Analysis of Twitter Data for Business Intelligence

Abstract

Enhancement of any business requires feedback from customers. This feedback plays a crucial role in knowing the strengths and weaknesses of any business. Gaining these insights these days has become very simple. They are available in the form of—website reviews, social media, etc. The organizations have employees manually analysing this data to figure out the customer sentiments about their products and services, but this process is very time consuming and prone to human error. This cumbersome process of strategic analysis for business intelligence, can be automated. This can be done in two ways rule-based and statistical. There are various automated tools that perform strategic analysis of this data but they are mostly rule-based systems. To address these challenges, we have proposed a system which will automatically analyse customer reviews which takes tweets from twitter as an input and allows the brands to analyse what makes customers happy or frustrated, so that they can tailor products and services to meet their customers’ needs. So, in this paper we extract tweets about Samsung mobiles from twitter and use them to analyse which aspects of the product in this case mobiles are performing well and which are not and derive business intelligence from the same.