To take it further, companies could combine this with sentiment analysis to find out which of their products are written about the most and how positively or negatively viewed they are.įor example, here is a word cloud from ‘Laudato Si’, a Vatican encyclical put out 6 years ago. For example, if you are able to get text of speeches or writings of a public figure, you can easily visualize the most important topics that are covered with a word cloud. Word cloudsmay not be the most penetrating way to analyze text data but, can be a very engaging and simple means for analyzing text data and discovering words or common word patterns that frequently appear.
In this article, we are going to scrape a series of articles from several different news sources and once we have extracted the keywords from each of the articles we can create a word cloud that displays the most important topics of the day from the keywords obtained from each article using Newspaper3k. You can check out the full code on GitHub here. Here I’m going to demonstrate for you a project which takes articles from a set of different news agencies, picks out the most used words from them, and shows a word cloud of the results with the help of NLP and Matplotlib. To carry on from our introduction to Newspaper3k, we can now take our basic knowledge and realize the possibilities of what we can do with this library.
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