research-article

Purple Feed: Identifying High Consensus News Posts on Social Media

Authors:

Mahmoudreza Babaei,

Juhi Kulshrestha,

Abhijnan Chakraborty,

Fabrício Benevenuto,

Krishna P. Gummadi,

Adrian WellerAuthors Info & Claims

AIES '18: Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

Pages 10 - 16

https://doi.org/10.1145/3278721.3278761

Published: 27 December 2018 Publication History

Abstract

Although diverse news stories are actively posted on social media, readers often focus on the news which reinforces their pre-existing views, leading to 'filter bubble' effects. To combat this, some recent systems expose and nudge readers toward stories with different points of view. One example is the Wall Street Journal's 'Blue Feed, Red Feed' system, which presents posts from biased publishers on each side of a topic. However, these systems have had limited success. We present a complementary approach which identifies high consensus 'purple' posts that generate similar reactions from both 'blue' and 'red' readers. We define and operationalize consensus for news posts on Twitter in the context of US politics. We show that high consensus posts can be identified and discuss their empirical properties. We present a method for automatically identifying high and low consensus news posts on Twitter, which can work at scale across many publishers. To do this, we propose a novel category of audience leaning based features, which we show are well suited to this task. Finally, we present our 'Purple Feed' system which highlights high consensus posts from publishers on both sides of the political spectrum.

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Cited By

Rezk ASimkute AVines JElsden CEvans MJones RLuger E(2024)User-Centric Tensions: Exploring Perceived Benefits and (Dis)comfort in Media PersonalisationProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685365(1-13)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685365
Rezk ASimkute ALuger EVines JElsden CEvans MJones R(2024)Agency Aspirations: Understanding Users' Preferences And Perceptions Of Their Role In Personalised News CurationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642634(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642634
Rezk A(2023)“Way too good and way beyond comfort”Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3600211.3604761(996-998)Online publication date: 8-Aug-2023
https://dl.acm.org/doi/10.1145/3600211.3604761
Show More Cited By

Index Terms

Purple Feed: Identifying High Consensus News Posts on Social Media
1. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning
        Supervised learning by classification
2. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social media
  2. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies

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cover image ACM Conferences

AIES '18: Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society

December 2018

406 pages

ISBN:9781450360128

DOI:10.1145/3278721

Program Chairs:
Jason Furman
Harvard University, USA
,
Gary Marchant
Arizona State University, USA
,
Huw Price
Cambridge University, UK
,
Francesca Rossi
IBM Research, USA & University of Padova, Italy

Copyright © 2018 ACM.

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SIGAI: ACM Special Interest Group on Artificial Intelligence

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 December 2018

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Funding Sources

Google India PhD Fellowship
Prime Minister's Fellowship Scheme for Doctoral Research
The Alan Turing In- stitute under EPSRC grant EP/N510129/1 & TU/B/000074
Fapemig CNPq Capes and Alexander von Humboldt Foundation
public-private partnership between Science & Engineering Research Board (SERB) Department of Science & Technology Government o
David MacKay Newton re- search fellowship at Darwin College

Conference

AIES '18

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SIGAI

AIES '18: AAAI/ACM Conference on AI, Ethics, and Society

February 2 - 3, 2018

LA, New Orleans, USA

Acceptance Rates

AIES '18 Paper Acceptance Rate 61 of 162 submissions, 38%;

Overall Acceptance Rate 61 of 162 submissions, 38%

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Cited By

Rezk ASimkute AVines JElsden CEvans MJones RLuger E(2024)User-Centric Tensions: Exploring Perceived Benefits and (Dis)comfort in Media PersonalisationProceedings of the 13th Nordic Conference on Human-Computer Interaction10.1145/3679318.3685365(1-13)Online publication date: 13-Oct-2024
https://dl.acm.org/doi/10.1145/3679318.3685365
Rezk ASimkute ALuger EVines JElsden CEvans MJones R(2024)Agency Aspirations: Understanding Users' Preferences And Perceptions Of Their Role In Personalised News CurationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642634(1-16)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642634
Rezk A(2023)“Way too good and way beyond comfort”Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society10.1145/3600211.3604761(996-998)Online publication date: 8-Aug-2023
https://dl.acm.org/doi/10.1145/3600211.3604761
Laban PWu CMurakhovs'Ka LChen XXiong C(2023)Designing and Evaluating Interfaces that Highlight News Coverage Diversity Using Discord QuestionsProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581569(1-21)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581569
Hassoun ABeacock IConsolvo SGoldberg BKelley PRussell D(2023)Practicing Information Sensibility: How Gen Z Engages with Online InformationProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3581328(1-17)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3581328
Papakyriakopoulos OEngelmann SWinecoff A(2023)Upvotes? Downvotes? No Votes? Understanding the relationship between reaction mechanisms and political discourse on RedditProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580644(1-28)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544548.3580644
Krieger JSpinde TRuas TKulshrestha JGipp BAizawa AMandl TCarevic ZHinze AMayr PSchaer P(2022)A domain-adaptive pre-training approach for language bias detection in newsProceedings of the 22nd ACM/IEEE Joint Conference on Digital Libraries10.1145/3529372.3530932(1-7)Online publication date: 20-Jun-2022
https://dl.acm.org/doi/10.1145/3529372.3530932
An JKwak HQureshi HWeber I(2021)Precision Public Health Campaign: Delivering Persuasive Messages to Relevant Segments Through Targeted Advertisements on Social MediaJMIR Formative Research10.2196/223135:9(e22313)Online publication date: 24-Sep-2021
https://doi.org/10.2196/22313
Baughan APetelka JYoo CLo JWang SParamasivam AZhou AHiniker A(2021)Someone Is Wrong on the InternetProceedings of the ACM on Human-Computer Interaction10.1145/34492305:CSCW1(1-22)Online publication date: 22-Apr-2021
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Wang YZannettou SBlackburn JBradlyn BDe Cristofaro EStringhini G(2021)A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671843(1481-1492)Online publication date: 15-Dec-2021
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