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Understanding and Identifying Advocates for Political Campaigns on Social Media

Authors:

Suhas Ranganath,

Huan LiuAuthors Info & Claims

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

Pages 43 - 52

https://doi.org/10.1145/2835776.2835807

Published: 08 February 2016 Publication History

Abstract

Social media is increasingly being used to access and disseminate information on sociopolitical issues like gun rights and general elections. The popularity and openness of social media makes it conducive for some individuals, known as advocates, who use social media to push their agendas on these issues strategically. Identifying these advocates will caution social media users before reading their information and also enable campaign managers to identify advocates for their digital political campaigns. A significant challenge in identifying advocates is that they employ nuanced strategies to shape user opinion and increase the spread of their messages, making it difficult to distinguish them from random users posting on the campaign. In this paper, we draw from social movement theories and design a quantitative framework to study the nuanced message strategies, propagation strategies, and community structure adopted by advocates for political campaigns in social media. Based on observations of their social media activities manifesting from these strategies, we investigate how to model these strategies for identifying them. We evaluate the framework using two datasets from Twitter, and our experiments demonstrate its effectiveness in identifying advocates for political campaigns with ramifications of this work directed towards assisting users as they navigate through social media spaces.

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Cited By

Weichselbraun AKuntschik PFrancolino VSaner MDahinden UWyss V(2021)Adapting Data-Driven Research to the Fields of Social Sciences and the HumanitiesFuture Internet10.3390/fi1303005913:3(59)Online publication date: 26-Feb-2021
https://doi.org/10.3390/fi13030059
Hettiachchi DArora TGoncalves J(2021)Us Vs. Them – Understanding the Impact of Homophily in Political Discussions on TwitterHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85610-6_27(476-497)Online publication date: 26-Aug-2021
https://doi.org/10.1007/978-3-030-85610-6_27
Weichselbraun AHörler SHauser CHavelka AChbeir RManolopoulos YAkerkar RMizera-Pietraszko J(2020)Classifying News Media Coverage for Corruption Risks Management with Deep Learning and Web IntelligenceProceedings of the 10th International Conference on Web Intelligence, Mining and Semantics10.1145/3405962.3405988(54-62)Online publication date: 30-Jun-2020
https://dl.acm.org/doi/10.1145/3405962.3405988
Show More Cited By

Index Terms

Understanding and Identifying Advocates for Political Campaigns on Social Media
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

WSDM '16: Proceedings of the Ninth ACM International Conference on Web Search and Data Mining

February 2016

746 pages

ISBN:9781450337168

DOI:10.1145/2835776

General Chairs:
Paul N. Bennett
Microsoft Research
,
Vanja Josifovski
Pinterest
,
Program Chairs:
Jennifer Neville
Purdue University
,
Filip Radlinski
Microsoft

Copyright © 2016 ACM.

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Published: 08 February 2016

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Office of Naval Research

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WSDM 2016

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WSDM 2016: Ninth ACM International Conference on Web Search and Data Mining

February 22 - 25, 2016

California, San Francisco, USA

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WSDM '16 Paper Acceptance Rate 67 of 368 submissions, 18%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

Weichselbraun AKuntschik PFrancolino VSaner MDahinden UWyss V(2021)Adapting Data-Driven Research to the Fields of Social Sciences and the HumanitiesFuture Internet10.3390/fi1303005913:3(59)Online publication date: 26-Feb-2021
https://doi.org/10.3390/fi13030059
Hettiachchi DArora TGoncalves J(2021)Us Vs. Them – Understanding the Impact of Homophily in Political Discussions on TwitterHuman-Computer Interaction – INTERACT 202110.1007/978-3-030-85610-6_27(476-497)Online publication date: 26-Aug-2021
https://doi.org/10.1007/978-3-030-85610-6_27
Weichselbraun AHörler SHauser CHavelka AChbeir RManolopoulos YAkerkar RMizera-Pietraszko J(2020)Classifying News Media Coverage for Corruption Risks Management with Deep Learning and Web IntelligenceProceedings of the 10th International Conference on Web Intelligence, Mining and Semantics10.1145/3405962.3405988(54-62)Online publication date: 30-Jun-2020
https://dl.acm.org/doi/10.1145/3405962.3405988
Haq EBraud TKwon YHui P(2020)A Survey on Computational PoliticsIEEE Access10.1109/ACCESS.2020.30349838(197379-197406)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3034983
Zheng CZhang QLong GZhang CYoung SWang W(2020)Measuring Time-Sensitive and Topic-Specific Influence in Social Networks With LSTM and Self-AttentionIEEE Access10.1109/ACCESS.2020.29916838(82481-82492)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2991683
Zannettou SSirivianos MBlackburn JKourtellis N(2019)The Web of False InformationJournal of Data and Information Quality10.1145/330969911:3(1-37)Online publication date: 7-May-2019
https://dl.acm.org/doi/10.1145/3309699
Long CZhang XWang YLu XHan FZhang JLi X(2019)SNSaPP: Unbiased Social Media Analysis Against Paid Posters2019 International Conference on Data Mining Workshops (ICDMW)10.1109/ICDMW.2019.00163(1102-1105)Online publication date: Nov-2019
https://doi.org/10.1109/ICDMW.2019.00163
Caetano JLima HSantos MMarques-Neto H(2018)Using sentiment analysis to define twitter political users’ classes and their homophily during the 2016 American presidential electionJournal of Internet Services and Applications10.1186/s13174-018-0089-09:1Online publication date: 3-Sep-2018
https://doi.org/10.1186/s13174-018-0089-0
Ranganath SHu XTang JWang SLiu H(2018)Understanding and Identifying Rhetorical Questions in Social MediaACM Transactions on Intelligent Systems and Technology10.1145/31083649:2(1-22)Online publication date: 10-Jan-2018
https://dl.acm.org/doi/10.1145/3108364
Caetano JAlmeida JMarques-Neto H(2018)Characterizing Politically Engaged Users' Behavior During the 2016 US Presidential Campaign2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)10.1109/ASONAM.2018.8508459(523-530)Online publication date: Aug-2018
https://doi.org/10.1109/ASONAM.2018.8508459
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