Kate H
- Research Program Mentor
MS at Columbia University
Expertise
Machine Learning, Natural Language Processing
Bio
I am currently pursuing research on Misinformation and Fact-Checking using Natural Language Processing. My present focus is on COVID-19 scientific claim verification. In general, I am interested in how Machine Learning methods can be leveraged to effect positive change in the world, and especially interested in ensuring that those methods are fair and unbiased. When I'm not coding, I love reading and being active outdoors!Project ideas
Impact of Natural Disasters on Climate Change Sentiment
Climate change is a polarizing topic, and many people continue to renounce its existence. Social media, and tweets in particular, are a great way to gauge the trending views on a topic over time. In this project, the aim will be to show not only how the trends of social media expressions of climate change belief/disbelief have changed over time, but also to compare how the trends in these beliefs vary with the occurrence of large-scale natural disasters. Are people more likely to talk about climate change when Texas experiences an unprecedented storm and a large swath of the state loses power? Or when Australia experiences one of the worst wildfire disasters in history? Do these events lead to an uptick in assertions of climate change belief, or an uptick in assertions of disbelief? Can we predict the public’s response to a natural disaster in terms of their expressions about climate change? As these natural disasters become more prevalent, understanding how they impact the public’s views on climate change could provide useful guidance on how best to target climate change related messaging. Using NLP techniques to analyze twitter data, we will build an understanding of climate change opinion trends.