刘嘉宇, 李贺, 沈旺, 祝琳琳, 李世钰. 融合多源异构在线评论的开放式创新社区创意采纳预测研究[J]. 情报学报, 2024, 43(1): 48-60.
Liu Jiayu, Li He, Shen Wang, Zhu Linlin, Li Shiyu. Integrating Multi-source Heterogeneous Online Reviews to Predict the Adoption of Ideas in Open Innovation Communities. 情报学报, 2024, 43(1): 48-60.
1 曲青山. 深刻理解中国式现代化的科学内涵[OL]. (2022-11-04) [2024-01-08].http://theory.people.com.cn/n1/2022/1104/c40531-32558718.html. 2 张海涛, 刘伟利, 任亮, 等. 开放式创新社区的用户知识协同交互机理及其可视化研究[J]. 情报学报, 2021, 40(5): 523-533. 3 Chesbrough H W. Open innovation: the new imperative for creating and profiting from technology[M]. Boston: Harvard Business Review Press, 2006. 4 吉海颖, 戚桂杰, 李娜. 开放式创新平台用户交互对隐性社区的影响研究[J]. 图书情报工作, 2022, 66(5): 105-115. 5 王婷婷, 王凯平, 戚桂杰. 基于情感分析的开放式创新平台创意采纳研究: 以Salesforce为例[J]. 数据分析与知识发现, 2018, 2(4): 38-47. 6 Di Gangi P M, Wasko M, Hooker R E. Getting customers’ ideas to work for you: learning from Dell how to succeed with online user innovation communities[J]. MIS Quarterly Executive, 2010, 9(4): 213-228. 7 秦敏, 许安琪. 在线用户创新社区创意采纳机理研究——基于整合理论视角[J]. 信息系统学报, 2022(1): 47-61. 8 化柏林, 李广建. 大数据环境下多源信息融合的理论与应用探讨[J]. 图书情报工作, 2015, 59(16): 5-10. 9 Liu P, Wang L Y, Ding X H. Modeling product feature usability through web mining[C]// Proceedings of the 2nd International Conference on E-business and Information System Security. Piscataway: IEEE, 2010: 1-4. 10 Pirkkalainen H, Pawlowski J M, Bick M, et al. Engaging in knowledge exchange: the instrumental psychological ownership in open innovation communities[J]. International Journal of Information Management, 2018, 38(1): 277-287. 11 Stanko M A. Toward a theory of remixing in online innovation communities[J]. Information Systems Research, 2016, 27(4): 773-791. 12 黄璐. 开放式创新社区创意采纳预测的研究——基于Salesforce社区[D]. 广州: 华南理工大学, 2020. 13 Martinez-Torres R, Olmedilla M. Identification of innovation solvers in open innovation communities using swarm intelligence[J]. Technological Forecasting and Social Change, 2016, 109: 15-24. 14 王婷婷. 创新价值链视角下企业开放式创新平台创意管理研究[D]. 济南: 山东大学, 2018. 15 Lee H J, Suh Y. Who creates value in a user innovation community? A case study of MyStarbucksIdea.com[J]. Online Information Review, 2016, 40(2): 170-186. 16 谢海华, 陈雪飞, 都仪敏, 等. 结合统计特征和图模型的半监督式中文关键短语抽取方法[J]. 中文信息学报, 2022, 36(4): 57-65. 17 Hu G N, Dai X Y, Song Y Y, et al. A synthetic approach for recommendation: combining ratings, social relations, and reviews[C]// Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Palo Alto: AAAI Press, 2015: 175-181. 18 Yang X, Yang G F, Wu J N. Integrating rich and heterogeneous information to design a ranking system for multiple products[J]. Decision Support Systems, 2016, 84: 117-133. 19 Guo C H, Du Z L, Kou X Y. Mining online customer reviews for products aspect-based ranking[C]// Proceedings of the International Symposium on Knowledge and Systems Sciences. Singapore: Springer, 2017: 150-161. 20 贺雅琪. 多源异构数据融合关键技术研究及其应用[D]. 成都: 电子科技大学, 2018. 