As the world around us continues to become increasingly digital, it has been acknowledged that there is a growing need for emotion analysis of social media content.
Automatic speech recognition is a tool used to transform human speech into a written form.
In recent times, applications have been developed to regulate and control the spread of negativity and toxicity on online platforms.
In recent times, there exists an abundance of research to classify abusive and offensive texts focusing on negative comments but only minimal research using the positive reinforcement approach.
Data in general encodes human biases by default; being aware of this is a good start, and the research around how to handle it is ongoing.
This research paper bestows a tiny contribution to this research in the form of sentiment analysis of code-mixed social media comments in the popular Dravidian languages Kannada, Tamil and Malayalam.