research-article

Effective Messaging on Social Media: What Makes Online Content Go Viral?

Authors:

Maryam Mousavi,

Robert Axelrod,

Scott AtranAuthors Info & Claims

WWW '22: Proceedings of the ACM Web Conference 2022

Pages 2957 - 2966

https://doi.org/10.1145/3485447.3512016

Published: 25 April 2022 Publication History

Abstract

In this paper, we propose and test three content-based hypotheses that significantly increase message virality. We measure virality as the retweet counts of messages in a pair of real-world Twitter datasets A large dataset - UK Brexit with 51 million tweets from 2.8 million users between June 1, 2015 and May 12, 2019 and a smaller dataset - Nord Stream 2 with 516,000 tweets from 250,000 users between October 1, 2019 and October 15, 2019. We hypothesize, test and conclude that messages incorporating “negativity bias”, “causal arguments” and “threats to personal or societal core values of target audiences” singularly and jointly increase message virality on social media.

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Index Terms

Effective Messaging on Social Media: What Makes Online Content Go Viral?

Index terms have been assigned to the content through auto-classification.

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cover image ACM Conferences

WWW '22: Proceedings of the ACM Web Conference 2022

April 2022

3764 pages

ISBN:9781450390965

DOI:10.1145/3485447

Editors:
Frédérique Laforest
INSA Lyon, France
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Raphaël Troncy
EURECOM, France
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Elena Simperl
King’s College London, UK
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Deepak Agarwal
Pinterest, USA
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KTH Royal Institute of Technology, Sweden
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W3C / retired
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Université Lyon 1, France

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Published: 25 April 2022

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https://dl.acm.org/doi/10.1145/3706119
Qin YJu WWu HLuo XZhang M(2024)Learning Graph ODE for Continuous-Time Sequential RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.334939736:7(3224-3236)Online publication date: 1-Jul-2024
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