Twitter Sentiment Analysis on Tesla Earnings Call

See how Twitter users feel about Tesla’s recent earnings call

Disclaimer: The material in this article is purely educational and should not be taken as professional investment advice. Invest at your own discretion. Some external links in this post are affiliated.

In this article, I’ll analyze the sentiment of tweets from Twitter users using sentiment analysis.

“Sentiment analysis is the measurement of neutral, negative, and positive language. It is a way to evaluate spoken or written language to determine if the expression is favorable (positive), unfavorable (negative), or neutral, and to what degree.” — Clarabridge

“Sentiment analysis: the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc. is positive, negative, or neutral.” — Oxford English Dictionary

There are many methods and algorithms to implement sentiment-analysis systems, which can be classified as:

• Rule-based systems that perform sentiment analysis based on a set of manually crafted rules
• Automatic systems that rely on machine learning techniques to learn from data