D2: CASE STUDY - SENTIMENT DATA MINING PREDICTS POLITICAL OUTCOMES (Essay Sample)

Instructions:

D2: Case Study - Sentiment data mining predicts political outcomes No unread replies.No replies. Directions Read the "Case Study - Sentiment Data Mining Predicts Political Outcomes" in Chapter 4. Answer the following questions: Why was BrandsEye able to correctly predict the results of the national referendum on Brexit and the US Presidential Elections? Be specific. Since BrandsEye correctly predicted the results of the national referendum on Brexit and the US Presidential Elections, how could Nike use a tool like BrandsEye to gather information about its customers? Suggest some ideas of the type of customer data Nike would collect and how it could be used. Please post your initial response by 11:59 PM ET Wednesday, and comment on the posts of two classmates by 11:59 PM ET Sunday. Your initial post: Respond to the questions posed above. Your total response should be at least 200 - 300 words. Include specific reasons or examples to support your answer. Before you post, view the discussion rubric to see how you will be graded. Comment on AT LEAST 2 of your classmates' postings: View at least two of your classmates’ postings and respond to these two postings. Your response should be at least 80 words each. Use the ABC METHOD of RESPONDING to POSTS Acknowledge the contributions of the person to whom you are responding. Build on the ideas of the original posting by adding your own thoughts or analysis. Contribute to the discussion by asking a probing question that deepens understanding of the material and/or provide a supplemental resource. NOTE: You will need to POST your response FIRST before you can read and respond to your classmates. Return to this Discussion in a few days to read the responses to your posting and responses. Note what you have learned and/or any insights that you have gained from your colleagues’ comments. Before posting your response view the discussion rubric to see how you will be graded. source..

Content:

Sentiment data mining predicts political outcomes First Name Last Name Institutional Affiliation Course Number and Name Instructor’s Name and Title Assignment Due Date Sentiment data mining predicts political outcomes Soon after successfully predicting the outcome of the Brexit referendum, BrandsEye began its analysis of the electoral process in the United States. In 2016, BrandsEye drew the attention of media outlets worldwide when it predicted that Donald Trump would defeat Hillary Clinton in the presidential election by utilizing its one-of-a-kind combination of artificial intelligence and human audiences. According to BrandsEye's observations, traditional polls do not appear to capture social media's immense and intense emotional discontent (BrandsEye, 2019). After making an accurate forecast of the result of the Brexit referendum in June, analysts working for BrandsEye speculated that a result in the election that was as surprising would take place. BrandsEye is an open-source, scalable, and adaptable platform for social opinion mining and commercial information. This tool may be utilized by corporations, private organizations, and even government agencies to monitor debates about their policies and brands. BrandsEye is a tool that can be used by businesses and other types of organizations to learn what drives the conversation around them (Saura et al., 2019). Organizations can circumvent issues this way and make the most of positive responses, particularly from those who serve as brand ambassadors. In addition, BrandsEye offers its consumers a platform to engage in one-on-one communication with famous public personalities. Additionally, BrandsEye can measure conversations in many different languages and dialects. This ensures that businesses are constantly aware of what is said about them, regardless of the language used. When collecting customer information with the help of BrandsEye, Nike could use the tool for analytical displays and reports. Nike could use the tool to customize reports and export them. In addition, the organization can use the tool f...

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D2: CASE STUDY - SENTIMENT DATA MINING PREDICTS POLITICAL OUTCOMES (Essay Sample)

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