Students write successful IBM Big Data proposals
Early in the fall semester, Adjunct Assistant Professor Susan Zeng’s Big Data class toured the IBM Center in Columbia. Following the tour, Michael Robison, an IBM manager, made a presentation about the company’s Smarter Planet initiatives, including the “Students for a Smarter Planet” program, which seeks to engage students in community improvement projects through use of IBM technologies.
“A quarter of each student’s grade is to propose and complete a semester project,” said Zeng. “I had students break into pairs to work on the exercise as a team. For their proposals, they had the choice of addressing the ‘Students for a Smarter Planet’ themes to compete for IBM awards.”
“Smarter Planet” themes include energy, sustainability, analytics, water, commerce and public safety. Winning proposals receive a requested budget award of up to $3,000, and if selected, teams must agree to blog about their projects as they progress.
IBM selected two proposals from student teams in Zeng’s class:
Team “Zeros and Ones,” consisting of computer science master’s students Hongfei Cao and Mike Phinney, is working on the project, “Identifying Gene Duplications Across DNA Sequences.”
Team “Geek Inside,” consisting of computer science master’s students Caiwei Wang and Zhaoyu Li, is working on “Real-time Emotion Analysis On Twitter.”
“We came up with four ideas and talked about what was the most valuable or attractive to people,” said Wang of Geek Inside’s project.
She and Li decided to analyze “tweets” about various products — such as Apple’s iOS-7 operating system — for emotional reactions to them.
“Social networking is very interesting and is a fortune for companies,” said Li. “If I buy a computer, I take a picture and say, ‘This is a good computer,’ and share it with my friends. It’s a good source for companies to learn about how people feel about their products. We will use tools to analyze people’s language — happy or sad.”
The $1,000 they received from IBM was used to purchase reference materials for the data tools they will use to complete their project. Li explained the project in his blog:
“Twitter is one of the most popular social networks. People tweet their emotions, feelings, status and locations and share interesting things with their friends.
“However, sometimes these data are very large and hard to analyze. Our project is to use big data analytic technologies to evaluate this massive amount of data and extract the most useful information, feelings. In addition, we plan to make it work in real-time so that the company can see the marketing reaction instantly. It can also help companies to provide better customer services in the future. For the investors, they can use this information to help them make decisions on investment. What is more, people can make stock price predictions and decide whether to buy their stocks or not.
“Our project is in line with the topic “Smarter Commerce” in IBM Smarter Planet. It can help companies to optimize their marketing processes by tracking online behavior to inform marketing decisions, and capturing data from customers’ interactions for real-time marketing. It provides a way for them to do better business.”
Zeng said the project has proved to be a great way for students to explore the field of Big Data and she will repeat the exercise when she next teaches the class in the 2014 fall semester.