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Quick Evaluation of Research Impacts at Conferences Using SNS

机译:使用SNS快速评估会议上的研究影响

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We are investigating ways of evaluating research impact as soon as possible after publication. Traditionally, the research impact or importance of academic journals has been evaluated using citation relations, such as the impact factor and the citation half-life. However, these citation-based methods require long periods to evaluate research impact and therefore are not suitable for evaluating the current impact of research papers at conferences. To solve this problem, we are studying the automatic evaluation of research impact using Twitter. Researchers participating in academic conferences often post their opinions or comments on Twitter. Here, research papers (presentations) that have many comments are considered to be outstanding and to have strong impact during the conference. In this paper, we propose a method for automatically aligning tweets with research papers. The procedure consists of the following three steps: (1) detecting valuable tweets, (2) aligning each valuable tweet with a research paper, and (3) calculating the research impact of each research paper by the number of aligned tweets. We conducted some experiments to confirm the effectiveness of our method. From the results, we obtained an MRR score of 0.223, which outperformed a baseline method.
机译:我们正在研究发表后尽快评估研究影响的方法。传统上,学术期刊的研究影响或重要性是使用引文关系(例如影响因子和引文半衰期)进行评估的。但是,这些基于引用的方法需要很长时间才能评估研究影响,因此不适合评估会议上研究论文的当前影响。为了解决这个问题,我们正在研究使用Twitter进行研究影响的自动评估。参加学术会议的研究人员经常在Twitter上发表他们的意见或评论。在这里,具有很多评论的研究论文(演讲)被认为是杰出的,并且在会议期间具有很强的影响力。在本文中,我们提出了一种自动将推文与研究论文对齐的方法。该过程包括以下三个步骤:(1)检测有价值的推文;(2)将每条有价值的推文与研究论文对齐;以及(3)通过对齐的推文数量计算每篇研究论文的研究影响。我们进行了一些实验,以确认我们方法的有效性。从结果中,我们获得了0.223的MRR得分,优于基线方法。

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