Predicting the Popularity of Trending Articles in the Arabic Wikipedia Using Data Mining Techniques

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Predicting the Popularity of Trending Articles in the Arabic Wikipedia Using Data Mining Techniques - scientific work related to Wikipedia quality published in 2014, written by Hanadi Muqbil Al-Mutairi and Muhammad Badruddin Khan.

Overview

Wikipedia, the open domain encyclopaedia, is considered to be one of the most prominent and most famous online encyclopaedias. There are approximately 270,000 Arabic articles, making it the focus of research and study of many researchers and of those interested in the Arabic language field. In this poster paper, authors 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 articles in terms of the number of visitors, which authors named the popularity level. By using a data- and text- mining techniques, and the software platform Rapidminer, authors developed four models that enabled us to predict the popularity level of Arabic articles on Wikipedia, depending on the features of their stimulants.

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