Friction Interventions to Curb the Spread of Misinformation on Social Media

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning

Standard

Friction Interventions to Curb the Spread of Misinformation on Social Media. / Jahn, Laura; Rendsvig, Rasmus Kræmmer; Flammini, Alessandro; Menczer, Filippo ; Hendricks, Vincent F.

I: arXiv preprint arXiv:1908.00605, 2023, s. 1-17.

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning

Harvard

Jahn, L, Rendsvig, RK, Flammini, A, Menczer, F & Hendricks, VF 2023, 'Friction Interventions to Curb the Spread of Misinformation on Social Media', arXiv preprint arXiv:1908.00605, s. 1-17. https://doi.org/10.48550/arXiv.2307.11498

APA

Jahn, L., Rendsvig, R. K., Flammini, A., Menczer, F., & Hendricks, V. F. (2023). Friction Interventions to Curb the Spread of Misinformation on Social Media. arXiv preprint arXiv:1908.00605, 1-17. https://doi.org/10.48550/arXiv.2307.11498

Vancouver

Jahn L, Rendsvig RK, Flammini A, Menczer F, Hendricks VF. Friction Interventions to Curb the Spread of Misinformation on Social Media. arXiv preprint arXiv:1908.00605. 2023;1-17. https://doi.org/10.48550/arXiv.2307.11498

Author

Jahn, Laura ; Rendsvig, Rasmus Kræmmer ; Flammini, Alessandro ; Menczer, Filippo ; Hendricks, Vincent F. / Friction Interventions to Curb the Spread of Misinformation on Social Media. I: arXiv preprint arXiv:1908.00605. 2023 ; s. 1-17.

Bibtex

@article{c59b4bc263ae4ffd913fa056d1b9053c,
title = "Friction Interventions to Curb the Spread of Misinformation on Social Media",
abstract = "Social media has enabled the spread of information at unprecedented speeds and scales, and withit the proliferation of high-engagement, low-quality content. Friction—behavioral design measures that make the sharing of content more cumbersome—might be a way to raise the quality of what isspread online. Here, we study the effects of friction with and without quality-recognition learning. Experiments from an agent-based model suggest that friction alone decreases the number of posts without improving their quality. A small amount of friction combined with learning, however, increasesthe average quality of posts significantly. Based on this preliminary evidence, we propose a friction intervention with a learning component about the platform{\textquoteright}s community standards, to be tested via a field experiment. The proposed intervention would have minimal effects on engagement and may easily be deployed at scale as it does not require labeling of content or detection of badactors.",
author = "Laura Jahn and Rendsvig, {Rasmus Kr{\ae}mmer} and Alessandro Flammini and Filippo Menczer and Hendricks, {Vincent F.}",
year = "2023",
doi = "10.48550/arXiv.2307.11498",
language = "English",
pages = "1--17",
journal = "arXiv preprint arXiv:1908.00605",

}

RIS

TY - JOUR

T1 - Friction Interventions to Curb the Spread of Misinformation on Social Media

AU - Jahn, Laura

AU - Rendsvig, Rasmus Kræmmer

AU - Flammini, Alessandro

AU - Menczer, Filippo

AU - Hendricks, Vincent F.

PY - 2023

Y1 - 2023

N2 - Social media has enabled the spread of information at unprecedented speeds and scales, and withit the proliferation of high-engagement, low-quality content. Friction—behavioral design measures that make the sharing of content more cumbersome—might be a way to raise the quality of what isspread online. Here, we study the effects of friction with and without quality-recognition learning. Experiments from an agent-based model suggest that friction alone decreases the number of posts without improving their quality. A small amount of friction combined with learning, however, increasesthe average quality of posts significantly. Based on this preliminary evidence, we propose a friction intervention with a learning component about the platform’s community standards, to be tested via a field experiment. The proposed intervention would have minimal effects on engagement and may easily be deployed at scale as it does not require labeling of content or detection of badactors.

AB - Social media has enabled the spread of information at unprecedented speeds and scales, and withit the proliferation of high-engagement, low-quality content. Friction—behavioral design measures that make the sharing of content more cumbersome—might be a way to raise the quality of what isspread online. Here, we study the effects of friction with and without quality-recognition learning. Experiments from an agent-based model suggest that friction alone decreases the number of posts without improving their quality. A small amount of friction combined with learning, however, increasesthe average quality of posts significantly. Based on this preliminary evidence, we propose a friction intervention with a learning component about the platform’s community standards, to be tested via a field experiment. The proposed intervention would have minimal effects on engagement and may easily be deployed at scale as it does not require labeling of content or detection of badactors.

UR - https://arxiv.org/abs/2307.11498

U2 - 10.48550/arXiv.2307.11498

DO - 10.48550/arXiv.2307.11498

M3 - Journal article

SP - 1

EP - 17

JO - arXiv preprint arXiv:1908.00605

JF - arXiv preprint arXiv:1908.00605

ER -

ID: 374172879