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9. Min, C., Bu, Y., & Sun, J. (in press). Predicting Scientific Breakthroughs Based on Knowledge Structure Variations. Technological Forecasting & Social Change, 164, 120502. https://doi.org/10.1016/j.techfore.2020.120502
8. Min, C., Bu, Y., Wu, D., Ding, Y., & Zhang, Y. (2020) Identifying citation patterns of scientific breakthroughs: A perspective of dynamic citation process. Information Processing & Management, 58(1), 102428. https://doi.org/10.1016/j.ipm.2020.102428
7. Min, C., Chen, Q, Yan, E, Bu, Y, Sun, J. (2020). Citation cascade and the evolution of topic relevance. Journal of the Association for Information Science and Technology, 1– 18. https://doi.org/10.1002/asi.24370
6. Zhao, Z., Bu, Y., Kang, L., Min, C., Bian, Y., Tang, L., & Li, J. (2020). An investigation of the relationship between scientists’ mobility to/from China and their research performance. Journal of Informetrics, 14(2), 101037.
5. Zhao, L., & Min, C. (2019). The Rise of Fashion Informatics: A Case of Data-Mining-Based Social Network Analysis in Fashion. Clothing and Textiles Research Journal, 37(2), 87-102.
4. Min, C., Ding, Y., Li, J., Bu, Y., Pei, L., & Sun, J. (2018). Innovation or imitation: The diffusion of citations. Journal of the Association for Information Science and Technology, 69(10), 1271-1282.
3. Sun, J., Sheng, D., Gu, D., Du, J. T., & Min, C. (2017). Understanding link sharing tools continuance behavior in social media. Online Information Review, 41(1), 119-133.
2. Min, C., Sun, J., Pei, L., & Ding, Y. (2016). Measuring delayed recognition for papers: Uneven weighted summation and total citations. Journal of Informetrics, 10(4), 1153-1165.
1. Sun, J., Min, C., & Li, J. (2016). A vector for measuring obsolescence of scientific articles. Scientometrics, 107(2), 745-757.
Chinese journal articles
19. 高伊林, & 闵超#. (2021). 中美对一带一路地区技术扩散结构比较研究. 数据分析与知识发现, 1-22.
18. 皮耶特·弗朗索瓦, J.G.曼宁, 哈维·怀特豪斯, 罗布·布伦南, 托马斯·柯里, 凯文·费尼, 彼得·特钦, & 闵超. (2020). 全球史的宏观显微镜: Seshat全球史数据库的方法论梳理. 全球史评论, 2020(02), 42-61+305-306.
17. 赵英男, 王欣, 王全胜, 闵超, & 陈晓威. (2020). 默认好评对消费者购买行为的影响. 管理科学(国家自科基金委管理学部认定的管理类A类期刊), 33(4), 137-148.
16. 颜嘉麒, 闵超#, 余厚强, 魏家鹏, 贾韬, & 马建. (2020). 科学大数据背景下的科研协作:特征、案例与机遇. 图书与情报(人大复印资料全文转载), (3), 127-133.
15. 闵超#, 张帅, 孙建军. (2020). 科学文献网络中的引文扩散——以2011年诺贝尔化学奖获奖论文为例. 情报学报(国家自科基金委管理学部认定的管理类A类期刊, 南大文科一流期刊), 39(3), 259-273.
14. 陆天驰, 闵超#,高伊林, & 李阳 (2019). 竞争情报视角下的中美人工智能技术领域差距分析——以美国商品管制清单为例. 情报杂志.
13. 高伊林, & 闵超#. (2019). 中美与 “一带一路” 沿线国家专利合作态势分析. 图书情报知识, (4), 94-103.
12. 张靖雯, 孙建军, & 闵超. (2019). 引文起飞的定义与量化方法研究. 情报学报(国家自科基金委管理学部认定的管理类A类期刊, 南大文科一流期刊), 38(8), 786-797.
11. 李凌英, 闵超#, & 孙建军. (2019). 引文波峰的量化与分布探究. 情报学报(国家自科基金委管理学部认定的管理类A类期刊, 南大文科一流期刊), 38(7), 697-708.
