Use the attached dataset for this activity.
- Open the file and get familiar at a high level with the dataset.
- Follow the step-by-step directions on how to conduct the Add-In of the Azure Machine Learning function in Excel and the steps needed to conduct a text sentiment analysis and score for each of the product reviews in your data set for this activity.
- After conducting that process, answer these questions in a 3-4 page paper with screenshots:
- Provide a screenshot showing the Azure Machine Learning add-in and output of the sentiment scores on at least the top few products you can show as evidence of the application.
- Conduct an assessment of the sentiment scores and answer the following:
- For each of the Positive, Negative, and Neutral reviews, answer the following for each score type:
- What was the total number of this type of sentiment?
- What was the average sentiment score for this type of sentiment?
- Based on the sentiment, do you think that there is enough of this type to warrant a need for the company to conduct further research on their product reviews such as fixing problems or marketing?
- For the negative reviews, read 4-5 different reviews and see if you think any of them have anything in common, or are they drastically different. Explain.
- For the negative reviews, do you think that the average negative sentiment score has merit based on the reviews you are reading, why or why not?
- Finally, provide a 2-3 paragraph summary on your final thoughts and findings on this sentiment analysis, as if to an executive in the business.
Formatting Guidelines:
This paper should be between 3-4 pages in length where you both provide the screenshots and your answers to each question in APA Format, 12 Pt. Font, Times New Roman, and double-spaced.
