A Survey on Uncovering trending stories from Twitter by extracting ground truth from datasets

Abstract

Today’s online social networking services generates series of conversation that shows the all kinds of real-world events, however the large amount of data are available on social network. This data can be filtered for finding trending topics using standard natural language processing techniques. An Uncovering trending stories is therefore a building block is to extract and summarizes the information raised from social networking services, this building block is very useful to find trending stories and its initiator .There are verity of methods that improves quality of result. This paper explores about different Topic detection method for uncovering trending topics from twitter datasets, such as Document-Pivot methods, Feature-Pivot methods, Frequent Pattern Mining, Soft Frequent Pattern Mining and BNgram.