research-article

A Tale of Two Sides: Study of Protesters and Counter-protesters on #CitizenshipAmendmentAct Campaign on Twitter

Authors:

Vishwesh Kumar,

Abhishek Chopra,

Arun Balaji Buduru,

Ponnurangam KumaraguruAuthors Info & Claims

WebSci '22: Proceedings of the 14th ACM Web Science Conference 2022

Pages 279 - 289

https://doi.org/10.1145/3501247.3531584

Published: 26 June 2022 Publication History

Abstract

Online social media platforms have evolved into a significant place for debate around socio-political phenomena such as government policies and bills. Studying online debates on such topics can help infer people’s perception and acceptance of the happenings. At the same time, various inauthentic users that often pollute the democratic discussion of the subject need to be weeded out from the debate. The characterization of a campaign keeping in mind various forms of involved actors thus becomes very important. On December 12, 2019, Citizenship Amendment Act (CAA) was enacted by the Indian Government, triggering a debate on whether the act was unfair. In this work, we investigate the user’s perception of the #CitizenshipAmendmentAct on Twitter, as the campaign unrolled with divergent discourse in the country. Keeping the campaign participants as the prime focus, we study 9,947,814 tweets produced by 275,111 users during the starting 3 months of protest. Our study includes the analysis of user engagement, content, and network properties with online accounts divided into authentic (genuine users) and inauthentic (bots, suspended, and deleted) users. Our findings show different themes in shared tweets among protesters and counter-protesters. We find presence of inauthentic users on both side of discourse, with counter-protesters having more inauthentic users than protesters. The follow network of the users suggests homophily among users on the same side of discourse and connection between various inauthentic and authentic users. This work contributes to filling the gap of understanding the role of users (from both sides) in a less studied geo-location, India.

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References

[1]

2019. CAB protest: Students clash with police near Assam secretariat. Economic Times (2019).

[2]

2019. Anti-CAA Protests Highlights December 24: Rahul and Priyanka Gandhi stopped outside Meerut by police, returns Delhi. jagran News Desk (2019).

[3]

2019. Indian-Americans protest CAA third time in nine days, author=IANS. freepressjournal (2019).

[4]

2019. Breaking news on December 20, author=India TV News Desk. newindianexpress (2019).

[5]

2019. Flash protest in Hyderabad again CAA, NRC on New Year’s eve: Six detained. The News Minute. (2019).

[6]

2019. Internet shutdowns. (May 2019). https://internetshutdowns.in/static-page/caa-protest/

[7]

Edwin Amenta and Michael P. Young. 1999. Democratic States and Social Movements: Theoretical Arguments and Hypotheses. Social Problems 46, 2 (1999), 153–168. http://www.jstor.org/stable/3097250

[8]

ANI. 2019. Amid protests, Mamata Banerjee announces mega rally in Kolkata to protest against CAA, NRC today. freepressjournal (2019).

[9]

ANI. 2019. CAA protest row: Section 144 imposed in UP Mau’s Hajipura Chowk area. freepressjournal (2019).

[10]

Ahmer Arif, Leo Graiden Stewart, and Kate Starbird. 2018. Acting the part: Examining information operations within# BlackLivesMatter discourse. Proceedings of the ACM on Human-Computer Interaction 2, CSCW(2018), 1–27.

Digital Library

[11]

Rawia Awadallah, Maya Ramanath, and Gerhard Weikum. 2012. Harmony and dissonance: organizing the people’s voices on political controversies. In Proceedings of the fifth ACM international conference on Web search and data mining. 523–532.

Digital Library

[12]

Mohsen Bahrami, Yasin Findik, Burçin Bozkaya, and Selim Balcisoy. 2018. Twitter Reveals: Using Twitter Analytics to Predict Public Protests. CoRR abs/1805.00358(2018). arxiv:1805.00358http://arxiv.org/abs/1805.00358

[13]

Alessandro Bessi and Emilio Ferrara. 2016. Social bots distort the 2016 US Presidential election online discussion. First monday 21, 11-7 (2016).

[14]

David M Blei, Andrew Y Ng, and Michael I Jordan. 2002. Latent dirichlet allocation. In Advances in neural information processing systems. 601–608.

[15]

Danah Boyd and Kate Crawford. 2012. Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information, communication & society 15, 5 (2012), 662–679.

