Quick Evaluation of Research Impacts at Conferences Using SNS

S. Fukuda, Hikaru Nakahashi, Hidetsugu Nanba, T. Takezawa
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Abstract

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.
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利用SNS快速评价会议研究影响
我们正在研究在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力或重要性是通过引文关系来评价的,如影响因子和引文半衰期。然而,这些基于引用的方法需要较长的时间来评估研究影响,因此不适合评估研究论文在会议上的当前影响。为了解决这个问题,我们正在研究使用Twitter自动评估研究影响。参加学术会议的研究人员经常在Twitter上发表自己的观点或评论。在这里,有很多评论的研究论文(报告)被认为是优秀的,在会议期间有很强的影响力。在本文中,我们提出了一种自动将tweet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一篇研究论文对齐,(3)通过对齐推文的数量计算每篇研究论文的研究影响。我们做了一些实验来证实我们方法的有效性。从结果中,我们获得了0.223的MRR评分,优于基线方法。
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