@inproceedings{mohanty-etal-2020-annotated,
title = "Annotated Corpus for Sentiment Analysis in {O}dia Language",
author = "Mohanty, Gaurav and
Mishra, Pruthwik and
Mamidi, Radhika",
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.339",
pages = "2788--2795",
abstract = "Given the lack of an annotated corpus of non-traditional Odia literature which serves as the standard when it comes sentiment analysis, we have created an annotated corpus of Odia sentences and made it publicly available to promote research in the field. Secondly, in order to test the usability of currently available Odia sentiment lexicon, we experimented with various classifiers by training and testing on the sentiment annotated corpus while using identified affective words from the same as features. Annotation and classification are done at sentence level as the usage of sentiment lexicon is best suited to sentiment analysis at this level. The created corpus contains 2045 Odia sentences from news domain annotated with sentiment labels using a well-defined annotation scheme. An inter-annotator agreement score of 0.79 is reported for the corpus.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>Given the lack of an annotated corpus of non-traditional Odia literature which serves as the standard when it comes sentiment analysis, we have created an annotated corpus of Odia sentences and made it publicly available to promote research in the field. Secondly, in order to test the usability of currently available Odia sentiment lexicon, we experimented with various classifiers by training and testing on the sentiment annotated corpus while using identified affective words from the same as features. Annotation and classification are done at sentence level as the usage of sentiment lexicon is best suited to sentiment analysis at this level. The created corpus contains 2045 Odia sentences from news domain annotated with sentiment labels using a well-defined annotation scheme. An inter-annotator agreement score of 0.79 is reported for the corpus.</abstract>
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%0 Conference Proceedings
%T Annotated Corpus for Sentiment Analysis in Odia Language
%A Mohanty, Gaurav
%A Mishra, Pruthwik
%A Mamidi, Radhika
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth Language Resources and Evaluation Conference
%D 2020
%8 May
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F mohanty-etal-2020-annotated
%X Given the lack of an annotated corpus of non-traditional Odia literature which serves as the standard when it comes sentiment analysis, we have created an annotated corpus of Odia sentences and made it publicly available to promote research in the field. Secondly, in order to test the usability of currently available Odia sentiment lexicon, we experimented with various classifiers by training and testing on the sentiment annotated corpus while using identified affective words from the same as features. Annotation and classification are done at sentence level as the usage of sentiment lexicon is best suited to sentiment analysis at this level. The created corpus contains 2045 Odia sentences from news domain annotated with sentiment labels using a well-defined annotation scheme. An inter-annotator agreement score of 0.79 is reported for the corpus.
%U https://aclanthology.org/2020.lrec-1.339
%P 2788-2795
Markdown (Informal)
[Annotated Corpus for Sentiment Analysis in Odia Language](https://aclanthology.org/2020.lrec-1.339) (Mohanty et al., LREC 2020)
ACL