social media

16% Conversion from Real Time Twitter Sentiment Analysis

The Challenge

Social sentiment moves at the speed of social media – streaming by the second. During COVID-19 the world came closer together, yet opinions were divided online.

The client wanted to gauge social sentiment on COVID-19 to provide data-driven insights to help align product offerings to audiences segmented by sentiment and create targeted result-driven campaigns.


Vacon created a dashboard showing real-time (hourly) analytics on COVID tweets and related sentiment. The real-time dashboard showed the number of positive, neutral, and negative COVID tweets upon the hour.

Word cloud sentiments showcased dominant words being used on Twitter.

How it works:

  • The Python-based script scans Twitter every hour, scraping tweets mentioning COVID.

  • The tweet data was cleaned from stop words and other text, including emojis.

  • After data cleaning, the text classifier was built using tf-idf methods, in combination with an SVM Classifier.

  • Once the training was complete, an API was built to report the result on live tweets to a Tableau dashboard.

Tech Stack


  • Reduced client’s customer acquisition costs (CAC) by 37%

  • Conversions up 16%

  • Click-through rates (CTR) increased by 27%

Scroll to Top