[16]

Abhinav Chandrachud. 2020. Secularism and the Citizenship Amendment Act. Indian Law Review 4, 2 (2020), 138–162. https://doi.org/10.1080/24730580.2020.1757927 arXiv:https://doi.org/10.1080/24730580.2020.1757927

[17]

Ho-Chun Herbert Chang, Emily Chen, Meiqing Zhang, Goran Muric, and Emilio Ferrara. 2021. Social Bots and Social Media Manipulation in 2020: The Year in Review. arXiv preprint arXiv:2102.08436(2021).

[18]

Danish Contractor, Bhupesh Chawda, Sameep Mehta, L. Subramaniam, and Tanveer A. Faruquie. 2015. Tracking Political Elections on Social Media: Applications and Experience. In IJCAI.

[19]

Vijaita Singh Damini Nath. 2019. After a heated debate, Rajya Sabha clears Citizenship (Amendment) Bill. The Hindu (2019).

[20]

Kareem Darwish, Peter Stefanov, Michaël Aupetit, and Preslav Nakov. 2020. Unsupervised User Stance Detection on Twitter. Proceedings of the International AAAI Conference on Web and Social Media 14, 1 (May 2020), 141–152. https://ojs.aaai.org/index.php/ICWSM/article/view/7286

[21]

Munmun De Choudhury, Shagun Jhaver, Benjamin Sugar, and Ingmar Weber. 2016. Social media participation in an activist movement for racial equality. In Proceedings of the... International AAAI Conference on Weblogs and Social Media. International AAAI Conference on Weblogs and Social Media, Vol. 2016. NIH Public Access, 92.

[22]

Adam G Dunn, Didi Surian, Jason Dalmazzo, Dana Rezazadegan, Maryke Steffens, Amalie Dyda, Julie Leask, Enrico Coiera, Aditi Dey, and Kenneth D Mandl. 2020. Limited role of bots in spreading vaccine-critical information among active twitter users in the United States: 2017–2019. American Journal of Public Health 110, S3 (2020), S319–S325.

[23]

Mai ElSherief, Elizabeth Belding, and Dana Nguyen. 2017. #notokay: Understanding gender-based violence in social media. In Eleventh International AAAI Conference on Web and Social Media.

[24]

Yi Fang, Luo Si, Naveen Somasundaram, and Zhengtao Yu. 2012. Mining contrastive opinions on political texts using cross-perspective topic model. In Proceedings of the fifth ACM international conference on Web search and data mining. 63–72.

Digital Library

[25]

Emilio Ferrara, Onur Varol, Clayton Davis, Filippo Menczer, and Alessandro Flammini. 2016. The rise of social bots. Commun. ACM 59, 7 (2016), 96–104.

Digital Library

[26]

Anjalie Field, Gayatri Bhat, and Yulia Tsvetkov. 2019. Contextual Affective Analysis: A Case Study of People Portrayals in Online #MeToo Stories. Proceedings of the International AAAI Conference on Web and Social Media 13 (Jul. 2019), 158–169. https://www.aaai.org/ojs/index.php/ICWSM/article/view/3358

[27]

Ryan J. Gallagher, Morgan R. Frank, Lewis Mitchell, Aaron J. Schwartz, Andrew J. Reagan, Christopher M. Danforth, and Peter Sheridan Dodds. 2020. Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts. CoRR abs/2008.02250(2020). arxiv:2008.02250https://arxiv.org/abs/2008.02250

[28]

Ryan J. Gallagher, Andrew J. Reagan, Christopher M. Danforth, and Peter Sheridan Dodds. 2018. Divergent discourse between protests and counter-protests: #BlackLivesMatter and #AllLivesMatter. PLOS ONE 13, 4 (04 2018), 1–23. https://doi.org/10.1371/journal.pone.0195644

[29]

Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis. 2018. Quantifying Controversy on Social Media. Trans. Soc. Comput. 1, 1, Article 3 (Jan. 2018), 27 pages. https://doi.org/10.1145/3140565

Digital Library

[30]

Genevieve Gorrell, Mehmet Emin Bakir, Ian Roberts, Mark Anthony Greenwood, Benedetta Iavarone, and Kalina Bontcheva. 2019. Partisanship, Propaganda and Post-Truth Politics: Quantifying Impact in Online Debate. The Journal of Web Science 7 (2019).

[31]

Saket Gurukar, Deepak Ajwani, Sourav Dutta, J. Lauri, S. Parthasarathy, and A. Sala. 2020. Towards Quantifying the Distance between Opinions. In ICWSM.

[32]

K Sree Hari, Disha Aravind, Ashish Singh, and Bhaskarjyoti Das. 2021. Detecting Propaganda in Trending Twitter Topics in India—A Metric Driven Approach. In Emerging Technologies in Data Mining and Information Security. Springer, 657–671.

[33]

IANS. 2019. Bhopal: Hundreds join BJP’s pro CAA-NRC rally. freepressjournal (2019).

[34]

IANS. 2019. Anti-CAA protests continue to hit rail, road traffic in West Bengal. freepressjournal (2019).

[35]

IANS. 2019. Delhi’s Shaheen Bagh rings in new year with anti-Citizenship Act slogans. The Hindu (2019).

[36]

Maurice Jakesch, Kiran Garimella, Dean Eckles, and Mor Naaman. 2021. Trend Alert: A Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election. Proc. ACM Hum.-Comput. Interact. 5, CSCW2, Article 379 (oct 2021), 19 pages. https://doi.org/10.1145/3479523

Digital Library

[37]

Apalak Khatua and Aparup Khatua. 2016. Leave or Remain? Deciphering Brexit Deliberations on Twitter. In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW). 428–433. https://doi.org/10.1109/ICDMW.2016.0067

[38]

Fannie Liu, Denae Ford, Chris Parnin, and Laura Dabbish. 2017. Selfies as Social Movements: Influences on Participation and Perceived Impact on Stereotypes. Proc. ACM Hum.-Comput. Interact. 1, CSCW, Article 72, 21 pages. https://doi.org/10.1145/3134707

Digital Library

[39]

Luca Luceri, Silvia Giordano, and Emilio Ferrara. 2020. Detecting Troll Behavior via Inverse Reinforcement Learning: A Case Study of Russian Trolls in the 2016 US Election. Proceedings of the International AAAI Conference on Web and Social Media 14, 1 (May 2020), 417–427. https://ojs.aaai.org/index.php/ICWSM/article/view/7311

[40]

Sangeeta Mahapatra and Kiran Garimella. 2021. Digital Public Activism and the Redefinition of Citizenship: The movement against the citizenship (amendment) act of India. In Weizenbaum Conference 2021: Democracy in Flux–Order, Dynamics and Voices in Digital Public Spheres. DEU, 3.

[41]

Leland McInnes and John Healy. 2017. Accelerated hierarchical density based clustering. In 2017 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 33–42.

[42]

Leland McInnes, John Healy, and James Melville. 2018. Umap: Uniform manifold approximation and projection for dimension reduction. arXiv preprint arXiv:1802.03426(2018).

[43]

Marcelo Mendoza, Maurizio Tesconi, and Stefano Cresci. 2020. Bots in social and interaction networks: detection and impact estimation. ACM Transactions on Information Systems (TOIS) 39, 1 (2020), 1–32.

Digital Library

[44]

Tanushree Mitra, Scott Counts, and James W Pennebaker. 2016. Understanding anti-vaccination attitudes in social media. In Tenth International AAAI Conference on Web and Social Media.

[45]

Saif Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, and Colin Cherry. 2016. Semeval-2016 task 6: Detecting stance in tweets. In Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016). 31–41.

[46]

Saif Mohammad and Peter Turney. 2010. Emotions Evoked by Common Words and Phrases: Using Mechanical Turk to Create an Emotion Lexicon. In Proceedings of the NAACL HLT 2010 Workshop on Computational Approaches to Analysis and Generation of Emotion in Text. Association for Computational Linguistics, Los Angeles, CA, 26–34. https://aclanthology.org/W10-0204

[47]

Sathappan Muthiah, Patrick Butler, Rupinder Paul Khandpur, Parang Saraf, Nathan Self, Alla Rozovskaya, Liang Zhao, Jose Cadena, Chang-Tien Lu, Anil Vullikanti, 2016. Embers at 4 years: Experiences operating an open source indicators forecasting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 205–214.

Digital Library

[48]

Leonardo Nizzoli, Serena Tardelli, Marco Avvenuti, Stefano Cresci, and Maurizio Tesconi. 2021. Coordinated Behavior on Social Media in 2019 UK General Election. In ICWSM.

[49]

Diogo Pacheco, Alessandro Flammini, and Filippo Menczer. 2020. Unveiling coordinated groups behind white helmets disinformation. In Companion Proceedings of the Web Conference 2020. 611–616.

Digital Library

[50]

Diogo Pacheco, Pik-Mai Hui, Christopher Torres-Lugo, Bao Tran Truong, Alessandro Flammini, and Filippo Menczer. 2021. Uncovering Coordinated Networks on Social Media: Methods and Case Studies. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 15. 455–466.

[51]

Anmol Panda, Ramaravind Kommiya Mothilal, Monojit Choudhury, Kalika Bali, and Joyojeet Pal. 2020. Topical Focus of Political Campaigns and its Impact: Findings from Politicians’ Hashtag Use during the 2019 Indian Elections. Proceedings of the ACM on Human-Computer Interaction 4, CSCW1(2020), 1–14.

Digital Library

[52]

Mainul Quraishi, Pavlos Fafalios, and Eelco Herder. 2018. Viewpoint discovery and understanding in social networks. In Proceedings of the 10th ACM Conference on Web Science. 47–56.

Digital Library

[53]

Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang, and Huan Liu. 2016. Predicting Online Protest Participation of Social Media Users. In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (Phoenix, Arizona) (AAAI’16). AAAI Press, 208–214.

Digital Library

[54]

Ammar Rashed, Mucahid Kutlu, Kareem Darwish, Tamer Elsayed, and Cansın Bayrak. 2021. Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey. Proceedings of the International AAAI Conference on Web and Social Media 15, 1 (May 2021), 537–548. https://ojs.aaai.org/index.php/ICWSM/article/view/18082

[55]

Ammar Rashed, Mucahid Kutlu, Kareem Darwish, Tamer Elsayed, and Cansın Bayrak. 2021. Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 15. 537–548.

[56]

Vincent Raynauld, Emmanuelle Richez, and Katie Boudreau Morris. 2018. Canada is #IdleNoMore: exploring dynamics of Indigenous political and civic protest in the Twitterverse. Information, Communication & Society 21, 4 (2018), 626–642. https://doi.org/10.1080/1369118X.2017.1301522 arXiv:https://doi.org/10.1080/1369118X.2017.1301522

[57]

B. Riedel, Isabelle Augenstein, Georgios P. Spithourakis, and S. Riedel. 2017. A simple but tough-to-beat baseline for the Fake News Challenge stance detection task. ArXiv abs/1707.03264(2017).

[58]

Anna Rogers, Olga Kovaleva, and Anna Rumshisky. 2019. Calls to Action on Social Media: Potential for Censorship and Social Impact. EMNLP-IJCNLP 2019 (2019), 36.

[59]

Express News Service. 2019. Government open to suggestions to implement Citizenship Act, says MHA amid raging protests. newindianexpress (2019).

[60]

Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessandro Flammini, and Filippo Menczer. 2018. The spread of low-credibility content by social bots. Nature communications 9, 1 (2018), 1–9.

[61]

Karishma Sharma, Yizhou Zhang, Emilio Ferrara, and Yan Liu. 2021. Identifying coordinated accounts on social media through hidden influence and group behaviours. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 1441–1451.

Digital Library

[62]

Ivan Slobozhan, Tymofii Brik, and Rajesh Sharma. 2021. Longitudinal change in language behaviour during protests: A case study of Euromaidan in Ukraine. arXiv preprint arXiv:2109.11623(2021).

[63]

Jitendra Soni. 2019. CAA protest row: Section 144 imposed in UP Mau’s Hajipura Chowk area. freepressjournal (2019).

[64]

Kate Starbird and Leysia Palen. 2012. (How) Will the Revolution Be Retweeted? Information Diffusion and the 2011 Egyptian Uprising. In Proceedings of the ACM 2012 Conference on Computer Supported Cooperative Work (Seattle, Washington, USA) (CSCW ’12). Association for Computing Machinery, New York, NY, USA, 7–16. https://doi.org/10.1145/2145204.2145212

Digital Library

[65]

Abraham Ronel Martínez Teutle. 2010. Twitter: Network properties analysis. In 2010 20th International Conference on Electronics Communications and Computers (CONIELECOMP). IEEE, 180–186.

[66]

Zeynep Tufekci. 2014. Big questions for social media big data: Representativeness, validity and other methodological pitfalls. In Eighth international AAAI conference on weblogs and social media.

[67]

Joshua Uyheng and Kathleen M Carley. 2021. Computational Analysis of Bot Activity in the Asia-Pacific: A Comparative Study of Four National Elections. In Proceedings of the International AAAI Conference on Web and Social Media, Vol. 15. 727–738.

[68]

Michel Verleysen 2003. Learning high-dimensional data. Nato Science Series Sub Series III Computer And Systems Sciences 186 (2003), 141–162.

