Predicting the Popularity of Trending Arabic Wikipedia Articles Based on External Stimulants Using Data/Text Mining Techniques

被引：0

作者：

AL-Mutairi, Hanadi Muqbil ^{[1
]}

Khan, Mohammad Badruddin ^{[1
]}

机构：

[1] Al Imam Univ, Coll Comp & Informat Sci, Riyadh, Saudi Arabia

来源：

2015 INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (ICCC) | 2015年

关键词：

Arabic Wikipedia articles; Behavior analysis; Classification; Data mining; Wikipedia mining; Prediction; Popularity level; Trending topics; Twitter;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Wikipedia is considered to be one of the most famous online encyclopedias. We study the issues related to trending articles on Arabic Wikipedia and how it is influenced by certain external stimulants: for example, breaking news, celebrities' tweets, special events from the past, instant messages on any social media application or any other reasons that could affect the Arabic Wikipedia articles in terms of the number of visitors, which we named the popularity level. By using a data- and text- mining techniques, and the software platform Rapidminer, we developed two models that enabled us to predict the popularity level of Arabic articles on Wikipedia, depending on the features of their stimulants.

引用

页码：295 / 300

页数：6

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