Sentiment analysis can reveal how people are truly responding to a product, service, or social issue. Using Twitter data, Pierre DeBois demonstrates how to conduct a sentiment analysis in R programming—a standard choice among data scientists and programmers to explorer data and associated statistical techniques.
Twitter is a great platform for sentiment analysis because of the range of user responses, especially in reaction to social issues raised on the platform. Pierre walks you through using R for sentiment analysis, covering R basics, packages that can be used on Twitter (and other social media) to download data, functions to parse hashtags and comments in Twitter, and best practices in displaying results. The result is a better understanding of trending topics and remarks about brands, services, and products as well as a means to identify grievances and key social issues.
Pierre DeBois is the founder of Zimana, an analytics consultancy that helps organizations achieve profitability improvements in marketing and web development and within their business operations. Zimana’s blog is an AllTop analytics blog, while its @zimanaanalytics was named among the top 100 Twitter accounts for big data discussion according to the Big Data Republic and PeerIndex #BigData100. Pierre also leads digital marketing and analytic workshops for clients like the City of Chicago Treasurer’s Office, General Assembly, and the Yceeya Network and at events such as Blue1647, the DX Summit, and Interop ITX and Content Marketing World. Pierre has contributed articles to CMS Wire, All Analytics, and DMNews and is an associate editor of business book reviews for Small Business Trends and a technical editor for two Pearson Que publications. He has been featured in the Chicago Sun Times and is a presenter in the Google Get Your Business Online program. A native of Gary, Indiana, Pierre holds a degree in mechanical engineering from Prairie View A&M University and an MBA from Georgia Tech.
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