Popularity Prediction of Online News Item Based on Social Media Response

被引：1
|
作者：
Arafat, Hossain Md [1 ]
Sagar, Didar Hossain [1 ]
Ahmed, Kawsar [1 ,2 ]
Paul, Bikash Kumar [1 ,2 ,3 ]
Rahman, Md Zamilur [1 ]
Habib, Md Ahsan [1 ]
机构：
[1] Mawlana Bhashani Sci & Technol Univ, Dept ICT, Tangail 1902, Bangladesh
[2] Daffodil Int Univ, Dept Software Engn SWE, Dhaka, Bangladesh
[3] Mawlana Bhashani Sci & Technol Univ, Grp Biophotomatix, Tangail 1902, Bangladesh
来源：
2019 JOINT 8TH INTERNATIONAL CONFERENCE ON INFORMATICS, ELECTRONICS & VISION (ICIEV) AND 2019 3RD INTERNATIONAL CONFERENCE ON IMAGING, VISION & PATTERN RECOGNITION (ICIVPR) WITH INTERNATIONAL CONFERENCE ON ACTIVITY AND BEHAVIOR COMPUTING (ABC) | 2019年
关键词：
Popularity prediction; News item; News sharing; Intelligent Systems; Social Media Response;
D O I：
10.1109/iciev.2019.8858525
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：173 / 177
页数：5
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