Vartalaap: What Drives #AirQuality Discussions: Politics, Pollution or Pseudo-science?
Rishiraj Adhikary, Zeel B. Patel, Tanmay Srivastava, Nipun Batra, Mayank Singh, Udit Bhatia, Sarath Guttikunda
Abstract
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 to gauge public perception of air pollution via the microblogging social network Twitter. We curated a dataset of more than 1.2M tweets discussing Delhi-specific air pollution. 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.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 02bf1c8e-5674-473c-8a50-bc1209654dd6Related papers
- Exploring Temporal and Multilingual Dynamics of Post-Disaster Social Media Discourse: A Case of Fukushima Daiichi Nuclear AccidentSaiyue Lyu, Zhicong LuCSCW 2023 · 12 citations
- LEAP: LLM-powered End-to-end Automatic Library for Processing Social Science Queries on Unstructured DataChuxuan Hu, Austin Peters, Daniel KangVLDB 2025 · 7 citations
- On the Reliability and Validity of Detecting Approval of Political Actors in TweetsIndira Sen, Fabian Flöck, Claudia WagnerEMNLP 2020 · 23 citations
- Spanning the Spectrum of Hatred Detection: A Persian Multi-Label Hate Speech Dataset with Annotator RationalesZahra Delbari, Nafise Sadat Moosavi, Mohammad Taher PilehvarAAAI 2024 · 11 citations
- "Short is the Road that Leads from Fear to Hate": Fear Speech in Indian WhatsApp GroupsPunyajoy Saha, Binny Mathew, Kiran Garimella, Animesh MukherjeeWWW 2021 · 66 citations
