本研究对互联网上的学术型用户生成内容进行质量评价，首先通过信息检索用户实验和实验后的访谈获取科研人员对网络学术信息的评价标准，然 后结合已有研究的成果设计出一个质量评估标准体系；接着利用大规模问卷 的方式获取科研人员对各评价标准的重要性打分情况；最后用主成分分析法 得出模型中的评估标准及权重。研究结论是得到一个包括 2 个一级指标和 12 个二级指标的质量评估模型，每个指标都被赋予了权重。研究意义在于为科研 人员在互联网上查找更高质量的学术信息提供评价标准和方法，以及为搜索 引擎结果重排序提供理论依据。

This study aims to evaluate the quality of online academic information. Firstly,we collected evaluation criteria by conducting information retrieval behavior experiments and interviews. Then, an online information quality evaluation criteria system was formed with the help of existing studies. After that, using an online questionnaire that presented these criteria with definition, we collected data on the importance of each criterion. At last, principal components analysis of data was used to decide the criteria and rights to produce the model. The conclusion is a quality evaluation model with two first-class indicators and twelve second-class indicators. The purpose of this study is to help researchers find high-quality online academic information and to provide theoretical basis for later studies like search engine results re-ranking.