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This repository contains codes (Jupyter Notebooks) to reproduce the figures and results of our submission accepted in COMPASS 2022.

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Samachar: News Media on Air Pollution in India

This repository contains codes (Jupyter Notebooks) to reproduce the figures and results of our submission (https://dl.acm.org/doi/pdf/10.1145/3530190.3534812) accepted in COMPASS 2022. Each folder represents a section in the paper.

  • Section Overview
Section Title Decription
3 Dataset We are making the News-articles-dataset public. (Note: PM25 data is publicly available in CPCB portal and OpenAQ website.)
5.1 Research-Question-1 Does the news media coverage around air pollution exhibit a geographical and/or temporal bias?
5.2 Research-Question-2 Does the news media coverage around air pollution exhibit deviation from scientific evidence around sources and impact of air pollution?



  • Tables/Figures
Figure/Table File/Folder Decription
Figure 1 dataset/Figure-1_Number-of-cities-for-pm25-data-available.ipynb To plot number of cities along with time for which PM25 data is available.
Figure 2 dataset/Figure-2_TOI-vs-Hindu-articles_over_time.ipynb To plot articles of TOI and The Hindu over time (2010-21).
Figure 3 Research_Question_1/Figure-3_Choropleth_map_PM25_and_articles.ipynb Python Notebook to generate Choropleth map of India showing PM2.5 level and number of news articles
Figure 4 Research_Question_1/Figure-4_Violation_of_India_limit_by_IGP.ipynb Time series of PM2.5 level and Number of articles for Delhi
Figure 5 Research_Question_1/Figure-5_timeseries_of_aq_articles_delhi.ipynb Time series of PM2.5 level and Number of articles for Delhi
Table 3 Research_Question_1/Table-3,4_pollution-in-IG-Plain_and_Delhi-time-series.ipynb PM2.5 and articles of Cities of Indo Gangetic (IG) plain
Table 4 Research_Question_1/Table-3,4_pollution-in-IG-Plain_and_Delhi-time-series.ipynb PM2.5 and articles of 10 most highlighted cities in News-media
Figure 6 Research_Question_2/Figure-6_Topic-Modeling-tarining-LDA-model.ipynb Train LDA Topic modeling model using gensim and create visualization LDA_topic_modelling_Visualization.html using pyLDAvis.
Figure 7 Research_Question_2/Figure-7_Topic-evolution-over-time.ipynb Frequency of articles of topic over time
Figure 8 Research_Question_2/Figure-8_Open-fire-vs-Stubble-burning-articles.ipynb Timeseries of NASA Open Fire cout data (VIIRS) firedata to identify when stubble burning is happening and compare firecount
Figure 9 Research_Question_2/Figure-9_Source-contribution-Delhi.ipynb Comparison of Sources contribution to PM2.5 in Delhi and articles relavent to particular sources, to verify if media discussion is in consonance with source contribution.
  • Citation
@inproceedings{patel2022samachar,
  title={Samachar: print news media on air pollution in India},
  author={Patel, Karm and Adhikary, Rishiraj and Patel, Zeel B and Batra, Nipun and Guttikunda, Sarath},
  booktitle={ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies (COMPASS)},
  pages={401--413},
  year={2022}
}

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This repository contains codes (Jupyter Notebooks) to reproduce the figures and results of our submission accepted in COMPASS 2022.

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