Concordia Big Data Analytics Class Students Present in Hawaii
Four students from Concordia’s Big Data Analytics class have been invited to present their research at the 2018 International Conference on Big Data and Education in the US this spring.
The conference, which will be held in Honolulu, Hawaii, in March, received submissions from nearly 12 countries and regions around the globe. Submissions were reviewed by international experts, and 40 papers were selected for presentation. Among them were three submitted by Concordia students.
QUANTIFYING AIR QUALITY AT CONCORDIA WITH BIG DATA USING WATSON ANALYTICS – ZI XUAN TEH, NICHOLAS HO, AND PETER TONG
Abstract: Grey skies and dry eyes are a shared experience among all of us here in Shanghai. We all remember those days where the AQI was abnormally high, but how was the air quality indoors? This project made use of a massive dataset spanning multiple school years––through the use of big data analytics, we were able to find trends and uncover insights regarding the allocation of air quality in Concordia.
INVESTIGATING CHRONOLOGICAL CORRELATIONS BETWEEN LUNG DISEASE AND CLIMATE DATA – ZEMEI AMANDA LEE AND PETER TONG
Abstract: Asthma is a chronic lung disease that affects over 300 million people worldwide. Yet, its environmental causes remain indefinite — what are less known pollutants that are potentially contributing to asthma development? How can these act as early indicators of rising asthma rates to assist medical professionals in their practice? The goal of this project is to investigate the progression of asthma in recent years with a US geographical focus. This data was then compared to the trends of over twenty minor, but potent, air contaminants in those areas.
FAKE NEWS: THE INSIDE SCOOP-SEEKING UNDERSTANDING WITH WATSON ANALYTICS – MEGAN YANG AND PETER TONG
Abstract: Fake news is the deliberate creation of news stories to fool, entertain or increase traffic, typically stretching the facts or lacking details. Why has it become so important? What do people think about it? How can we recognize what's real and what's fake in the news? These are all questions that this project seeks to answer. Tools like sentiment analysis, Kaggle, Gallup, Google Trends, Google Public Data Explorer, and Watson Analytics, helped to unravel the mysteries of fake news. Through this project, general opinion on the phenomenon and responses from tech moguls should demonstrate the flaws of communication in the media. These understandings about fake news leads to more informed consumption of news, an essential skill in today's society.
Concordia teachers Dr. Peter Tong, Michael Lambert and Craig Gingerich submitted a joint paper that was also chosen for presentation.
“I am so thankful to be at Concordia,” gushes Dr. Tong, who teaches a big data course in Concordia's high school, “and to be coaching amazing students and working with awesome colleagues.”
Big Data Analytics is one of nine high school applied learning courses offered at Concordia.
