基于用户信息需求分析的学术社交网络功能优化策略研究

Optimization Strategies for Academic Social Network Functions Based on User Information Demands Analysis

厘清学术社交网络用户信息需求层次,对照国内外主流学术社交网络平台功能与需求匹配差异,优化学术社交网络服务功能,对促进学术交流与合作具有重要意义。首先,通过访谈法获取学术社交网络用户信息需求,结合LDA主题模型形成10个信息需求要素;其次,基于Kano模型设计问卷并调查,界定信息需求要素的类别。研究结果表明,科研协同、多元化平台、社交网络和文献获取为期望型需求要素,学术评价和交流互动为必备型需求要素,写作投稿和自我展示为无差别型需求要素,激励机制和项目申报属于魅力型需求要素。据此,根据不同的需求要素类型及主流学术社交网络平台功能,针对性提出我国学术社交网络优化策略,以更好地服务于科研人员学术交流与创新。

It is of great significance for promoting academic exchanges and cooperation to clarify the level of information demands of users of academic social network(ASN),compare the function and demand matching differences of mainstream ASN at home and abroad,and optimize the service functions of ASN accordingly.This paper obtains the information demands of the users of ASN through interviews,and forms 10 elements of information demands combined with the LDA topic model.Secondly,based on Kano model,questionnaires are designed and investigated to define the categories of information demand elements.The results show that research collaboration,diversified platform,social network,and literature acquisition are performance demand elements.Academic evaluation and communication and interaction are must-be demand elements.Writing and submission and self-presentation are indifferent demand elements.Incentive mechanism and project application are attractive demand elements.According to different types of demand elements and mainstream ASN functions,the optimization strategies for ASN in China are put forward to better serve the academic exchange and innovation of researchers.