Cricket Comment Sentiment Analysis on Bangla Texts From Social Media Using Supervised Machine Learning

dc.contributor.authorTutul, Hasibul Hasan
dc.contributor.authorSaha, Mithun
dc.contributor.authorShovon, Md. Shaikh Ahemed
dc.date.accessioned2022-11-10T03:57:25Z
dc.date.available2022-11-10T03:57:25Z
dc.date.issued2022-01-02
dc.description.abstractPeople nowadays use various social platforms and video-sharing mediums to communicate their emotions, ideas, Viewpoints, and Proposals. On Twitter, Facebook, and other social media platforms, there are numerous discussions about sports, particularly cricket as well as football. The viewpoint may communicate detraction in various ways, using notation that may include numerous polarities such as positive, negative, or neutral, and understanding the sentiment of each opinion is a difficult and time-consuming effort even for humans. This challenge can be solved by using natural language processing to analyze sentiment in relevant comments (NLP).[8] In NLP tasks such as sentiment analysis, supervised machine learning classifiers are commonly utilized. We created a dataset of real people's attitudes about cricket in Bangla text in three divisions: positive, neutral, and negative. then processed by removing superfluous terms from the dataset.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8879
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/8879
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectSocial media and society
dc.subjectCommunity media
dc.titleCricket Comment Sentiment Analysis on Bangla Texts From Social Media Using Supervised Machine Learning
dc.typeOther

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