AirCalypse: Can Twitter Help in Urban Air Quality Measurement and Who are the Influential Users?
- URL: http://arxiv.org/abs/2502.19421v1
- Date: Sat, 25 Jan 2025 11:13:15 GMT
- Title: AirCalypse: Can Twitter Help in Urban Air Quality Measurement and Who are the Influential Users?
- Authors: Prithviraj Pramanik, Tamal Mondal, Subrata Nandi, Mousumi Saha,
- Abstract summary: This work is an empirical study on using Twitter as a "Sensor" to measure air quality.<n>The focal point of this work is to identify the users who have been actively tweeting in the air pollution events in Delhi.<n>We further study the behavior, i.e., perception of pollution from those users' posts with respect to the actual air pollution levels using the physical sensors.
- Score: 0.6441880253307178
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: In this digital age, Online Social Media's ubiquity has led it to it's role as a "Sensor". Starting from disaster response to political predictions, online social media like Twitter, have been instrumental and are actively researched areas. In this work, we have focused on something quite insidious in the current context, i.e., air pollution in developing regions. Starting as an empirical study on using Twitter as a "Sensor" to measure air quality, the focal point of this work is to identify the users who have been actively tweeting in the air pollution events in Delhi, the capital of India. From these users, we try to identify the influential ones, who play a significant role in creating the initial awareness and hence act as "Sensors". We have utilized a tailored "TRank" algorithm for finding out the influential users by considering \textit{Retweet, Favorite, and Follower influence} of the users. After ranking the users based on their social influence, we further study the behavior, i.e., perception of pollution from those users' posts with respect to the actual air pollution levels using the physical sensors. The tracking of influential users in air quality monitoring assists in developing a crowd sensed air quality measurement framework, which can augment the physical air quality sensors for raising awareness against air pollution.
Related papers
- AirCast: Improving Air Pollution Forecasting Through Multi-Variable Data Alignment [46.56288727659417]
Air pollution remains a leading global health risk, exacerbated by rapid industrialization and urbanization.
We introduce AirCast, a novel multi-variable air pollution forecasting model.
AirCast employs a multi-task head architecture that simultaneously forecasts atmospheric conditions and pollutant concentrations.
arXiv Detail & Related papers (2025-02-25T07:34:18Z) - Use of Air Quality Sensor Network Data for Real-time Pollution-Aware POI Suggestion [10.782779065468558]
AirSense-R is a mobile application that provides real-time, pollution-aware recommendations for points of interest (POIs) in urban environments.<n>The proposed system aims to help users make health-conscious decisions about the locations they visit.
arXiv Detail & Related papers (2025-02-13T10:36:17Z) - VayuBuddy: an LLM-Powered Chatbot to Democratize Air Quality Insights [2.2754055137802074]
VayuBuddy is a Large Language Model (LLM)-powered chatbots for air quality sensor data analysis.
VyuBuddy receives the questions in natural language, analyses the structured sensory data with a LLM-generated Python code and provides answers in natural language.
VyuBuddy can also generate visual analysis such as line-plots, map plot, bar charts and many others from the sensory data.
arXiv Detail & Related papers (2024-11-16T08:02:35Z) - Sensor Deprivation Attacks for Stealthy UAV Manipulation [51.9034385791934]
Unmanned Aerial Vehicles autonomously perform tasks with the use of state-of-the-art control algorithms.
In this work, we propose a multi-part.
Sensor Deprivation Attacks (SDAs), aiming to stealthily impact.
process control via sensor reconfiguration.
arXiv Detail & Related papers (2024-10-14T23:03:58Z) - Wireless Crowd Detection for Smart Overtourism Mitigation [50.031356998422815]
This chapter describes a low-cost approach to monitoring overtourism based on mobile devices' wireless activity.
The crowding sensors count the number of surrounding mobile devices, by detecting trace elements of wireless technologies.
They run detection programs for several technologies, and fingerprinting analysis results are only stored locally in an anonymized database.
arXiv Detail & Related papers (2024-02-14T13:20:24Z) - Gaussian Processes for Monitoring Air-Quality in Kampala [3.173497841606415]
We investigate the use of Gaussian Processes for nowcasting the current air-pollution in places where there are no sensors and forecasting the air-pollution in the future at the sensor locations.
We focus on the city of Kampala in Uganda, using data from AirQo's network of sensors.
arXiv Detail & Related papers (2023-11-28T09:25:23Z) - Climate Change & Computer Audition: A Call to Action and Overview on
Audio Intelligence to Help Save the Planet [98.97255654573662]
This work provides an overview of areas in which audio intelligence can contribute to overcome climate-related challenges.
We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether.
arXiv Detail & Related papers (2022-03-10T13:32:31Z) - SOK: Seeing and Believing: Evaluating the Trustworthiness of Twitter
Users [4.609388510200741]
Currently, there is no automated way of determining which news or users are credible and which are not.
In this work, we created a model which analysed the behaviour of50,000 politicians on Twitter.
We classified the political Twitter users as either trusted or untrusted using random forest, multilayer perceptron, and support vector machine.
arXiv Detail & Related papers (2021-07-16T17:39:32Z) - News consumption and social media regulations policy [70.31753171707005]
We analyze two social media that enforced opposite moderation methods, Twitter and Gab, to assess the interplay between news consumption and content regulation.
Our results show that the presence of moderation pursued by Twitter produces a significant reduction of questionable content.
The lack of clear regulation on Gab results in the tendency of the user to engage with both types of content, showing a slight preference for the questionable ones which may account for a dissing/endorsement behavior.
arXiv Detail & Related papers (2021-06-07T19:26:32Z) - On spatial variation in the detectability and density of social media
user protest supporters [52.77024349608834]
The research reported here uses spatial capture-recapture methods to determine the influence of the built environment, physical proximity to protest location, and collective posting rhythm on variations in users' spatial detectability and density during a protest in Mexico City.
arXiv Detail & Related papers (2021-03-10T14:08:08Z) - AiR -- An Augmented Reality Application for Visualizing Air Pollution [5.564705758320338]
AiR considers the air quality measured by CPCB, in a locality detected by the user's GPS or in a locality of user's choice, and visualizes various air pollutants present in the locality.
AiR also creates awareness in an interactive manner about the different pollutants, sources, and their impacts on health.
arXiv Detail & Related papers (2020-06-03T10:03:47Z) - Quantifying the Vulnerabilities of the Online Public Square to Adversarial Manipulation Tactics [43.98568073610101]
We use a social media model to quantify the impacts of several adversarial manipulation tactics on the quality of content.
We find that the presence of influential accounts, a hallmark of social media, exacerbates the vulnerabilities of online communities to manipulation.
These insights suggest countermeasures that platforms could employ to increase the resilience of social media users to manipulation.
arXiv Detail & Related papers (2019-07-13T21:12:08Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.