Moore and Obradovich have gone on to use Twitter data to evaluate the extent and impact of coastal flooding, using information from Twitter to supplement more standard environmental monitoring instruments like tide gauges. “We’re trying to get at some of the negative effects of climate change that are widespread but not necessarily disastrous. They’re having these negative consequences across large populations, they’re interrupting people’s daily lives, they’re annoying, and they’re causing some damage,” said Moore, as quoted here. “Maybe not a huge amount, but those types of impacts are pretty important as people are trying to go about their daily lives.”
Moore goes on to say: “The main reason I like [Twitter] as a source of data is that it integrates not just a measure of typical exposure — which is ‘Did the water come onto the land in a place where it wasn’t supposed to be?’... [But also] measures ‘What are people noticing? What are people talking about?’ Twitter can give us this aggregated measure of what those social consequences of that particular flood are.”
The scientists plan to expand their research. “While the bag of words classifiers worked fine in this climate change case, we want to do more. We are looking to improve our use of NLP (natural language processing) technologies to better identify types of speech, and there are very good deep learning models. Such models are the future of where we’ll go to figure out what people are talking about and how they’re talking about it,” said Obradovich.