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Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models

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Published in:Радіоелектронні і комп'ютерні системи
Format: Online Article RSS Article
Published: 2026
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FRELIP Feed Integration
container_title Радіоелектронні і комп'ютерні системи
description
discipline_display Computer Engiineering
discipline_facet Computer Engiineering
format Online Article
RSS Article
genre Journal Article
id rss_article:78972
institution FRELIP
journal_source_facet Радіоелектронні і комп'ютерні системи
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
Computer Engiineering
General
Computer Engiineering
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Engiineering
General
Computer Engiineering
Computer Engiineering
General
Computer Engiineering
subject_facet Computer Engiineering
General
Computer Engiineering
title Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_auth Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_full Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_fullStr Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_full_unstemmed Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_short Sentiment analysis of trending tweets using Spark NLP and deep learning: a benchmark study of CNN vs transformer models
title_sort sentiment analysis of trending tweets using spark nlp and deep learning: a benchmark study of cnn vs transformer models
topic Computer Engiineering
General
Computer Engiineering
url https://nti.khai.edu/ojs/index.php/reks/article/view/reks.2026.1.10