Text Analysis Using Python NLP Paper

Preparation of the text data      for analysis

Elimination of stop words,       punctuation, digits, lowercase

Identify the 10 most frequently      used words in the text

• How about the ten least       frequently used words?

How does lemmatization change       the most/least frequent words?

Explain and demonstrate this        topic

• Generate a world cloud for the      text
• Demonstrate the generation of      n-grams and part of speech tagging

Create a Topic model of the      text

• Find the optimal number of       topics

test the accuracy of your       model

Display your results 2       different ways. 1) Print the topics and explain any insights at this       point. 2) Graph the topics and explain any insights at this point.

• Important: Make sure you provide complete and thorough explanations for all of your analysis. You need to defend your thought processes and reasoning.