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

Author

Al-Mutairi, Hanadi Muqbil ; Khan, Mohammad Badruddin

Author_Institution

Coll. of Comput. & Inf. Sci., Al-Imam Univ., Saudi Arabia

fYear

2015

fDate

26-29 April 2015

Firstpage

1

Lastpage

6

Abstract

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.

Keywords

Web sites; data mining; encyclopaedias; natural language processing; text analysis; Arabic Wikipedia article; Rapidminer; data mining technique; external stimulant; online encyclopedia; popularity level; software platform; text mining technique; Classification algorithms; Electronic publishing; Encyclopedias; Internet; Text categorization;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing (ICCC), 2015 International Conference on

Conference_Location

Riyadh

Print_ISBN

978-1-4673-6617-5

Type

conf

DOI

10.1109/CLOUDCOMP.2015.7149651

Filename

7149651