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How Humans Versus Bots React to Deceptive and Trusted News Sources: A Case Study of Active Users

机译:人类与机器人如何应对欺骗性和可信新闻源:活跃用户的案例研究

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Society`s reliance on social media as a primary source of news has spawned a renewed focus on the spread of misinformation. In this work, we identify the differences in how social media accounts identified as bots react to news sources of varying credibility, regardless of the veracity of the content those sources have shared. We analyze bot and human responses annotated using a fine-grained model that labels responses as being an answer, appreciation, agreement, disagreement, an elaboration, humor, or a negative reaction. We present key findings of our analysis into the prevalence of bots, the variety and speed of bot and human reactions, and the disparity in authorship of reaction tweets between these two sub-populations. We observe that bots are responsible for 9-15% of the reactions to sources of any given type but comprise only 7-10% of accounts responsible for reaction-tweets; trusted news sources have the highest proportion of humans who reacted; bots respond with significantly shorter delays than humans when posting answer-reactions in response to sources identified as propaganda. Finally, we report significantly different inequality levels in reaction rates for accounts identified as bots vs not.
机译:社会对社交媒体作为新闻的主要来源的依赖使得人们重新关注错误信息的传播。在这项工作中,我们确定了被识别为漫游器的社交媒体帐户对信誉各异的新闻来源的反应方式的差异,无论这些来源共享内容的准确性如何。我们使用细粒度模型分析被注释的漫游器和人类响应,该模型将响应标记为答案,赞赏,同意,不同意,阐述,幽默或否定反应。我们提供了关于机器人的流行率,机器人和人类反应的种类和速度以及这两个子群体之间的反应推文的作者差异的分析的主要发现。我们发现,漫游器负责对任何给定类型的源进行9-15%的反应,但仅占负责反应推文的7-10%的帐户;值得信赖的新闻来源做出回应的人比例最高;在发布针对被识别为宣传的消息的答案时,机器人的响应延迟比人类要短得多。最后,我们报告了被识别为漫游器的帐户与未发现漫游器的帐户的反应率存在显着不同的不平等程度。

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