Topic Modeling in R

As a part of Twitter Data Analysis, So far I have completed Movie review using R& Document Classification using R. Today we will be dealing with discovering topics in Tweets, i.e. to mine the tweets data to discover underlying topics– approach known as Topic Modeling. A statistical approach for discovering "abstracts/topics" from a collection of text documents based on statistics of each word. In simple terms, the process of looking into a large collection of documents, identifying clusters of words and grouping them together based on similarity and identifying patterns in the clusters appearing in multitude. When we apply Topic Modeling to the above statements, we will be able to group statement 1&2 as Topic-1 (later we can identify that the topic is Sport),statement 3 as Topic-2 (topic is Movies), statement 4&5 as Topic-3 (topic isdata Analytics). Topic Modeling can be achieved by using Latent Dirichlet Allocation algorithm.