MIS 2502: Data Analytics
Sentiment and Text Analysis in Businesses
With everything taking place on social media platforms, companies have now start to invest in new tools to help improve their companies. Companies are investing in sentiment analysis. Sentiment analysis is the “process to determine the attitude or polarity of opinions or reviews written by humans to rate products or services” (Younis, 2). In other word, this is the process that helps companies examine people reactions to their products or their brand through products reviews. Text mining or analysis is another tool, companies can use to gather feedback data. Text mining is an “automated process of detecting and revealing new, uncovered knowledge and inter-relationships and patterns in unstructured textual data resources” (Younis, 1). Sentiment analysis relates to texting mining because text mining helps gather and analyze an abundant amount of unstructured text documents to predict any patterns or trends. Text mining is useful when it comes to feedbacks because it can help companies study the “face value of the words, including grammar and the relationships among words” (Sigler), in order to get certain feedbacks by filtering out non-important information.
In MIS 2502, we learn that all business action starts with data. Companies use data to enhance productivity and to solve business problems. Sentiment and text analysis are tools that can transform unorganized data from text into valuable information. A demonstration of sentiment analysis being use is how Budweiser advertise during the July 4th. With sentimental analysis brands like Budweiser knows the feedbacks of Americans about beer products during July 4th. There is an estimate that Americans spend about $1 billion on beer every July 4th weekend (Gannon). With this knowledge, Budweiser try to focus their attention on making their beer the “America” beer by rebranding it in 2016. With the help of sentiment analysis, Budweiser released ads that align their brand with the American values to bring in more consumers.
References:
Gannon, Will. “Measuring Brand Reputations of Beverage Companies around National Holidays – Monthly Media Review with the AYLIEN News API.” Aylien, 13 Apr. 2018, blog.aylien.com/general/.
Sigler, Lisa. “Text Analytics vs. Sentiment Analysis.” Clarabridge, 25 July 2015, www.clarabridge.com/blog/text-analytics-vs-sentiment-analysis/.
Younis, Eman M. G. and Jeffrey Breen. “Sentiment Analysis and Text Mining for Social Media Microblogs using Open Source Tools: An Empirical Study.” (2015).