@inproceedings{gokani-mamidi-2023-gsac,
title = "{GSAC}: A {G}ujarati Sentiment Analysis Corpus from {T}witter",
author = "Gokani, Monil and
Mamidi, Radhika",
editor = "Barnes, Jeremy and
De Clercq, Orph{\'e}e and
Klinger, Roman",
booktitle = "Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, {\&} Social Media Analysis",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.wassa-1.12",
doi = "10.18653/v1/2023.wassa-1.12",
pages = "129--137",
abstract = "Sentiment Analysis is an important task for analysing online content across languages for tasks such as content moderation and opinion mining. Though a significant amount of resources are available for Sentiment Analysis in several Indian languages, there do not exist any large-scale, open-access corpora for Gujarati. Our paper presents and describes the Gujarati Sentiment Analysis Corpus (GSAC), which has been sourced from Twitter and manually annotated by native speakers of the language. We describe in detail our collection and annotation processes and conduct extensive experiments on our corpus to provide reliable baselines for future work using our dataset.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="gokani-mamidi-2023-gsac">
<titleInfo>
<title>GSAC: A Gujarati Sentiment Analysis Corpus from Twitter</title>
</titleInfo>
<name type="personal">
<namePart type="given">Monil</namePart>
<namePart type="family">Gokani</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Radhika</namePart>
<namePart type="family">Mamidi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis</title>
</titleInfo>
<name type="personal">
<namePart type="given">Jeremy</namePart>
<namePart type="family">Barnes</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Orphée</namePart>
<namePart type="family">De Clercq</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Roman</namePart>
<namePart type="family">Klinger</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Toronto, Canada</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Sentiment Analysis is an important task for analysing online content across languages for tasks such as content moderation and opinion mining. Though a significant amount of resources are available for Sentiment Analysis in several Indian languages, there do not exist any large-scale, open-access corpora for Gujarati. Our paper presents and describes the Gujarati Sentiment Analysis Corpus (GSAC), which has been sourced from Twitter and manually annotated by native speakers of the language. We describe in detail our collection and annotation processes and conduct extensive experiments on our corpus to provide reliable baselines for future work using our dataset.</abstract>
<identifier type="citekey">gokani-mamidi-2023-gsac</identifier>
<identifier type="doi">10.18653/v1/2023.wassa-1.12</identifier>
<location>
<url>https://aclanthology.org/2023.wassa-1.12</url>
</location>
<part>
<date>2023-07</date>
<extent unit="page">
<start>129</start>
<end>137</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T GSAC: A Gujarati Sentiment Analysis Corpus from Twitter
%A Gokani, Monil
%A Mamidi, Radhika
%Y Barnes, Jeremy
%Y De Clercq, Orphée
%Y Klinger, Roman
%S Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F gokani-mamidi-2023-gsac
%X Sentiment Analysis is an important task for analysing online content across languages for tasks such as content moderation and opinion mining. Though a significant amount of resources are available for Sentiment Analysis in several Indian languages, there do not exist any large-scale, open-access corpora for Gujarati. Our paper presents and describes the Gujarati Sentiment Analysis Corpus (GSAC), which has been sourced from Twitter and manually annotated by native speakers of the language. We describe in detail our collection and annotation processes and conduct extensive experiments on our corpus to provide reliable baselines for future work using our dataset.
%R 10.18653/v1/2023.wassa-1.12
%U https://aclanthology.org/2023.wassa-1.12
%U https://doi.org/10.18653/v1/2023.wassa-1.12
%P 129-137
Markdown (Informal)
[GSAC: A Gujarati Sentiment Analysis Corpus from Twitter](https://aclanthology.org/2023.wassa-1.12) (Gokani & Mamidi, WASSA 2023)
ACL
- Monil Gokani and Radhika Mamidi. 2023. GSAC: A Gujarati Sentiment Analysis Corpus from Twitter. In Proceedings of the 13th Workshop on Computational Approaches to Subjectivity, Sentiment, & Social Media Analysis, pages 129–137, Toronto, Canada. Association for Computational Linguistics.