Welcome to solve-iwmi documentation! ¶
solve-iwmi is the repository used by our DSSG Solve team to develop the project “Amphan: analyzing experiences of extreme weather events using online data”. It contains code for Twitter data pulling, as well as the preprocessing pipeline, feature extraction, modelling and analysis techniques used throughout the project.
Project Overview ¶
With wind speeds up to 200 kilometres per hour, Cyclone Amphan was the first super cyclone to form in the Bay of Bengal since 1999. It made landfall in West Bengal, India on May 20, 2020 before tracing a destructive path northward to Bangladesh. Along the way, Cyclone Amphan damaged nearly 3 million houses, 18,000 square kilometres of agricultural lands and 449,000 electric poles, leaving 18 million affected people in its wake. Cyclone Amphan was also the costliest cyclone in the history of the North Indian Ocean; India reports 13.2 billion USD in damages in the state of West Bengal alone.
Extreme weather events are expected to increase in magnitude and frequency due to the impacts of climate change, and Cyclone Amphan is one such example. The Bay of Bengal’s unprecedentedly high sea surface temperature, which is linked to anthropogenic climate change, likely contributed to Cyclone Amphan’s speed and energy. Unfortunately, warming ocean temperatures will intensify more cyclones and hurricanes in the future — both in the Bay of Bengal and beyond. Furthermore, major flooding events are predicted to become 6 times more frequent worldwide due to climate change, and extreme droughts are expected to affect more than 1 billion people by 2050. Thus, it is imperative to develop and refine approaches for responding to extreme weather events that draw upon all available tools.
In the case of Cyclone Amphan, response efforts were complicated by COVID-19. For instance, in addition to the typical heavy rains and obstructed roads, responders had to cope with restricted mobility due to India’s nationwide lockdown; limitations on shelter capacities due to social distancing measures; and the need to obtain, use and distribute personal protective equipment. On-the-ground response efforts by governments, disaster relief organizations and civil society are no doubt crucial and life-saving following extreme weather events. Could online data serve as an additional tool to complement on-the-ground efforts, particularly when they are hindered?
We recognize that social media does not provide a complete or representative picture of extreme weather events, especially in low-resource environments where people may not have access to technology. For instance, in 2019, Internet penetration in West Bengal, India was at 29%. Furthermore, of rural Internet users in India, 72% were male. While online data should consequently not be used alone, it could help fill knowledge gaps when there are challenges reaching affected people, such as those caused by COVID-19.
We took Cyclone Amphan as our use case in exploring the potential for Twitter content to target relief efforts in response to extreme weather events. We first aimed to characterize how collective knowledge about Cyclone Amphan was produced on Twitter. Twitter is a decentralized microblogging platform, meaning that anyone with Internet access and a Twitter account can add their commentary to an issue — thus providing an opportunity to listen to the voices of people directly affected by Cyclone Amphan, in addition to public officials’ formal statements and news stories, which might have sensationalized or added layers of interpretation to on-the-ground realities. Accordingly, our first research question was: Who and which ideas are shaping the narratives around Cyclone Amphan, and whose experiences are going unheard? Next, we aimed to explore how to best support people affected by extreme weather events. This led to our second research question: Can Twitter content help identify unmet needs of people affected by Cyclone Amphan? If so, how?
The resulting web tool aims to help users better understand people and organizations’ diverse experiences of and reactions to Cyclone Amphan, with implications for disaster relief efforts.
Getting Started ¶
The main documentation. The user guide contains an abridged description of our project as well as realizations of it and how to apply it. It also contains the exact API of all functions and classes, as given in the docstring.
Technical Report ¶
The technical report contains a detailed description of the work developed towards this project.
Additional Information ¶
about section of cluster-over-sampling.
See the README for more information.