Moving Beyond Set-It-And-Forget-It Privacy Settings on Social Media
Moving Beyond Set-It-And-Forget-It Privacy Settings on Social Media
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DOI：
10.1145/3319535.3354202
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发表时间：
2019-11
期刊：
影响因子：
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通讯作者：
Mainack Mondal;Günce Su Yilmaz;Noah Hirsch;Mohammad Taha Khan;Michael Tang;Christopher Tran;Chris Kanich;Blase Ur;E. Zheleva
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文献类型：
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作者：
Mainack Mondal;Günce Su Yilmaz;Noah Hirsch;Mohammad Taha Khan;Michael Tang;Christopher Tran;Chris Kanich;Blase Ur;E. Zheleva
当用户在社交媒体上发帖时，他们通过选择很少被再次访问的访问控制设置来保护自己的隐私。用户生活和关系的变化，以及社交媒体平台本身的变化，可能会导致帖子的活跃隐私设置与期望设置之间的不匹配。管理这一设置的重要性，加上需要评估的潜在朋友-帖子对的数量很大，因此有必要采用半自动方法。我们通过结合用户研究和开发潜在不匹配隐私设置的自动推理来解决这个问题。共有78名Facebook用户重新评估了他们在Facebook上发布的五篇帖子的隐私设置，还指出了一些朋友是否应该能够访问每一篇帖子。他们还解释了他们的决定。有了这些用户数据，我们设计了一个分类器来识别当前分享设置不正确的帖子。该分类器比基于好友互动的基准分类器提高了317%。我们还发现，许多最有用的特征可以在没有用户干预的情况下收集，并确定了提高分类器精度的方向。
When users post on social media, they protect their privacy by choosing an access control setting that is rarely revisited. Changes in users' lives and relationships, as well as social media platforms themselves, can cause mismatches between a post's active privacy setting and the desired setting. The importance of managing this setting combined with the high volume of potential friend-post pairs needing evaluation necessitate a semi-automated approach. We attack this problem through a combination of a user study and the development of automated inference of potentially mismatched privacy settings. A total of 78 Facebook users reevaluated the privacy settings for five of their Facebook posts, also indicating whether a selection of friends should be able to access each post. They also explained their decision. With this user data, we designed a classifier to identify posts with currently incorrect sharing settings. This classifier shows a 317% improvement over a baseline classifier based on friend interaction. We also find that many of the most useful features can be collected without user intervention, and we identify directions for improving the classifier's accuracy.