TY - GEN
T1 - Quick Evaluation of Research Impacts at Conferences Using SNS
AU - Fukuda, Satoshi
AU - Nakahashi, Hikaru
AU - Nanba, Hidetsugu
AU - Takezawa, Toshiyuki
PY - 2016/2/11
Y1 - 2016/2/11
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84962220270&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962220270&partnerID=8YFLogxK
U2 - 10.1109/DEXA.2015.64
DO - 10.1109/DEXA.2015.64
M3 - Conference contribution
T3 - Proceedings - International Workshop on Database and Expert Systems Applications, DEXA
SP - 259
EP - 263
BT - Proceedings - 26th International Workshop on Database and Expert Systems Applications, DEXA 2015
A2 - Spies, Marcus
A2 - Wagner, Roland R.
A2 - Tjoa, A Min
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 26th International Workshop on Database and Expert Systems Applications, DEXA 2015
Y2 - 1 September 2015 through 4 September 2015
ER -