UBC graduate students trained computers to “read” news articles about landslides on Reddit to bolster a NASA database, which could improve predictions of when and where these natural disasters will occur.
For their Master of Data Science in Computational Linguistics capstone project, Badr Jaidi and his team, the Social Landslides group, trained computers to automatically extract useful information from relevant news articles about landslides that were posted to Reddit. In this Q&A, he discusses how this tool could end up saving lives.
Q. Why do we need this tool?
A. According to the World Health Organization, landslides are more widespread than any other geological event. They’re so destructive, and we don’t have that much data about them. The more accurate landslide data you have, the more it’s possible to accurately predict which places have higher risk, which could ultimately save lives.
NASA collects such information in a public database called the Cooperative Open Online Repository or COOLR and uses this to predict when and where landslides will occur. But people have had to manually submit landslide information or search for news articles and data one by one which is pretty tedious. Our tool automates that process, completing in minutes what previously might have taken months.
That would free up resources for more important research, and would also mean we get more data, faster, potentially improving research in landslides generally, as well as NASA’s landslide predictions.
Please read the full Q+A at the Faculty of Science website.
Through Strategy 8: Student Research, UBC is expanding opportunities for undergraduates to gain first-hand experience in research and is strengthening research experiences for graduate students and postdoctoral fellows.