Journalist system using Tweeter news media traffic

Abstract

Journalists have some responsibility as their duty. Besides delivering the right news to public, they also have to deliver fast. Therefore getting the potential news fast is one important key for journalist.. This study tries to use the information public from social media tweeter. Social media is considered as public information which every people can be involved. This system, starts collecting tweets which mention formal tweeter media. The application will group each tweets into various themes based on the cosine similarity. If cosine similarity is big, it can be indicated as one group news.. The tweets which are more than the certain threshold, it can be indicated as the candidate news. This candidate news is then classified into one of ten categories using support vector machine (SVM). This classification has 85% accuracy. The category classified is used for assigning the specific journalist to cover this candidate news. This system has two important modules. One in center server which is responsible for collecting and processing data, the other one application mobile which is installed in journalist is called Journes. The results show the Journes give notification to journalist for getting some candidate news.