关于鉴别和剔除虚假数据的讨论 #81
lilongsky
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Enhancement
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(还有 仲恺说唱职业技术学院 |
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关于这个滥用、虚假的数据 如果先每个都查一遍再放出来,工作量太大了,问卷几乎是一天能有 1k 份的量。 现在我们的策略是: 对于集中反馈帖这个正有想法,应该不久后可以有。 |
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一个粗暴的建议,如果能按照ip排列的话,遇到虚假数据就将那个ip段所有的提交拎出来放到最后处理。 |
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在翻查 Github的学校页面时,发现一个明显为虚假的学校数据。
链接:
https://github.com/CollegesChat/university-information/blob/master/questionnaires/universities/%E9%BA%BB%E7%9C%81%E7%90%86%E5%B7%A5.md
条件允许的话,可以考虑招募志愿者对于问卷进行一轮检视,排除那些明显的虚假数据。
或者在允许在讨论区集中反馈后修改?
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