21 Khaleghi B, Khamis A, Karray F O, et al. Multisensor data fusion: a review of the state-of-the-art[J]. Information Fusion, 2013, 14(1): 28-44. 22 刘嘉璐, 袁勤俭. 信任转移理论及其在信息系统研究领域的应用与展望[J]. 现代情报, 2022, 42(5): 160-169. 23 Stewart K J. Transference as a means of building trust in World Wide Web sites[C]// Proceedings of the 20th International Conference on Information Systems. Atlanta: Association for Information Systems, 1999: 459-464. 24 Verhagen T, van Dolen W. Online purchase intentions: a multi-channel store image perspective[J]. Information & Management, 2009, 46(2): 77-82. 25 Ma D D, Li S Q, Du J T, et al. Engaging voluntary contributions in online review platforms: the effects of a hierarchical badges system[J]. Computers in Human Behavior, 2022, 127: 107042. 26 Leong L Y, Hew T S, Ooi K B, et al. Understanding trust in ms-commerce: the roles of reported experience, linguistic style, profile photo, emotional, and cognitive trust[J]. Information & Management, 2021, 58(2): 103416. 27 Rihova I, Buhalis D, Moital M, et al. Social layers of customer-to-customer value co-creation[J]. Journal of Service Management, 2013, 24(5): 553-566. 28 张宁, 赵文斐, 庞智亮, 等. 企业开放式创新社区创意采纳影响因素研究——价值共创视角[J]. 科技进步与对策, 2021, 38(16): 91-100. 29 Ham J, Lee K, Kim T, et al. Subjective perception patterns of online reviews: a comparison of utilitarian and hedonic values[J]. Information Processing & Management, 2019, 56(4): 1439-1456. 30 蒋翠清, 宋凯伦, 丁勇, 等. 基于用户生成内容的潜在客户识别方法[J]. 数据分析与知识发现, 2018, 2(3): 1-8. 31 丁子轩, 俞雷, 张娟, 等. 基于深度残差自适应注意力网络的图像超分辨率重建[J]. 计算机工程, 2023, 49(5): 231-238. 32 Huang Z G. DHSEGATs: distance and hop-wise structures encoding enhanced graph attention networks[J]. Journal of Systems Engineering and Electronics, 2023, 34(2): 350-359. 33 Veli?kovi? P, Cucurull G, Casanova A, et al. Graph attention networks[C/OL]// Proceedings of the 6th International Conference on Learning Representations. Appleton: ICLR, 2018-02-16. https://openreview.net/pdf?id=rJXMpikCZ. 34 Wang J J, Xie H R, Wang F L, et al. Jointly modeling intra- and inter-session dependencies with graph neural networks for session-based recommendations[J]. Information Processing & Management, 2023, 60(2): 103209. 35 杨世刚, 刘勇国. 融合语料库特征与图注意力网络的短文本分类方法[J]. 计算机应用, 2022, 42(5): 1324-1329. 36 Zhao Y H, Da J W, Yan J Q. Detecting health misinformation in online health communities: incorporating behavioral features into machine learning based approaches[J]. Information Processing & Management, 2021, 58(1): 102390. 37 卢小宾, 张杨燚, 杨冠灿, 等. 新兴技术识别中的不均衡分类研究——基于代价敏感的随机森林算法[J]. 情报学报, 2022, 41(10): 1059-1070. 38 Daradkeh M. The relationship between persuasion cues and idea adoption in virtual crowdsourcing communities: evidence from a business analytics community[J]. International Journal of Knowledge Management, 2022, 18(1). DOI: 10.4018/IJKM.291708. 39 白彦壮, 郭蕾, 殷红春. 企业家精神驱动下自主知识产权品牌成长机制研究——以小米科技为例[J]. 科技进步与对策, 2015, 32(12): 79-85.
