Literature DB >> 32541771

How behavioural sciences can promote truth, autonomy and democratic discourse online.

Philipp Lorenz-Spreen1, Stephan Lewandowsky2,3, Cass R Sunstein4, Ralph Hertwig5.   

Abstract

Public opinion is shaped in significant part by online content, spread via social media and curated algorithmically. The current online ecosystem has been designed predominantly to capture user attention rather than to promote deliberate cognition and autonomous choice; information overload, finely tuned personalization and distorted social cues, in turn, pave the way for manipulation and the spread of false information. How can transparency and autonomy be promoted instead, thus fostering the positive potential of the web? Effective web governance informed by behavioural research is critically needed to empower individuals online. We identify technologically available yet largely untapped cues that can be harnessed to indicate the epistemic quality of online content, the factors underlying algorithmic decisions and the degree of consensus in online debates. We then map out two classes of behavioural interventions-nudging and boosting- that enlist these cues to redesign online environments for informed and autonomous choice.

Year:  2020        PMID: 32541771     DOI: 10.1038/s41562-020-0889-7

Source DB:  PubMed          Journal:  Nat Hum Behav        ISSN: 2397-3374


  15 in total

1.  Citizens Versus the Internet: Confronting Digital Challenges With Cognitive Tools.

Authors:  Anastasia Kozyreva; Stephan Lewandowsky; Ralph Hertwig
Journal:  Psychol Sci Public Interest       Date:  2020-12

2.  On network backbone extraction for modeling online collective behavior.

Authors:  Carlos Henrique Gomes Ferreira; Fabricio Murai; Ana P C Silva; Martino Trevisan; Luca Vassio; Idilio Drago; Marco Mellia; Jussara M Almeida
Journal:  PLoS One       Date:  2022-09-15       Impact factor: 3.752

3.  A CNN-Based Framework for Predicting Public Emotion and Multi-Level Behaviors Based on Network Public Opinion.

Authors:  Hangfeng Lin; Naiqing Bu
Journal:  Front Psychol       Date:  2022-06-23

4.  A federated graph neural network framework for privacy-preserving personalization.

Authors:  Chuhan Wu; Fangzhao Wu; Lingjuan Lyu; Tao Qi; Yongfeng Huang; Xing Xie
Journal:  Nat Commun       Date:  2022-06-02       Impact factor: 17.694

5.  Understanding the dynamics emerging from infodemics: a call to action for interdisciplinary research.

Authors:  Stephan Leitner; Bartosz Gula; Dietmar Jannach; Ulrike Krieg-Holz; Friederike Wall
Journal:  SN Bus Econ       Date:  2021-01-11

6.  When Does an Individual Accept Misinformation? An Extended Investigation Through Cognitive Modeling.

Authors:  David Borukhson; Philipp Lorenz-Spreen; Marco Ragni
Journal:  Comput Brain Behav       Date:  2022-05-11

7.  The consequences of online partisan media.

Authors:  Andrew M Guess; Pablo Barberá; Simon Munzert; JungHwan Yang
Journal:  Proc Natl Acad Sci U S A       Date:  2021-04-06       Impact factor: 11.205

8.  Lateral reading and monetary incentives to spot disinformation about science.

Authors:  Folco Panizza; Piero Ronzani; Carlo Martini; Simone Mattavelli; Tiffany Morisseau; Matteo Motterlini
Journal:  Sci Rep       Date:  2022-04-05       Impact factor: 4.379

9.  News credibility labels have limited average effects on news diet quality and fail to reduce misperceptions.

Authors:  Kevin Aslett; Andrew M Guess; Richard Bonneau; Jonathan Nagler; Joshua A Tucker
Journal:  Sci Adv       Date:  2022-05-06       Impact factor: 14.957

10.  Out-group animosity drives engagement on social media.

Authors:  Steve Rathje; Jay J Van Bavel; Sander van der Linden
Journal:  Proc Natl Acad Sci U S A       Date:  2021-06-29       Impact factor: 11.205

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.