详细信息
从浏览到回答:注意力分配视角下问答社区流量转化的组态研究
From Browsing to Answering: A Configurational Analysis of Traffic Conversion in Q&A Community from the Perspective of Attention Distribution
文献类型:期刊文献
中文题名:从浏览到回答:注意力分配视角下问答社区流量转化的组态研究
英文题名:From Browsing to Answering: A Configurational Analysis of Traffic Conversion in Q&A Community from the Perspective of Attention Distribution
作者:仇姝懿[1];马玲[1]
机构:[1]华东理工大学商学院,上海200237
年份:2024
卷号:14
期号:1
起止页码:84
中文期刊名:信息资源管理学报
外文期刊名:Journal of Information Resources Management
收录:国家哲学社会科学学术期刊数据库;CSSCI:【CSSCI2023_2024】;
语种:中文
中文关键词:问答社区;流量转化;注意力分配;内源性注意;外源性注意;模糊集定性比较分析(fsQCA)
外文关键词:Q&A community;Traffic conversion;Attention distribution;Endogenous attention;Exogenous attention;Fuzzy-set qualitative comparative analysis(fsQCA)
摘要:促进从问题浏览到作答的流量转化对问答社区至关重要。本研究将流量转化视为由问答界面信息线索协同作用的多要素并发过程,以知乎的2085条问题为样本,应用模糊集定性比较分析,从注意力分配视角对问答社区的流量转化进行组态研究,并辅以回归分析。研究发现,高流量转化率问题的组态路径包括低作答竞争-高社会关注刺激与低作答竞争-强社会影响刺激的高可读性问题,与非高流量转化率问题的组态路径并非完全因果对称;知识结构化程度不同的问题实现流量转化的组态存在差异。研究解释问答社区用户从浏览向作答转化过程中的注意力分配,揭示从浏览到回答的流量转化机制,有助于促进知识分享平台流量转化,优化问答界面设计。
Traffic conversion from question browsing to answering is of great significance to Q&A community.It is regarded as a multi-factor concurrent process of the synergy of information clues within the Q&A interface.Employing fuzzy-set qualitative comparative analysis,this study examines 2,085 questions from Zhihu to explore how traffic conversion in the Q&A community can be facilitated,with supplementary insights from regression analysis.The findings reveal that the configuration path of high traffic conversion rate includes readable question type of"low competition-high social concern"and"low competition-strong social influence".Conversely,the configuration path for non-high traffic conversion rates is causal asymmetry.Furthermore,the configuration paths of high traffic conversion are different for questions with different degrees of knowledge structure.These findings elucidate the user attention distribution in Q&A communities during the transition from browsers to answerers and reveal the mechanisms of traffic conversion,which helps to facilitate traffic conversion of knowledge sharing platform and optimize the Q&A interface design.
参考文献:
正在载入数据...
