "word":"die", "sentiment": 0, #"negative" }
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Who are the source language producers?[Needs More Information]
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Who are the annotators?[Needs More Information]
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GNU General Public License v3.
It is distributed here under the GNU General Public License . Note that this is the full GPL, which allows many free uses, but does not allow its incorporation into any type of distributed proprietary software, even in part or in translation. For commercial applications please contact the dataset creators (see "Citation Information").
This dataset was collected by Yanqing Chen and Steven Skiena. If you use it in your work, please cite the following paper:
@inproceedings{chen-skiena-2014-building, title = "Building Sentiment Lexicons for All Major Languages", author = "Chen, Yanqing and Skiena, Steven", booktitle = "Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)", month = jun, year = "2014", address = "Baltimore, Maryland", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/P14-2063", doi = "10.3115/v1/P14-2063", pages = "383--389", }
Thanks to @KMFODA for adding this dataset.