10. 黄文彬, 王冰璐, 步一, & 闵超. (2018). 关键词共引分析的科学计量方法研究. 情报资料工作, 221(02), 39-44.
9. 仇鹏飞, 孙建军, & 闵超. (2018). 科学研究中的师承关系评述与思考. 图书与情报, 183(05), 56-61+124.
8. 闵超, Ying Ding, 李江, & 孙建军. (2018). 单篇论著的引文扩散. 情报学报(国家自科基金委管理学部认定的管理类A类期刊, 南大文科一流期刊, 人大复印资料全文转载), 37(4), 341-350.
7. 闵超, 步一, & 孙建军. (2017). 基于专利大数据的中国国际专利技术流动分析. 图书与情报, 37(05), 33-39.
6. 闵超, & 孙建军. (2016). 美国政府科技报告网络服务新进展. 情报资料工作, 37(1), 80-86.
5. 闵超, 石佳靓, & 孙建军. (2015). 新闻出版业大数据应用新业态分析. 中国出版, (15), 65-68.
4. 闵超, 赵宇翔, & 孙建军. (2015). 国外灰色文献领域研究态势分析——基于自组织映射的文本挖掘方法. 情报学报(国家自科基金委管理学部认定的管理类A类期刊,南大文科一流期刊), 34(10), 1111-1120.
3. 闵超, & 孙建军. (2014). 基于关键词交集的学科交叉研究热点分析—以图书情报学和新闻传播学为例. 情报杂志, 33(5), 76-82.
2. 闵超, & 孙建军. (2014). 中文网络灰色文献分布探析——基于 Google Scholar 的样本分析. 图书情报工作, 58(24), 73-79.
1. 闵超, & 孙建军. (2014). 学科交叉研究热点聚类分析——以国内图书情报学和新闻传播学为例. 图书情报工作, 58(01), 109-116.
Conference papers & presentations
9. Xu, J., Min, C., Huang, W., & Bu, Y. (2021). Interdisciplinarity vs. Unidisciplinarity: A Structural Comparison of Multi-generation Citations and References. Proceedings of 18th International Society of Scientometrics and Informetrics Conference. 2021.
8. Min, C., Bu, Y., & Sun, J. (2019). Comparing Breakthrough and Non-Breakthrough Papers from Early Citing Structures. Proceedings of 17th International Society of Scientometrics and Informetrics Conference. Rome,Italy, 2019.
7. Zhao, Z., Li, J., Min, C., Bu, Y., Kang, L., & Bian, Y. (2019). Scientists’ academic disruptiveness significantly increased after they moved to China. Proceedings of the Association for Information Science and Technology, 56(1), 852-854. Melbourne, Australia, 2019.
6. Zhao, Y., Min, C., Han, X., Deng, S., Wang, H., & Li, J. (2019). Listening to the user’s voice: A temporal analysis of autism‐related questions on Quora. Proceedings of the Association for Information Science and Technology, 56(1), 513-516. Melbourne, Australia, 2019.
5. Min, C., Wang, Y., Bu, Y., Kang, L., Sun, J., & Li, J. (2019). Why are some studies more popular in social media?. iConference 2019 Proceedings. Washington DC, USA, 2019.
4. Min, C., Bu, Y., Sun, J., & Ding, Y. (2018). Is scientific novelty reflected in citation patterns?. Proceedings of the Association for Information Science and Technology, 55(1), 875-876. Vancouver, Canada, 2018.
3. Min, C., Sun, J., & Ding, Y. (2017). Quantifying the evolution of citation cascades. Proceedings of the Association for Information Science and Technology, 54(1), 761-763. Washington DC, USA, 2017.
2. Min, C., & Sun, J. (2016). A new perspective to measure delayed recognition in a simple way. iConference 2016 Proceedings. Philadelphia, USA, 2016.
1. Sun, J., Li, J. & Min, C. (2015). A vector for measuring obsolescence of scientific articles. Proceedings of 15th International Society of Scientometrics and Informetrics Conference. Istanbul,Turkey, 2015.
Others
Chen, M., & Min, C. (2017). Visualizing the knowledge of Voluntary and Nonprofit Sector Research: Panorama and Foundation.