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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2020
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2020
License: CC BY
Data sources: ZENODO
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Tunizi: Tunisian Arabizi Sentiment Analysis Dataset

Authors: Chayma Fourati;

Tunizi: Tunisian Arabizi Sentiment Analysis Dataset

Abstract

Tunizi is the first 100% Tunisian Arabizi sentiment analysis dataset. Tunisian Arabizi is the representation of the tunisian dialect written in Latin characters and numbers rather than Arabic letters.We gathered comments from social media platforms that express sentiment about popular topics. For this purpose, we extracted 100k comments using public streaming APIs. Tunizi was preprocessed by removing links, emoji symbols, and punctuations. The collected comments were manually annotated using an overall polarity: positive (1), negative (-1) and neutral (0) class. We divided the dataset into separate training, validation and test sets, with a ratio of 7:1:2 with a balanced split where the number of comments from positive class and negative class are almost the same.

This dataset contains comments written in Tunisian Arabizi which represents the Tunisian dialect written in Latin letters and numbers.

Keywords

Tunisian Arabizi, Dialect

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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