SocialMediaAnalytics

Sentimental analysis ,word cloud and topic modeling on social media data . Tweepy module of Python was used for collecting live tweets that contained the keyword 'Trump'. TextBlob module is used to calculate the polarity and subjectivity of tweets collected and they were plotted on a histogram using Matplotlib library. Wordcloud module was also used to create a wordcloud of the collected tweets. Non-negative Matrix Factorization (NMF) from Scikit-Learn and Latent Dirichlet Allocation (LDA) from GENSIM were used for conducting topic modelling of the collected tweets data. The processes were repeatedly carried out by adding geographic limitations such as 'Central America'. 'East coast' to collect the tweets streaming on the specified keyword about President Trump. Interesting insights were obtained from our analysis.