Pakistani student develops social media analysis tool
A university student in Qatar has developed an application that works as a Twitter Sentiment Classification system and automatically assigns feelings - positive, negative or neutral - to live tweets.
The application, Feedbox, was created by Sabih bin Wasi and classmate Rukshar Neyaz, students at Carnegie Mellon University in Qatar (CMUQ).
Through this, bin Wasi - a computer science student - has managed to turn what began as a routine class assignment into a product that could potentially change the face of social media data analysis, Gulf Times has reported.
As a self-professed Artificial Intelligence (AI) enthusiast, bin Wasi first applied his apparent algorithmic talent to enterprise at 18 when, in his native Pakistan, he developed an online retail portal for traditional clothing – now a full-fledged business.
"I chose to study computer science because the way I look at education is that it equips me with the right knowledge to be able to help people," said bin Wasi.
"Therefore, my interests lie in directly impacting society through creativity, outside the bounds of the corporate world. I believe that with AI, most inefficient tasks around us can be made easier, quicker and smarter."
"I moved from Pakistan to Doha for my undergraduate degree and, by living an independent life, faced many problems that I had never experienced before," he said.
"That’s when I got the idea of how to solve problems through automation technology to ultimately improve people’s lives and help them make better decisions that could impact humanity."
The Feedbox application allows for the polling of how people are feeling about something at any given moment in time.
Now, if this concept is applied to corporations, brands, celebrities and even governments, the penny drops – possibly straight into bin Wasi’s and Neyaz’s bank account, a statement from CMUQ said.
Explaining how Feedbox could be applicable to the business world, bin Wasi said: "If I am the head of marketing at Apple, for instance, and I want to know how my new product is being received in the market, Feedbox can analyse people’s tweets to essentially give a summary of public sentiment about the product."
The application was created as a demonstration of the Twitter Sentiment Classification system for the CMU-Q Meeting of the Minds 2014 annual research symposium.
They also won fourth place at SemEval 2014, an international competition on computational semantic evaluation.
Bin Wasi and Neyaz are presenting their system at the SemEval workshop in Ireland this month during the 2014 International Conference on Computational Linguistics.
Bin Wasi’s most recent creation is a food management system called Foodate.
Awarded a QR140,000 prize at Al Fikra, Qatar’s National Business Plan Competition run by Enterprise Qatar, Foodate learns the content of a person’s kitchen to then manage product expiry dates in order to reduce food wastage.
Very impressive work these students are doing. What do you think?
