Trending Topic Extraction from Twitter for an Arabic Speaking User

摘要

Social media has become the first source of information for many people. The amount of information posted on social media daily has become very vast that it became difficult to track. One of the most popular social media applications is Twitter. Users follow lots of news accounts, public figures, and their friends so they can be updated by the latest events around them. Since the dialect language and the style of writing differ from a region to another, our objective in this research is to extract trending topics for an Arabic speaking twitter user. In this way. the user can easily get at a glimpse of the trending topics discussed by the people he follows. By applying the document pivot approach using a development data set we could achieve a recall value of 100% and Fl measure of 0.8. To validate our results, we collected 12 different data sets of different sizes and from three different domains (sports, entertainment, and news) then applied the approach to them. The results showed that the document pivot approach could extract the trending topics for an Arabic speaking twitter user with an average recall value of 0.84. and average Fl measure value of 0.71.