期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2020
卷号：11
期号：12
页码：809-814
DOI：10.14569/IJACSA.2020.0111293
出版社：Science and Information Society (SAI)
摘要：Wrongdoing is increasing through social media. Detecting them requires highlighting the most interesting topics in the posts. This essential part in the characterization of social network users could be done by a classification of posts. For this, we use a tuple of keywords and the Map-reduce algorithm for data collection and extraction. The main purpose is to achieve success on software realization which will establish a network between social networks to extract data and to speed up the classification of posts. The proposed method consists of verifying a sequence of keywords in the posts, following a grammar in order to determine classes. It allows the categorization of posts and monitoring of social networks. The categorization facilitates research of a particular post containing specific words. Thus, we contribute to increase capacity for wrongdoing prevention and strengthening cyber-security.
关键词：Big Data; map-reduce; social network; cyber-security; classification
