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The effects of trust and influence on the spreading of low and high quality information

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  • Oliveira, Diego F.M.
  • Chan, Kevin S.

Abstract

In this work, we employ a minimal agent-based model to explore the mechanisms that regulate competition between memes that spread online. We investigate the case in which each piece of information has a quality, and the higher is the quality the higher are the chances of being transmitted. The model allows us to study the impact of influential nodes on the spreading behavior. We show that meme’s quality does not guarantee virility, but there is a strong correlation between the meme’s success and the influence of the agent who introduced it. When trust is incorporated into the model and the agents can decided whether or not to accept a meme, we show that both lifetime and popularity distributions have broad power-law tails indicating that only a few memes spread virally through the population reproducing perfectly the broad distributions obtained from empirical data.

Suggested Citation

  • Oliveira, Diego F.M. & Chan, Kevin S., 2019. "The effects of trust and influence on the spreading of low and high quality information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 657-663.
    • Handle: RePEc:eee:phsmap:v:525:y:2019:i:c:p:657-663
    DOI: 10.1016/j.physa.2019.03.034
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    References listed on IDEAS

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    1. Michael J. Stringer & Marta Sales‐Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    2. repec:cup:cbooks:9780511771576 is not listed on IDEAS
    3. Michael J. Stringer & Marta Sales-Pardo & Luís A. Nunes Amaral, 2010. "Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1377-1385, July.
    4. Sinan Aral & Dylan Walker, 2011. "Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks," Management Science, INFORMS, vol. 57(9), pages 1623-1639, February.
    5. Marcella Tambuscio & Diego F. M. Oliveira & Giovanni Luca Ciampaglia & Giancarlo Ruffo, 2018. "Network segregation in a model of misinformation and fact-checking," Journal of Computational Social Science, Springer, vol. 1(2), pages 261-275, September.
    6. Easley,David & Kleinberg,Jon, 2010. "Networks, Crowds, and Markets," Cambridge Books, Cambridge University Press, number 9780521195331, September.
    7. Xiaoyan Qiu & Diego F. M. Oliveira & Alireza Sahami Shirazi & Alessandro Flammini & Filippo Menczer, 2017. "Limited individual attention and online virality of low-quality information," Nature Human Behaviour, Nature, vol. 1(7), pages 1-7, July.
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    Cited by:

    1. Vincenza Carchiolo & Alessandro Longheu & Michele Malgeri & Giuseppe Mangioni & Marialaura Previti, 2021. "Mutual Influence of Users Credibility and News Spreading in Online Social Networks," Future Internet, MDPI, vol. 13(5), pages 1-15, April.
    2. Xusen Cheng & Fei Guo & Jin Chen & Kejiang Li & Yihui Zhang & Peng Gao, 2019. "Exploring the Trust Influencing Mechanism of Robo-Advisor Service: A Mixed Method Approach," Sustainability, MDPI, vol. 11(18), pages 1-20, September.

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