The deluge of new papers has significantly blocked the development of academics, which is mainly caused by author-level and publication-level evaluation metrics that only focus on quantity. Those metrics have resulted in several severe problems that trouble scholars focusing on the important research direction for a long time and even promote an impetuous academic atmosphere. To solve those problems, we propose Phocus, a novel academic evaluation mechanism for authors and papers. Phocus analyzes the sentence containing a citation and its contexts to predict the sentiment towards the corresponding reference. Combining others factors, Phocus classifies citations coarsely, ranks all references within a paper, and utilizes the results of the classifier and the ranking model to get the local influential factor of a reference to the citing paper. The global influential factor of the reference to the citing paper is the product of the local influential factor and the total influential factor of the citing paper. Consequently, an author's academic influential factor is the sum of his contributions to each paper he co-authors.

翻译：为了解决这些问题,我们建议Phocus为作者和论文提供一个新的学术评价机制。Phocus分析含有引用内容的句子及其背景,以预测对相应参考内容的看法。Phocus将其它因素合并在一起,Phocus粗略地分类引文,将所有参考文献列在文件中,并利用分类和排名模型的结果获得引用论文的地方影响因素。引用论文的全球影响因素是当地有影响因素的产物和引用论文的总影响因素。因此,作者的学术影响因素是他对每篇论文的共同作者的贡献的总和。