| Title | Twitter Data Analytics |
| Authors | Sowvik Kanti Das Fabiha Nazmi Islam, Shatadru Shikto, Raufir Ahmed Shanto |
| Supervisor | |
| Semester | Fall, 2016 |
Finding a trending topic or a popular topic that are commonly discussed by public is very difficult these days. This is because we know the popular topics by just gossiping and knowing from others. For example, a company wants to know its customer feedback for any product and for that they start polling, or send out questionnaires or allow customers to review and comment directly on their online website. But all these are direct approaches and only limited to those who are loyal customers and eager to give their opinion. There is no accuracy to know how popular the product is globally.
Our solution to this problem is to introduce a single page web application and a common platform where any user can know the current status of any topic at a global level. Since there is no requirement of user to sign up and open up an account to log in, anyone will be interested to visit the website for relevant information. Almost every person, especially the corporate and commercials, use the social media Twitter. Now, since we know that the Twitter posts are always streaming and posting in real time, we retrieve the relevant Twitter data and give output to the user with a particular query. We present data visualization collecting all these streaming data in two ways: (1) Visualization of tweets by 3D bars reacting to number of tweets live on a specific geo-location on 3D globe (2) Visualization of tweets on 2D statistical bar charts reacting dynamically to the number of tweets in a location on real time.
The outcome of our project is the amalgamation of various data visualization concepts. We not only make our system smarter but more friendly and accurate since this gathers up the ‘reactions of the world!’. The response time of the system is also pretty impressive. Companies can now solve their problem with customer feedback using our website completely free which can also provide knowledge of how many people across the world are tweeting on popular topics.