Air pollution is a global challenge for cities across the globe. Understanding the public perception of air pollution can help policymakers engage better with the public and appropriately introduce policies. Accurate public perception can also help people to identify the health risks of air pollution and act accordingly. Unfortunately, current techniques for determining perception are not scalable: it involves surveying few hundred people with questionnaire-based surveys. Using the advances in natural language processing (NLP), we propose a more scalable solution called Vartalaap (which means Conversation in Hindi Langauge) to gauge public perception of air pollution via the microblogging social network Twitter. We used more than 2.2M tweets on Delhi, India, from a 7.3M tweet dataset, which we curated for air pollution perception studies. We find that (unfortunately) the public is supportive of unproven mitigation strategies to reduce pollution, thus risking their health due to a false sense of security. We also find that air quality is a year-long problem, but the discussions are not proportional to the level of pollution and spike up when pollution is more visible. The information required by Vartalaap is publicly available and, as such, it can be immediately applied to study different societal issues across the world.
https://doi.org/10.1145/3449170
The 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing