tutorial

Public Access

Taming Social Bots: Detection, Exploration and Measurement

Authors:

Abdullah Mueen,

Nikan Chavoshi,

Amanda MinnichAuthors Info & Claims

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Pages 2967 - 2968

https://doi.org/10.1145/3357384.3360315

Published: 03 November 2019 Publication History

Abstract

Social bots have been around for over a decade since 2008. Social bots are capable of swaying political opinion, spreading false information, and recruiting for terrorist organizations. Social bots use various sophisticated techniques by adopting emotions, sympathy following, synchronous deletions, and profile molting. There are several approaches proposed in the literature for detection, exploration, and measuring social bots. We provide a comprehensive overview of the existing work from data mining and machine learning perspective, discuss relative strengths and weaknesses of various methods, make recommendations for researchers and practitioners, and propose novel directions for future research in taming the social bots. The tutorial also discusses pitfalls in collecting and sharing data on social bots.

References

[1]

[n. d.]. Tutorial Page:. ([n. d.]). https://www.cs.unm.edu/~mueen/Tutorial/TamingBots.html.

[2]

Noor Abu-El-Rub and Abdullah Mueen. 2019. BotCamp: Bot-driven Interactions in Social Campaigns. In The Web Conference.

[3]

Alex Beutel, Wanhong Xu, Venkatesan Guruswami, Christopher Palow, and Christos Faloutsos. 2013. CopyCatch: Stopping group attacks by spotting lockstep behavior in social networks. In Proceedings of the 22nd international conference on World Wide Web - WWW '13. ACM Press, New York, New York, USA, 119--130. https://doi.org/10.1145/2488388.2488400

Digital Library

[4]

Nikan Chavoshi, Hossein Hamooni, and Abdullah Mueen. 2016. DeBot: Twitter Bot Detection via Warped Correlation. In 2016 IEEE 16th International Conference on Data Mining (ICDM). IEEE, 817--822. https://doi.org/10.1109/ICDM.2016.0096

[5]

Nikan Chavoshi and Abdullah Mueen. 2018. Model Bots, not Humans on Social Media. In 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 178--185. https://doi.org/10.1109/ASONAM.2018.8508279

[6]

Alceu Ferraz Costa, Yuto Yamaguchi, Agma Juci Machado Traina, Caetano Traina Jr., and Christos Faloutsos. 2015. RSC: Mining and Modeling Temporal Activity in Social Media. In Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '15). ACM.

Digital Library

[7]

Stefano Cresci, Roberto Di Pietro, Marinella Petrocchi, Angelo Spognardi, and Maurizio Tesconi. 2017. Social fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling. IEEE Transactions on Dependable and Secure Computing (2017), 1--1. https://doi.org/10.1109/TDSC.2017.2681672

[8]

Stefano Cresci, Fabrizio Lillo, Daniele Regoli, Serena Tardelli, and Maurizio Tesconi. 2019. Cashtag Piggybacking: Uncovering Spam and Bot Activity in Stock Microblogs on Twitter. ACM Transactions on the Web 13, 2 (4 2019), 1--27. https://doi.org/10.1145/3313184

Digital Library

[9]

Clayton Allen Davis, Onur Varol, Emilio Ferrara, Alessandro Flammini, and Filippo Menczer. 2016. BotOrNot: A System to Evaluate Social Bots. In Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion. ACM Press, New York, New York, USA, 273--274. https://doi.org/10.1145/2872518.2889302

Digital Library

[10]

Emilio Ferrara, Onur Varol, Clayton Davis, Filippo Menczer, and Alessandro Flammini. 2014. The Rise of Social Bots. CoRR abs/1407.5 (2014). http://arxiv.org/abs/1407.5225

[11]

Michelle C Forelle, Philip N. Howard, Andres Monroy-Hernandez, and Saiph Savage. 2015. Political Bots and the Manipulation of Public Opinion in Venezuela. SSRN Electronic Journal (2015). https://doi.org/10.2139/ssrn.2635800

[12]

Andrew Hall, Loren Terveen, and Aaron Halfaker. 2018. Bot Detection in Wikidata Using Behavioral and Other Informal Cues. Proceedings of the ACM on HumanComputer Interaction 2, CSCW (11 2018), 1--18. https://doi.org/10.1145/3274333

Digital Library

[13]

Hossein Hamooni, Nikan Chavoshi, and Abdullah Mueen. 2016. On URL Changes and Handovers in Social Media. Springer International Publishing, 58--74. https://doi.org/10.1007/978--3--319--47880--7{_}4

[14]

Jytte Klausen, Christopher Marks, and Tauhid Zaman. 2016. Finding Online Extremists in Social Networks. (10 2016). http://arxiv.org/abs/1610.06242

[15]

Thai Le, Kai Shu, Maria D Molina, Dongwon Lee, S. Shyam Sundar, and Huan Liu. 2019. 5 Sources of Clickbaits You Should Know! Using Synthetic Clickbaits to Improve Prediction and Distinguish between Bot-Generated and Human-Written Headlines. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. 33--40. https://doi.org/10.1145/3341161.3342875

[16]

Kyumin Lee, James Caverlee, Zhiyuan Cheng, and Daniel Z. Sui. 2011. Contentdriven detection of campaigns in social media. In Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11. ACM Press, New York, New York, USA, 551. https://doi.org/10.1145/2063576.2063658

[17]

Enrico Mariconti, Jeremiah Onaolapo, Syed Sharique Ahmad, Nicolas Nikiforou, Manuel Egele, Nick Nikiforakis, and Gianluca Stringhini. 2017. What's in a Name?: Understanding Profile Name Reuse on Twitter. In Proceedings of the 26th International Conference on World Wide Web - WWW '17. ACM Press, New York, New York, USA, 1161--1170. https://doi.org/10.1145/3038912.3052589

Digital Library

[18]

A. Minnich, N. Chavoshi, D. Koutra, and A. Mueen. 2017. BotWalk: Efficient adaptive exploration of twitter bot networks. In Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2017. https://doi.org/10.1145/3110025.3110163

[19]

F Morstatter, K M Carley, and H Liu. 2015. Bot Detection in Social Media: Networks, Behavior, and Evaluation. In ASONAM - Tutorial.

[20]

Pujan Paudel, Trung T. Nguyen, Amartya Hatua, and Andrew H. Sung. 2019. How the Tables Have Turned: Studying the New Wave of Social Bots on Twitter Using Complex Network Analysis Techniques. In 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. 501--508. https://doi.org/10.1145/3341161.3342898

[21]

Pablo Suárez-Serrato, Margaret E. Roberts, Clayton Davis, and Filippo Menczer. 2016. On the Influence of Social Bots in Online Protests. Springer, Cham, 269--278. https://doi.org/10.1007/978--3--319--47874--6{_}19

[22]

V. S. Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer, Rand Waltzman, Andrew Stevens, Alexander Dekhtyar, Shuyang Gao, Tad Hogg, Farshad Kooti, Yan Liu, Onur Varol, Prashant Shiralkar, Vinod Vydiswaran, Qiaozhu Mei, and Tim Huang. 2016. The DARPA Twitter Bot Challenge. (1 2016). http://arxiv.org/abs/1601.05140

Digital Library

[23]

Kurt Thomas, Chris Grier, Dawn Song, and Vern Paxson. 2011. Suspended accounts in retrospect: an analysis of twitter spam. In Proceedings of the 2011 ACM . . . (IMC '11). 243--258. https://doi.org/10.1145/2068816.2068840

Digital Library

[24]

Mengfan Yao, Charalampos Chelmis, and Daphney-Stavroula Zois. 2019. Cyberbullying Ends Here: Towards Robust Detection of Cyberbullying in Social Media. In The World Wide Web Conference on - WWW '19. ACM Press, New York, New York, USA, 3427--3433. https://doi.org/10.1145/3308558.3313462

Cited By

Mantello PHo TPodoletz L(2023)Automating Extremism: Mapping the Affective Roles of Artificial Agents in Online RadicalizationThe Palgrave Handbook of Malicious Use of AI and Psychological Security10.1007/978-3-031-22552-9_4(81-103)Online publication date: 10-Jun-2023
https://doi.org/10.1007/978-3-031-22552-9_4
Shao HYao SJing ALiu SLiu DWang TLi JYang CWang RAbdelzaher T(2020)Misinformation Detection and Adversarial Attack Cost Analysis in Directional Social Networks2020 29th International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN49398.2020.9209609(1-11)Online publication date: Aug-2020
https://doi.org/10.1109/ICCCN49398.2020.9209609

Index Terms

Taming Social Bots: Detection, Exploration and Measurement
1. Information systems
  1. Information retrieval
    1. Specialized information retrieval
      1. Environment-specific retrieval
        Web and social media search

Recommendations

Bots in Social and Interaction Networks: Detection and Impact Estimation

The rise of bots and their influence on social networks is a hot topic that has aroused the interest of many researchers. Despite the efforts to detect social bots, it is still difficult to distinguish them from legitimate users. Here, we propose a ...
Red Bots Do It Better:Comparative Analysis of Social Bot Partisan Behavior
WWW '19: Companion Proceedings of The 2019 World Wide Web Conference

Recent research brought awareness of the issue of bots on social media and the significant risks of mass manipulation of public opinion in the context of political discussion. In this work, we leverage Twitter to study the discourse during the 2018 US ...
Discovering social bots on Twitter: a thematic review

The onset of online social networks (OSN) like Twitter became a predominant platform for social expression and public relations. Twitter had 330 million monthly active users by the year 2019. With the gain in popularity, the ratio of virulent and ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

November 2019

3373 pages

ISBN:9781450369763

DOI:10.1145/3357384

General Chairs:
Wenwu Zhu
Tsinghua University, China
,
Dacheng Tao
University of Massachusetts, USA
,
Xueqi Cheng
Institute of Computing Technology, CAS, China
,
Program Chairs:
Peng Cui
Tsinghua University, China
,
Elke Rundensteiner
Worcester Polytechnic Institute, USA
,
David Carmel
Amazon Research, USA
,
Qi He
LinkedIn, USA
,
Jeffrey Xu Yu
Chinese University of Hong Kong, China

Copyright © 2019 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2019

Check for updates

Author Tags

Qualifiers

Tutorial

Funding Sources

NSF

Conference

CIKM '19

Sponsor:

CIKM '19: The 28th ACM International Conference on Information and Knowledge Management

November 3 - 7, 2019

Beijing, China

Acceptance Rates

CIKM '19 Paper Acceptance Rate 202 of 1,031 submissions, 20%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

Upcoming Conference

CIKM '25

Sponsor:
sigir
sigir

The 34th ACM International Conference on Information and Knowledge Management

November 10 - 14, 2025

Seoul , Republic of Korea

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
752
Total Downloads

Downloads (Last 12 months)166
Downloads (Last 6 weeks)11

Reflects downloads up to 18 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Mantello PHo TPodoletz L(2023)Automating Extremism: Mapping the Affective Roles of Artificial Agents in Online RadicalizationThe Palgrave Handbook of Malicious Use of AI and Psychological Security10.1007/978-3-031-22552-9_4(81-103)Online publication date: 10-Jun-2023
https://doi.org/10.1007/978-3-031-22552-9_4
Shao HYao SJing ALiu SLiu DWang TLi JYang CWang RAbdelzaher T(2020)Misinformation Detection and Adversarial Attack Cost Analysis in Directional Social Networks2020 29th International Conference on Computer Communications and Networks (ICCCN)10.1109/ICCCN49398.2020.9209609(1-11)Online publication date: Aug-2020
https://doi.org/10.1109/ICCCN49398.2020.9209609

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents