Moderating (mis)information

被引:1
作者
Meyer, Jacob [1 ]
Mukherjee, Prithvijit [2 ]
Rentschler, Lucas [3 ,4 ]
机构
[1] Cornell Univ, Ithaca, NY USA
[2] Bryn Mawr Coll, Bryn Mawr, PA USA
[3] Utah State Univ, Dept Econ & Finance, Logan, UT 84322 USA
[4] Utah State Univ, Ctr Growth & Opportun, Logan, UT 84322 USA
关键词
Partisanship; Voting; Communication; Social media; Misinformation;
D O I
10.1007/s11127-022-01041-w
中图分类号
F [经济];
学科分类号
02 ;
摘要
This paper uses a laboratory experiment to investigate the efficacy of different content moderation policies designed to combat misinformation on social media. These policies vary the way posts are monitored and the consequence imposed when misinformation is detected. We consider three monitoring protocols: (1) individuals can fact check information shared by other group members for a cost; (2) the social media platform randomly fact checks each post with a fixed probability; (3) the combination of individual and platform fact checking. We consider two consequences: (1) fact-checked posts are flagged, such that the results of the fact check are available to all who view the post; (2) fact-checked posts are flagged, and subjects found to have posted misinformation are automatically fact checked for two subsequent rounds, which we call persistent scrutiny. We compare our data to that of Pascarella et al. (Social media, (mis)information, and voting decisions. Working paper, 2022), which studies an identical environment without content moderation. We find that allowing individuals to fact check improves group decision making and welfare. Platform checking alone does not improve group decisions relative to the baseline with no moderation. It can improve welfare, but only in the case of persistent scrutiny. There are marginal improvements when the two protocols are combined. We also find that flagging is sufficient to curb the negative effects of misinformation. Adding persistent scrutiny does not improve the quality of decision-making; it leads to less engagement on the social media platform as fewer group members share posts.
引用
收藏
页码:159 / 186
页数:28
相关论文
共 50 条
  • [21] Cooking with cannabis: the rapid spread of (mis)information on YouTube
    Cearley, Mary
    Koning, Hatti
    Judge, Bryan
    Riley, Brad
    Jones, Jeffrey
    CLINICAL TOXICOLOGY, 2017, 55 (07) : 821 - 821
  • [22] How orientations to expertise condition the acceptance of (mis)information
    Lyons, Benjamin A.
    CURRENT OPINION IN PSYCHOLOGY, 2023, 54
  • [23] The murmuration of information disorders Aotearoa New Zealand, mis- and disinformation ecologies and the Parliament Protest
    Hannah, Kate
    Hattotuwa, Sanjana
    Taylor, Kayli
    PACIFIC JOURNALISM REVIEW, 2022, 28 (1-2): : 138 - 161
  • [24] Exposure to Health (Mis)Information: Lagged Effects on Young Adults' Health Behaviors and Potential Pathways
    Tan, Andy S. L.
    Lee, Chul-joo
    Chae, Jiyoung
    JOURNAL OF COMMUNICATION, 2015, 65 (04) : 674 - 698
  • [25] The effect of information seeking behaviour on trust in AI in Asia: The moderating role of misinformation concern
    Neyazi, Taberez Ahmed
    Ee, Tan Khai
    Nadaf, Arif
    Schroeder, Ralph
    NEW MEDIA & SOCIETY, 2025, 27 (04) : 2414 - 2433
  • [26] (Mis)information and anxiety: Evidence from a randomized Covid-19 information campaign
    Sadish, D.
    Adhvaryu, Achyuta
    Nyshadham, Anant
    JOURNAL OF DEVELOPMENT ECONOMICS, 2021, 152
  • [28] Challenges Due to Excessive Amount of Online Data and (Mis)Information
    Rojko, Katarina
    Jelovac, Dejan
    CENTRAL EUROPEAN CONFERENCE ON INFORMATION AND INTELLIGENT SYSTEMS (CECIIS 2018), 2018, : 33 - 38
  • [29] Liked and shared tweets during the pandemic: the relationship between intrinsic message features and (mis)information engagement
    Lee, Jiyoung
    Kim, Youllee
    Zhu, Xun
    BEHAVIOUR & INFORMATION TECHNOLOGY, 2024, 43 (08) : 1596 - 1613
  • [30] A taxonomy for modelling and analysis of diffusion of (mis)information in social networks
    Kumar, K. P. Krishna
    Geethakumari, G.
    INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND DISTRIBUTED SYSTEMS, 2014, 13 (02) : 119 - 143