@inproceedings{ciobotaru-dinu-2021-red,
title = "{RED}: A Novel Dataset for {R}omanian Emotion Detection from Tweets",
author = "Ciobotaru, Alexandra and
Dinu, Liviu P.",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)",
month = sep,
year = "2021",
address = "Held Online",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/2021.ranlp-1.34/",
pages = "291--300",
abstract = "In Romanian language there are some resources for automatic text comprehension, but for Emotion Detection, not lexicon-based, there are none. To cover this gap, we extracted data from Twitter and created the first dataset containing tweets annotated with five types of emotions: joy, fear, sadness, anger and neutral, with the intent of being used for opinion mining and analysis tasks. In this article we present some features of our novel dataset, and create a benchmark to achieve the first supervised machine learning model for automatic Emotion Detection in Romanian short texts. We investigate the performance of four classical machine learning models: Multinomial Naive Bayes, Logistic Regression, Support Vector Classification and Linear Support Vector Classification. We also investigate more modern approaches like fastText, which makes use of subword information. Lastly, we fine-tune the Romanian BERT for text classification and our experiments show that the BERT-based model has the best performance for the task of Emotion Detection from Romanian tweets. Keywords: Emotion Detection, Twitter, Romanian, Supervised Machine Learning"
}
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<abstract>In Romanian language there are some resources for automatic text comprehension, but for Emotion Detection, not lexicon-based, there are none. To cover this gap, we extracted data from Twitter and created the first dataset containing tweets annotated with five types of emotions: joy, fear, sadness, anger and neutral, with the intent of being used for opinion mining and analysis tasks. In this article we present some features of our novel dataset, and create a benchmark to achieve the first supervised machine learning model for automatic Emotion Detection in Romanian short texts. We investigate the performance of four classical machine learning models: Multinomial Naive Bayes, Logistic Regression, Support Vector Classification and Linear Support Vector Classification. We also investigate more modern approaches like fastText, which makes use of subword information. Lastly, we fine-tune the Romanian BERT for text classification and our experiments show that the BERT-based model has the best performance for the task of Emotion Detection from Romanian tweets. Keywords: Emotion Detection, Twitter, Romanian, Supervised Machine Learning</abstract>
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<url>https://aclanthology.org/2021.ranlp-1.34/</url>
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%0 Conference Proceedings
%T RED: A Novel Dataset for Romanian Emotion Detection from Tweets
%A Ciobotaru, Alexandra
%A Dinu, Liviu P.
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
%D 2021
%8 September
%I INCOMA Ltd.
%C Held Online
%F ciobotaru-dinu-2021-red
%X In Romanian language there are some resources for automatic text comprehension, but for Emotion Detection, not lexicon-based, there are none. To cover this gap, we extracted data from Twitter and created the first dataset containing tweets annotated with five types of emotions: joy, fear, sadness, anger and neutral, with the intent of being used for opinion mining and analysis tasks. In this article we present some features of our novel dataset, and create a benchmark to achieve the first supervised machine learning model for automatic Emotion Detection in Romanian short texts. We investigate the performance of four classical machine learning models: Multinomial Naive Bayes, Logistic Regression, Support Vector Classification and Linear Support Vector Classification. We also investigate more modern approaches like fastText, which makes use of subword information. Lastly, we fine-tune the Romanian BERT for text classification and our experiments show that the BERT-based model has the best performance for the task of Emotion Detection from Romanian tweets. Keywords: Emotion Detection, Twitter, Romanian, Supervised Machine Learning
%U https://aclanthology.org/2021.ranlp-1.34/
%P 291-300
Markdown (Informal)
[RED: A Novel Dataset for Romanian Emotion Detection from Tweets](https://aclanthology.org/2021.ranlp-1.34/) (Ciobotaru & Dinu, RANLP 2021)
ACL