wk-7

Running Head: SENTIMENT ANALYSIS 1

SENTIMENT ANALYSIS 2

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SENTIMENT ANALYSIS

What are the common challenges with which sentiment analysis deals? What are the most popular application areas for sentiment analysis? Why?

Also referred to as opinion mining, sentiment analysis is a very critical process in business that involves the use of machine learning, data mining, and natural language process in interpreting data that helps in understanding the feedback of the customers (Sharda, Delen, & Turban, 2020). Customer satisfaction is critical in every business, and no business can survive without offering customers the satisfaction they require. This model is implemented in domains like customer service, customer voice, social media monitoring, and market research.

The clients' insights are tracked, and thus, the brand can know what the client's behavior pattern is and know how the brand will reposition itself in the market. Similarly, this analysis helps in dealing with the customers who launch complaints regarding the brand or the products or services. This model does this through processing the call to the designated personnel depending on the issue that the customer want addressed as well as depending with the urgency of the customers’ request. This model is also used in market research. It helps analyze and understand the trends o the market and predict where the market is headed, and convert the knowledge obtained to the brand's advantage. These analyses are done in real-time, and thus the brand can gain maximum benefit. The companies can, therefore, reduce the risks and increase their revenue.

Similarly, by analyzing and predicting market trends, the management can take drastic measures and make informed decisions. This is because a brand can analyze its competitors and what can be done to stay on the top and maintain relevance in the market. Despite all these advantages, this tool has some few drawbacks that include its complexity in handing, and its inoperability with different domains is also very wanting. However, if it is used correctly, it can help a brand to analyze the clients and the market and stay abreast in the market.

References

Sharda, R., Delen, D., Turban, E. (2020). Analytics, data science, & artificial intelligence: systems for decision support, global edition. pearson education limited. Retrieved from: https://www.pearson.com/us/higher-education/program/Sharda-Analytics-Data-Science-Artificial-Intelligence-Systems-for-Decision-Support-11th-Edition/PGM2067063.html