An Analytical Study on Consumer Perception for a Product against its Social Media Imprint

Abstract

Data is the key to create insights, and with the expansion of social media in the last decade, the quantity of data generated about human behavior has increased multifold. Billions of opinions are floated around the social media platforms of Twitter, Facebook, Instagram, among others covering topics ranging from politics, sports, entertainment, products, and so on. Every post has a sentiment that can be measured and processed to form insights about various products. Consumer Behavior and Insights is benefited mainly from such practices and leverages the use of public Application Programming Interfaces (APIs) and Analytics tools to cleanse and crunch unstructured data to extract meaning out of it. This paper is a study of generic perception formulated towards a brand and how it is reflected through social media. We also look at Kaggle, which also serves as a platform to correlate with data uploaded by other Data Science enthusiasts. It covers the usage of Twitter APIs, Analytics through R Language and presents a business scenario of how marketers can benefit from the use of these technology solutions.