“The model would predict the answer based on the language involved, for example, ‘The landslide most likely happened here, according to this sentence,’ and we would let it know if it was correct or not.” “We would give it a news article, and ask where a landslide might have happened,” Jaidi explained in a post. The team trained the computer to then process the natural language of landslide data so it can recognize relevant information. To weed out unhelpful information, the computer can tell if the word “landslide” is being used in a different context, like when someone wins “by a landslide.” The tool scans Reddit for news articles within a given period of time and extracts the relevant information. Now the tool automates the process, completing the search and submission in minutes. “So the more we understand landslides the more those measure can be implemented.”īefore the invention, people had to manually submit landslide information by searching through news articles. “When we know where landslides are most likely to occur, there are some preventative measures that can be implemented to avoid that sort of damage,” Jaidi said in an interview with CTV News Vancouver.
Jaidi and the team are completing their master's degrees in data science at UBC. Climate Barometer newsletter: Sign up to keep your finger on the climate pulse.The computers improve predictions of when and where landslides occur by processing news articles on the natural disasters and feeding the information to the public database, the Cooperative Open Online Repository (COOLR). University of British Columbia graduate student Badr Jaidi and his team, the Social Landslides group, trained computers to “read” Reddit to help a NASA database. A group of Canadian students are using a popular social media site to help gather information for a major space agency.
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