Scopus Indexed Paper

Paper Details


Title
Popularity prediction of online news item based on social media response
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.
Keywords
Predictive models, Publishing, Facebook, Data mining, Analytical models, Sociology
Authors
Hossain Md. Arafat, Didar Hossain Sagar, Kawsar Ahmed, Bikash Kumar Paul, Md. Zamilur Rahman, Md. Ahsan Habib
Phone
Journal or Conference Name
2019 Joint 8th International Conference on Informatics, Electronics and Vision, ICIEV 2019
Publish Year
2019
Indexing
Scopus