Twitter is one of the most popular social networks through which millions of users hare information and express views and opinions. The rapid growth of internet data is a driver for mining the huge amount of unstructured data that is generated to uncover insights from it.
In the first part of this post we explore different text mining tools. We collect tweets containing the “#MachineLearning” hashtag, prepare the data and run a series of diagnostics to mine the text that is contained in tweets. We also examine the issue of topic modeling that allows to estimate the similarity between documents in a larger corpus.
Download and read the full document : Text Mining and Social Network Analysis of Twitter Data Part 1