Text Analysis Using Python NLP Paper

Description

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.

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