Can we trust sentiment analysis? It was imperative that you explain your method?
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Can we trust sentiment analysis? It was imperative that you explain your method?
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Solved in 3 steps
- In your own words, please explain the notion of sentiment analysis.To what extent can one rely on the results of sentiment analyses? In your opinion, what process is employed to accomplish this goal?Damon Davis was creating the Drano Plumbing Company's spreadsheet. He determined that the net income would be $50,000. When he tallied the columns on the Balance Sheet, the totals were as follows: debit, $400,000; and credit, $300,000. What was the most likely reason for this discrepancy? If this was not the case, how should he proceed to determine the source of the error?
- What is your mental picture of an email? The path of an email starts and finishes in the same location. Keep track of your results. Why are differences necessary to begin with? Have you ever seen how model abstraction (or amount of detail) may vary?Is there any way to determine how trustworthy the results of sentiment analysis actually are, and if so, what is that technique? What do you believe is the typical method for achieving this goal?When you consider email, what pictures come to mind? How is an email sent from point A to point B? List all you have learnt to date. Who knows the reason for these variances, and if so, what are they? Do your models have varying degrees of complexity?
- After listing the different mathematical procedures, arrange them in a rational fashion.Are there truly just three of you?As a benchmark, use a normalized histogram. Is the absence of a non-normalized histogram in a normalized histogram acceptable?What mental representations do you associate with the concept of email? What are the subsequent events that occur after an email is dispatched to its intended recipients? Please document any current thoughts that are occupying your mind. Is there a discernible cause or agent that can be held accountable for these disparities? To what extent do your models exhibit efficacy when applied to datasets of varying levels of complexity?
- How can we evaluate the robustness of our program, and what elements influence it?When you think of an email, what comes to mind? The origin and destination of an email are the same place. Take notes on your research. Let's start with the obvious question: what's the deal with all the variations? Take note of how the degree of model detail (or abstraction) varies.When you think of an email, what comes to mind? All emails begin and end at the same position. Keep track of your findings. To begin with, why are there so many differences? In terms of model level of detail (or abstraction), how can you tell?