Sabih bin Wasi (22), a senior at Carnegie Mellon University in Qatar (CMU-Q), 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, has been created alongside classmate Rukshar Neyaz under the mentorship of assistant professor of computer science Behrang Mohit.

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, according to a statement issued yesterday.

Millions of people all over the world use Twitter to share information about what is going on around them. However, researchers have only recently begun investigating how to automatically mine and understand these opinions and sentiments using machine-learning tools.

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, the statement adds.

“Although Feedbox is still in the testing phase, it is essentially an application that facilitates the automatic search of hashtags to grab live tweets from the Internet. It then processes them, through the Twitter sentiment classification algorithm we developed in class, to display whether tweets are positive, negative or neutral,” he said. “And because I am minoring in entrepreneurship, turning concepts into business projects is something I personally love to do.”

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.

The pair’s late-night brainstorms paid off as bin Wasi and Neyaz won Best Undergraduate Research Project and Best Poster for Feedbox at the 2014 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.

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 known as www.maarvi.com

“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.”

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.

CMU-Q is a member of Qatar Foundation.