Topic Sentiment analysis is contextual examination of words, and words within sentences across all social media...

 

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Topic Sentiment analysis is contextual examination of words, and words within sentences across all social media platforms and web sites, in order to reveal the sentiment of the writer. All texts (unstructured texts) are mined to gain insight into various subjects of interests with regard to the degree of positivity/negativity revealed in the text. In this manner, unstructured texts are transformed into a quantitative scale and the results can be presented in charts and tables so that important information can be revealed and easily digested. The purpose of this assignment is to give you an experience of how sentiment analysis works at a rudimentary level. In reality, the analysis is done by software applications that examine each word within the context of the sentence, along with other metrics on the frequency/count metrics, sources, demographics, key words, etc. The analysis is then connected to data visualization tools to create dashboards with charts and alerts that are updated as new messages are posted. In this assignment, learn from the example of a sentiment analysis to give you a better grasp of dealing with unstructured data. Part I. 1. Discuss the importance of unstructured data in understanding customers' behaviors, actions, pains and gains in much greater depth? 2. How can you use unstructured data to improve products and operational effectiveness? 3. How can unstructured data help the firm spot upcoming emerging trends, before they show up on the firm's CRM systems? 4. Discuss the controversy regarding the value /effectiveness of the Net Promoter Score (NPS). What problems does HBR version of NPS 3.0 solve? Topic Sentiment analysis is contextual examination of words, and words within sentences across all social media platforms and web sites, in order to reveal the sentiment of the writer. All texts (unstructured texts) are mined to gain insight into various subjects of interests with regard to the degree of positivity/negativity revealed in the text. In this manner, unstructured texts are transformed into a quantitative scale and the results can be presented in charts and tables so that important information can be revealed and easily digested. The purpose of this assignment is to give you an experience of how sentiment analysis works at a rudimentary level. In reality, the analysis is done by software applications that examine each word within the context of the sentence, along with other metrics on the frequency/count metrics, sources, demographics, key words, etc. The analysis is then connected to data visualization tools to create dashboards with charts and alerts that are updated as new messages are posted. In this assignment, learn from the example of a sentiment analysis to give you a better grasp of dealing with unstructured data. Part I. 1. Discuss the importance of unstructured data in understanding customers' behaviors, actions, pains and gains in much greater depth? 2. How can you use unstructured data to improve products and operational effectiveness? 3. How can unstructured data help the firm spot upcoming emerging trends, before they show up on the firm's CRM systems? 4. Discuss the controversy regarding the value /effectiveness of the Net Promoter Score (NPS). What problems does HBR version of NPS 3.0 solve?