Getting Valuable Insights and Visualizations from Tweets Using Python and Twint

Getting Valuable Insights and Visualizations from Tweets Using Python and Twint

​ This article will discuss the use of twint, including how to installtwint; how to look up user information, and searching historical tweets given conditions. After gathering the data, I will use the Pandas library to clean the data and derive insights.

Recently I got myself obsessed with a Japanese tv show, I found myself cannot stop checking on Twitter, Instagram, and a Chinese app called Douban, for updates and discussions about the show. In the meantime, I ran into an introduction article about the Python library Twint, which is very convenient in gathering twitter data. While it is torturing waiting for the new episode to come out every week, I decided to use the waiting time exploring Twint and derive some insights about the show from Twitter.

This article will discuss the use of twint, including how to installtwint; how to look up user information, and searching historical tweets given conditions. After gathering the data, I will use the Pandas library to clean the data and derive insights. I hope this article can get you started withtwint, and most importantly, if you have some topics that you are very interested in exploring using data science skills, I hope my article can inspire you in structuring your thoughts, and guide you towards a starting point.

data-visualization data-scientist data-science python pandas

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