学习Reddit上的用户声誉

Alexandre Parmentier, R. Cohen
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引用次数: 7

摘要

在线社交网络的快速发展和对其作为传播错误信息媒介的潜力的认识,引发了人们对多代理网络中声誉和信任建模的兴趣日益浓厚。作为一种对用户对在线社区的影响进行建模的新方法,本文提出了一种从树形讨论中提取特征的方法,并评估了一组基于语言和元数据的特征在Reddit评论数据集中的预测能力。我们表明,仅基于对随后讨论的分析,讨论开始评论的一些品质是可预测的,并概述了如何使用社区反应和可检测的反社会行为之间的学习关联来模拟用户声誉的路线图。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Learning User Reputation on Reddit
The rapid growth of online social networks and the recognition of their potency as a medium for the spread of misinformation has provoked a growing interest in modelling reputation and trust in multi agent networks. Intended as a novel approach towards modelling the effects a user is having on the well-being of an online community, this paper presents a method for extracting features from tree-shaped discussions and evaluates a large set of linguistic and metadata based features for their predictive ability in a data set of Reddit comments. We show that some qualities of discussion-starting comments are predictable based solely on an analysis of the discussion that follows, and outline a road-map for how learning associations between community reactions and detectable antisocial behaviour could be used to model the reputation of users.
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