Gauging words, moods, and memes at a glance

We are now ready to proceed with building the wordclouds which will give us a sense of the important words carried in those tweets. We will create wordclouds for the datasets harvested. Wordclouds extract the top words in a list of words and create a scatterplot of the words where the size of the word is correlated to its frequency. The more frequent the word in the dataset, the bigger will be the font size in the wordcloud rendering. They include three very different themes and two competing or analogous entities. Our first theme is obviously data processing and analytics, with Apache Spark and Python as our entities. Our second theme is the 2016 presidential election campaign, with the two contenders: ...

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