Popularity Prediction of Online News Item Based on Social Media Response

Arafat, Hossain Md.; Sagar, Didar Hossain; Ahmed, Kawsar; Paul, Bikash Kumar; Rahman, Md. Zamilur; Habib, Md. Ahsan

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dc.contributor.author	Arafat, Hossain Md.
dc.contributor.author	Sagar, Didar Hossain
dc.contributor.author	Ahmed, Kawsar
dc.contributor.author	Paul, Bikash Kumar
dc.contributor.author	Rahman, Md. Zamilur
dc.contributor.author	Habib, Md. Ahsan
dc.date.accessioned	2021-09-28T09:08:20Z
dc.date.available	2021-09-28T09:08:20Z
dc.date.issued	2019-10-07
dc.identifier.uri	http://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/6210
dc.description.abstract	The objective of the research study is to predict the popularity of printed as well as online news articles that are publicized on the online social network. Keywords are extracted from the collected data sets and compared with trained data sets. The popularity of any news contents are calculated through the proposed prediction model according to training data sets and lifetime of that news. 100 newly published news items have collected and analyzed them. We have found an accuracy of 70% which is more than prior studies. Our proposed system will make a significant way for the user to explore the news articles.	en_US
dc.language.iso	en_US	en_US
dc.publisher	2020 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019 and 3rd International Conference on Imaging, Vision and Pattern Recognition, icIVPR 2019 with International Conference on Activity and Behavior Computing, ABC 2019, IEEE	en_US
dc.subject	Data mining	en_US
dc.subject	Analytical models	en_US
dc.subject	Sociology	en_US
dc.subject	Social networking	en_US
dc.subject	Information resources	en_US
dc.title	Popularity Prediction of Online News Item Based on Social Media Response	en_US
dc.type	Article	en_US