Sentiment analysis is a big data problem which seeks to determine the general attitude of a writer given some text they have written. for instance, we would like to have a program that could look at the text "the film was a breath of fresh air" and realize that it was a positive statement while "it made me want to poke out my eye balls" is negative.
one algorithm that we can use for this is to assign a numeric value to any given word based on how positive or negative that word is and then score the statement based on the values of the words. but, how do we come up with our word scores in the first place?
that's the problem that we’ll solve in this assignment. you are going to search through a file containing movie reviews from the rotten tomatoes website which have both a numeric score as well as text. you’ll use this to learn which words are positive and which are negative. the data file looks like this:
4 this quiet , introspective and entertaining independent is worth seeking .
1 aggressive self-glorification and a manipulative whitewash .
4 best indie of the year , so far .
2 nothing more than a run-of-the-mill action flick .
2 reeks of rot and hack work from start to finish .
note that each review starts with a number 0 through 4 with the following meaning:
0 : negative
1 : somewhat negative
2 : neutral
3 : somewhat positive
4 : positive