Quantum Computing - A Web Scraping Project

Posted on Oct 2, 2018

Sentiment Analysis

I struggled at first to perform sentiment analysis but ultimately discovered TextBlob application. TextBlob is a Python library that provides an API for various language processing tasks. The results can be found below.

Most tweets were positive, although some expressed fears about the negative consequences of QC-enhanced AI. As you can see below, the more positive the tweet, the greater likelihood that it was retweeted. In the following graph, a positive polarity corresponds to a more favorable sentiment; a polarity of 0 corresponds to a neutral or indecipherable sentiment; and a negative polarity corresponds to a less favorable sentiment.

Statistics and Relationships

After performing the above data analysis, I examined various relationships between Twitter feature actions (Like, Reply, Retweet). In other words, I investigated how the Twitter-sphere reacted to tweets about quantum computing. I found there was a strong relationship between whether tweets were retweeted and liked:

A closer look into the "Likes" Density Plot:

The relationships between these three features for QC-related tweets can be visualized below.

Table and Correlations


Link to Github & Web Scraper Python Code:


About Author


Michael is currently a Data Science Fellow at the NYC Data Science Academy. He graduated from the Wharton School of the University of Pennsylvania with a B.S. in Economics before securing the position of Investment Banking Analyst at...
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