公众参与应对社交媒体虚假信息的众包模式及激励策略研究

Research on Crowdsourcing Model and Incentive Strategy of Public Participation to Response Social Media Misinformation

为更好地发挥社交媒体环境下公众在虚假信息应对方面的重要作用,探究能够提升公众参与度与参与质量的激励策略,提出公众群体参与应对社交媒体虚假信息的众包模型,考虑众包任务类型、显性激励和隐性激励对公众群体参与的影响,建立风险偏好下的激励模型,求解其最优激励策略,并据此提出了相关建议。结果显示,众包在虚假信息的应对领域可得到较好的应用;在最优激励的求解过程中,只有较为复杂的众包任务才能对用户产生激励,当任务较为简单时,用户的自我努力和协作性努力与协作效应、参与人数正相关,与感知风险负相关;同时任务发布方的最优激励策略也随各参数的变化而动态改变。

In order to better play the important role of the public in responding to misinformation in the social media environment,explore the best incentive strategies to improve the public participation and the quality of their participation,this paper proposes applying the crowdsourcing mode to the response of the misinformation in the social media,by constructing the conceptual model of the crowdsourcing task,then establishing the crowdsourcing incentive model under the risk preference which considering the impact of the types of crowdsourcing tasks,explicit incentives and implicit incentives on users’participation,and solving the optimal incentive strategy.It also puts forward some relevant suggestions.The results show that the crowdsourcing can be applied to the response of misinformation.In the process of solving the optimal incentive,only complex crowdsourcing task can inspire users,while the crowdsourcing task is simple,users’self-effort and collaborative effort are positively correlated with collaboration effect,number of participants,and negatively correlated with perceived risk.Beside that,the optimal incentive strategy of the task issuer changes dynamically with the change of each parameter.