[69]

Rong Wang and Alvin Zhou. 2021. Hashtag activism and connective action: A case study of# HongKongPoliceBrutality. Telematics and Informatics 61 (2021), 101600.

[70]

Human Right Watch. 2019. India: Citizenship Bill Discriminates Against Muslims. Human Right Watch (Dec. 2019).

[71]

FPJ Web. 2019. CAA protests: Why are students protesting? Here’s all you need to know. (2019).

[72]

Kai Wei, Yu-Ru Lin, and Muheng Yan. 2020. Examining Protest as An Intervention to Reduce Online Prejudice: A Case Study of Prejudice Against Immigrants. In Proceedings of The Web Conference 2020 (Taipei, Taiwan) (WWW ’20). Association for Computing Machinery, New York, NY, USA, 2443–2454. https://doi.org/10.1145/3366423.3380307

Digital Library

[73]

Kai-Cheng Yang, Onur Varol, Pik-Mai Hui, and Filippo Menczer. 2020. Scalable and Generalizable Social Bot Detection through Data Selection. Proceedings of the AAAI Conference on Artificial Intelligence 34, 01 (Apr. 2020), 1096–1103. https://doi.org/10.1609/aaai.v34i01.5460

Cited By

Das BRagothaman KKesari RT.S.B. S(2024)The tale of two sides in the 2019 anti-CAA protest—An analytical frameworkInternational Journal of Information Management Data Insights10.1016/j.jjimei.2024.1003004:2(100300)Online publication date: Nov-2024
https://doi.org/10.1016/j.jjimei.2024.100300
Neha KAgrawal VBuduru AKumaraguru PAlhajj RAgarwal NMa ZRokne JAn JCharalampos CMagdy W(2022)The Pursuit of Being Heard: An Unsupervised Approach to Narrative Detection in Online ProtestProceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM55673.2022.10068671(256-260)Online publication date: 10-Nov-2022
https://dl.acm.org/doi/10.1109/ASONAM55673.2022.10068671
Jaidka K(undefined)Organized Mobilization on Social Media: A Multi-Institutional Perspective on Protest Rhetoric, Reach, and ReinforcementSSRN Electronic Journal10.2139/ssrn.3901631
https://doi.org/10.2139/ssrn.3901631

Index Terms

A Tale of Two Sides: Study of Protesters and Counter-protesters on #CitizenshipAmendmentAct Campaign on Twitter
1. Applied computing

Index terms have been assigned to the content through auto-classification.

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cover image ACM Conferences

WebSci '22: Proceedings of the 14th ACM Web Science Conference 2022

June 2022

479 pages

ISBN:9781450391917

DOI:10.1145/3501247

General Chairs:
Ricardo Baeza-Yates
Northeastern University, MA, USA & Universitat Pompeu Fabra, Spain
,
Katrin Weller
GESIS & Center for Advanced Internet Studies, Germany
,
Organizing Chair:
Manuel Portela
Universitat Pompeu Fabra, Spain
,
Program Chairs:
Oshani Seneviratne
Rensselaer Polytechnic Institute, NY, USA
,
Ingmar Weber
Qatar Computing Research Institute, Qatar
,
Taha Yasseri
University College Dublin, Ireland
,
Publications Chairs:
Anna Bon
Vrije Universiteit Amsterdam, Netherlands
,
Srinath Srinivas
International Institute of Information Technology, Bangalore, India
,
Luis-Daniel Ibáñez
University of Southampton, UK

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Published: 26 June 2022

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Cited By

Das BRagothaman KKesari RT.S.B. S(2024)The tale of two sides in the 2019 anti-CAA protest—An analytical frameworkInternational Journal of Information Management Data Insights10.1016/j.jjimei.2024.1003004:2(100300)Online publication date: Nov-2024
https://doi.org/10.1016/j.jjimei.2024.100300
Neha KAgrawal VBuduru AKumaraguru PAlhajj RAgarwal NMa ZRokne JAn JCharalampos CMagdy W(2022)The Pursuit of Being Heard: An Unsupervised Approach to Narrative Detection in Online ProtestProceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.1109/ASONAM55673.2022.10068671(256-260)Online publication date: 10-Nov-2022
https://dl.acm.org/doi/10.1109/ASONAM55673.2022.10068671
Jaidka K(undefined)Organized Mobilization on Social Media: A Multi-Institutional Perspective on Protest Rhetoric, Reach, and ReinforcementSSRN Electronic Journal10.2139/ssrn.3901631
https://doi.org/10.2139/ssrn.3901631

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