AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus
AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus
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Publisher
Basel: MDPI AG
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Language
English
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Publisher
Basel: MDPI AG
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Scope and Contents
Contents
At a time when research in the field of sentiment analysis tends to study advanced topics in languages, such as English, other languages such as Arabic still suffer from basic problems and challenges, most notably the availability of large corpora. Furthermore, manual annotation is time-consuming and difficult when the corpus is too large. This pap...
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Full title
AraSenCorpus: A Semi-Supervised Approach for Sentiment Annotation of a Large Arabic Text Corpus
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TN_cdi_doaj_primary_oai_doaj_org_article_ad63516d69714c9fb42794d66de040ab
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_ad63516d69714c9fb42794d66de040ab
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ISSN
2076-3417
E-ISSN
2076-3417
DOI
10.3390/app11052434
