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| Research on Altmetrics Evaluation Model of Academic Conference Based on GBDT |
| Zhang Yang, Ye Yue, Zhang Zongxiang, She Fang, Chen Xiyu |
| School of Information Management, Sun Yat-sen University, Guangzhou 510006 |
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Abstract In order to spread and share academic achievements in a certain field, academic conferences serve as an inevitable and important part in the development of that subject field. In certain cases, academic conferences are favored by researchers because of their timely dissemination of knowledge. This paper collects relevant data from altmetrics indicators—Altmetrics. com and PlumX—on the international conferences on artificial intelligence from 2007 to 2014, with the help of descriptive statistics and gradient lifting decision tree. Using indicators screening, data imbalance processing, and model optimization, a meeting evaluation model based on the gradient lifting decision tree was formed. This model combines popular machine learning models with latest altmetrics indexes. It can effectively cover the deficiencies of traditional informetrics indicators and improve the accuracy of the conference evaluation model, which can enrich related research on conference evaluation and become a reference for future research.
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Received: 28 November 2018
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