On the role of political affiliation in human perception the case of Delhi OddEven experiment

Tahar Zanouda, Sofiane Abbar, Laure Berti-Equille, Kushal Shah, Abdelkader Baggag, Sanjay Chawla, Jaideep Srivastava

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In an effort to curb air pollution, the city of Delhi (India), known to be one of the most populated, polluted, and congested cities in the world has run a trial experiment in two phases of 15 days intervals. During the experiment, most of four-wheeled vehicles were constrained to move on alternate days based on whether their plate numbers ended with odd or even digits. While the local government of Delhi represented by A. Kejriwal (leader of AAP party) advocated for the benefits of the experiment, the prime minister of India, N. Modi (former leader of BJP) defended the inefficiency of the initiative. This later has led to a strong polarization of public opinion towards OddEven experiment. This real-world urban experiment provided the scientific community with a unique opportunity to study the impact of political leaning on humans perception at a large-scale. We collect data about pollution and traffic congestion to measure the real effectiveness of the experiment. We use Twitter to capture the public discourse about the experiment in order to study people’s opinion within different dimensions: time, location, and topics. Our results reveal a strong influence of political affiliation on how people perceived the outcomes of the experiment. For instance, AAP supporters were significantly more enthusiastic about the success of OddEven compared to BJP supporters. However, taking into account location of people revealed that personal experience is able to overcome political bias.

Original languageEnglish (US)
Title of host publicationSocial Informatics - 9th International Conference, SocInfo 2017, Proceedings
EditorsGiovanni Luca Ciampaglia, Taha Yasseri, Afra Mashhadi
PublisherSpringer Verlag
Number of pages15
ISBN (Print)9783319672557
StatePublished - 2017
Event9th International Conference on Social Informatics, SocInfo 2017 - Oxford, United Kingdom
Duration: Sep 13 2017Sep 15 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10540 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other9th International Conference on Social Informatics, SocInfo 2017
Country/TerritoryUnited Kingdom

Bibliographical note

Publisher Copyright:
© 2017, Springer International Publishing AG.


  • Computational social science
  • Political science
  • Urban big data analytics
  • Urban policy making


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