I need a analysis report for the following visualization. The visualization is a

Question

I need a analysis report for the following visualization. The visualization is about distribution of frequencies for different positive and negative word counts present in a review.

W Writer Home Insert Page Layout References Review View ection Special Feature:s Sign in X cut?T -KA-4 I- ?, ??'A, ?--x-? ?? E-: AaBbCcD AaBkAaBbC AaBbc. A Times New Roman12 B 1 u.tB-X' ?, wMy wPS copy Format ? ??,? ?, Normal Heading i Heading 2 Heading 3F New Style, find and Replace ?, - Paste, select, settings. Painter ? ??E'G ? € Assignment2.2018-SP2 (31.doc xeD Assignment 2 SP.docx × Frequency of Word Counts 0 2 4 6 8 10 12 14 16 18 Positive Word Count 0 2 4 6 8 10 12 14 16 18 Negative Word Count Page Num: 3 Page: 3/4 Section: 1/1 Row: 12 Column: 1 Words: 879Spell Check O Type here to search 839 PM 3/06/2018

Explanation / Answer

Analysis Report

Premise : Given a particular review, the number of positive words and the number of negative words are counted and then the frequencies of positive words and frequencies of negative words. A bar graph is then developed with the frequencies of these word counts.

Analysis : Let's look at the Positive word count first. We see that the frequency increases from word count = 0 and peaks at word count = 4 and then falls exponentially till around a word count = 18.

For the negative word count, the frequencies is at a maximum at and start falling exponentially from word count = 0 itself.

We infer that the reviews have a lot more positive words in them than negative ones. The typical value of positive words are around 300,000 - 600,000 words and then it's lesser on either side. This translates to scenarios wherein the reviewer would rarely not say anything positive in the review and that there would be something positive in every review as there should be, which is seen in the graph. And very rarely do situations arise where the reviewer floods the review with positive words which is why high word counts of above 8 have lesser frequencies. Also from the positive word count graph, we see that the graph rises in an almost quadratic fashion and then falls in an exponential way.

In the negative word count, we see that the word count = 0 itself has the maximum frequency. This means the most common scenario is where the reviewer hardly mentions negative words and the likelihood of mentioning negative words decreases with increasing number of negative words in a review.

Conclusion : On the overall then, it looks like positive reviews are much more common than negative reviews. The typical values for positive word counts are around 400,000 - 600,000 (assuming the scale of graph = 100,000) is correct and for the most frequently encountered negative word counts in a review are close to 0 - 100,000.

Cheers!

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