Text Mining and Sentiment Analysis with Tableau and R

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3-10-2020, 07:08
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  • Text Mining and Sentiment Analysis with Tableau and R

    Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz
    Language: English | VTT | Size: 478 MB | Duration: 4 section | 36 lectures | (3h 57m)

Text Mining and Sentiment Analysis with Tableau and R Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: aac, 48000 Hz Language: English | VTT | Size: 478 MB | Duration: 4 section | 36 lectures | (3h 57m) What you'll learn Connect Twitter and R to harvest Tweets for certain keywords Perform sentiment analysis based on a simple lexicon approach Clean and process Tweets for further analysis Export text based data and sentiment scores from R Use Tableau to visualize sentiment analysis data Identify situations where sentiment analysis can be applied in a company Requirements You can use either Tableau Public (free) or Tableau Desktop You need R and RStudio ready on your machine We will create a Twitter developer account (Twitter account required) You need basic R skills (course R Basics) Description Extract valuable info out of Twitter for marketing, finance, academic or professional research and much more. This course harnesses the upside of R and Tableau to do sentiment analysis on Twitter data. With sentiment analysis you find out if the crowd has a rather positive or negative opinion towards a given search term. This search term can be a product (like in the course) but it can also be a person, region, company or basically anything as long as it is mentioned regularly on Twitter. While R can directly fetch the text data from Twitter, clean and analyze it, Tableau is great at visualizing the data. And that is the power of the method outlined in this course. You get the best of both worlds, a dream team. Content overview and course structure: The R Side Getting a Twitter developers account Connection of Twitter and R Getting the right packages for our approach Harvesting Tweets and loading them into R Refining the harvesting approach by language, time, user or geolocation Handling Twitter meta data like: favorites, retweets, timelines, users, etc Text cleaning Sentiment scoring via a simple lexicon approach (in English) Data export (csv) for further Tableau work Tableau Side: Data preparation for visualizations Quick data exploration Dashboards Visualizing - Popularity of different products Popularity between different locations on a map Changes in popularity over time You only need basic R skills to follow along. There is a free version of Tableau called Tableau public desktop, or even better: as a full time college student you can get a free but full version of Tableau desktop professional. The course comes with the R code to copy into your R session. Disclaimer required by Twitter: 'TWITTER, TWEET, RETWEET and the Twitter logo are trademarks of Twitter, Inc or its affiliates.' Who this course is for: Data professionals Analysts in marketing, finance, ... Marketing professionals Entrepreneurs Researchers https://www.udemy.com/course/text-mining-and-sentiment-analysis-with-tableau-and-r/ Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me
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