HW$1$ Sentiment Analysis on Twitter$/$X

This homework assignment is to do the sentiment analysis based on a text file which contains

numerous tweets in its raw text format. All tweets collected in this file contains a key word

specified by the instructor. The key word being used is $$Trump$.$

You can use the raw tweets file $($Trump$\_$Raw$\_$Tweets.txt$)$ provided by instructor directly or you

can generate your own raw tweets file by following instructions in the file

$$Twitter$\_$Setup$\_$V$2.$pptx$.$ Your raw tweets file size at least needs to be $350$K$.$

After you have the raw tweets file ready, you need to perform the following tasks in a Jupyter

notebook file.

First you need to clean up the tweet file content to the best you can. A list of $$positive$,$

$$negative$$ and $$stop words$$ are provided to you in the assignment. For each word that is not a

$$stop word$($and$,$ the, a$,$ is$,$ as$,...),$ assign a value $+1$ for positive sentiment or a value $-1$ for

negative sentiment$.$ For the words that is not in positive$/$negative$/$stop words, count as $$others$.$

You need to answer the following questions:

$$ What$$s the word count for positive$/$negative$/$stop word$/$others$?$

$$ What$$s the ratio of positive$/$negative$/$stop word$/$others compare to the total word count?

$$ What$$s the ratio for positive vs negative word count?

$$ Do you think that the general sentiment is negative or positive? Weakly or strongly?

Submission

Submit one Jupyter notebook file $(.$ipynb$)$ with your code; be sure to explain your code using

mark downs cell and comments. No need to attach any other file.