DataSet for Arabic Classification

The dataset is a collection of Arabic texts, which covers modern Arabic language used in newspapers articles. The text contains alphabetic, numeric and symbolic words. The existence of numeric and symbolic words in this dataset could tell the efficiency and robustness of many Arabic text classification and indexing documents. The dataset consists of 111,728 documents (cf. Table 1) and 319,254,124 words (cf. Table 2) structured in text files, and collected from 3 Arabic online newspapers: Assabah [9], Hespress [10] and Akhbarona [11] using semi-automatic web crawling process. The documents in the dataset are categorized into 5 classes: sport, politic, culture, economy and diverse. The number of documents and words for each class varies from one class to another (cf. Tables 1-2).