It’s going to be okay: Measuring Access to Support in Online Communities
It’s going to be okay: Measuring Access to Support in Online Communities
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一切都会好起来的：衡量在线社区中获得支持的情况
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
E. L. Mendoncca
中科院分区：
文献类型：
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作者：
D. Dalmazi;A. D. Santos;E. L. Mendoncca
人们使用在线平台寻求对其信息和情感需求的支持。在这里，我们询问透露性别对获得支持有何影响。为了回答这个问题，我们创建了（i）用于识别支持性回复的新数据集和方法，以及（ii）从文本和姓名推断性别的新方法。我们应用这些方法创建了一个包含 1.02 亿个带有性别标签的用户在线互动的新海量语料库，每个语料库均按支持程度进行评级。我们的分析显示，支持率存在广泛且一致的差异：女性身份与较高的支持率相关，但也与较高的贬低率相关。
People use online platforms to seek out support for their informational and emotional needs. Here, we ask what effect does revealing one’s gender have on receiving support. To answer this, we create (i) a new dataset and method for identifying supportive replies and (ii) new methods for inferring gender from text and name. We apply these methods to create a new massive corpus of 102M online interactions with gender-labeled users, each rated by degree of supportiveness. Our analysis shows wide-spread and consistent disparity in support: identifying as a woman is associated with higher rates of support - but also higher rates of disparagement.