We present an approach to classify user validity in survey responses by using a machine learning techniques. The approach is based on collecting user mouse activity on web-surveys and fast predicting validity of the survey in general without analysis of specific answers. Rule based approach, LSTM and HMM models are considered. The approach might be used in web-survey applications to detect suspicious users behaviour and request from them proper answering instead of false data recording.

中文翻译：

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验证心理测量调查的反应

我们提出了一种使用机器学习技术对调查响应中的用户有效性进行分类的方法。该方法基于收集用户在网络调查中的鼠标活动，并在不分析具体答案的情况下快速预测一般调查的有效性。考虑了基于规则的方法、LSTM 和 HMM 模型。该方法可用于网络调查应用程序，以检测可疑用户的行为并要求他们做出正确的回答，而不是记录错误的数据。