Classification of microblogging users

Abstract

Recent advancements in Web 2.0, people can't be regarded as simple content reader, they can also contribute content as writers. This work consists of microblogging and text categorization. Text categorization steps were used in microblogs to find out users whose contributions are more valuable for its related category. 2015 RSS news feeds were taken for training and users' tweets were used as test data. This study also differs from other related projects in selection of features. Selected test feature must be also in training data. If it doesn't, test feature can't be taken as feature in test data. In conclusion, contents of news bots in Twitter have more categorical content than ordinary microbloggers.