基于知识行为的小米社区用户画像研究

doi:10.13998/j.cnki.issn1002-1248.20-1121

摘要/Abstract

摘要： [目的/意义]通过研究小米虚拟社区的用户画像,构建不同类型用户画像模型,深入研究小米社区中具有知识创新性的用户画像,探索用户在虚拟社区中的知识行为。[方法/过程]结合自然语言处理方法,选择了小米社区内较为活跃的用户发帖和评论文本数据,分析了小米社区用户画像及其典型特征,揭示了每类用户的特征和知识行为,探究用户之间的信息交流和知识交互过程。[结果/结论]研究发现,小米社区用户可以分为5类,分别是故障反馈用户、评论解答用户、社交用户、咨询用户、建议用户,对每类用户分别进行用户画像分析。最后,针对不同用户提出一些可实施的建议,以便于社区管理人员对这部分用户的知识行为进行更有针对性的维护和引导。

关键词: 用户画像, 小米社区, 知识行为, 活动理论, 信息行为

Abstract: [Purpose/Significance] By studying the user profiles of the Xiaomi virtual community, this paper constructs different types of user profile models, deeply studies the user profiles with knowledge innovation in the Xiaomi community, and explores the knowledge behavior of such users in the virtual community. [Method/Process] Combined with the natural language processing method, this paper selects the more active user posts and comments in the Xiaomi community, analyzes the user profiles and typical characteristics in the Xiaomi community, specifically the characteristics and knowledge behavior of each type of user, and explores the information exchange and knowledge interaction process between users. [Results/Conclusions] The study found that users in the Xiaomi community can be divided into five categories: fault feedback users, comment answering users, social users, consulting users and suggestion users. The user profiles of each category were analyzed. Finally, the paper puts forward some feasible suggestions for different users, so as to facilitate the community managers to maintain and guide the knowledge behavior of these users.

Key words: user profile, Xiaomi community, knowledge behavior, activity theory, information behavior

中图分类号:

G203

李旭光, 肖思琪, 李珊珊, 张恒. 基于知识行为的小米社区用户画像研究[J]. 农业图书情报学报, 2021, 33(8): 4-12.

LI Xuguang, XIAO Siqi, LI Shanshan, ZHANG Heng. Research on User Profiles of Xiaomi Community Based on Knowledge Behavior[J]. Journal of Library and Information Science in Agriculture, 2021, 33(8): 4-12.

参考文献

[1] 梁荣贤. 基于用户画像的图书馆精准信息服务研究[J]. 图书馆工作与研究, 2019(4): 65-69.
LIANG R X.Research on library precision information service based on user portrait[J]. Library work and research, 2019(4): 65-69.
[2] 杨帆. 画像分析为基础的图书馆大数据实践——以国家图书馆大数据项目为例[J]. 图书馆论坛, 2019, 39(2): 58-64.
YANG F.Practice of library big data based on portrait analysis-Taking big data project of National Library of China as an example[J]. Library forum, 2019, 39(2): 58-64.
[3] 宋美琦, 陈烨, 张瑞. 用户画像研究述评[J]. 情报科学, 2019, 37(4): 171-177.
SONG M Q, CHEN Y, ZHANG R.Review of user portrait research[J]. Information science, 2019, 37(4): 171-177.
[4] YAO W, HOU Q, WANG J, et al.A personalized recommendation system based on user portrait[C]//The 2019 international conference, 2019.
[5] YUAN H, NING M.User modeling of digital library knowledge community based on user portrait[J]. Library theory and practice, 2017.
[6] 高广尚. 用户画像构建方法研究综述[J]. 数据分析与知识发现, 2019, 3(3): 25-35.
GAO G S.A review of the methods of user portrait construction[J]. Data analysis and knowledge discovery, 2019, 3(3): 25-35.
[7] 单轸, 邵波. 国内图书馆领域用户画像研究的冷思考: 困境与出路[J]. 图书馆学研究, 2019(5): 8-13, 30.
SHAN Z, SHAO B.Cold thinking on the research of user portrait in the field of library in China: Dilemma and outlet[J]. Library science research, 2019(5): 8-13, 30.
[8] 张海涛, 崔阳, 王丹, 等. 基于概念格的在线健康社区用户画像研究[J]. 情报学报, 2018, 37(9): 912-922.
ZHANG H T, CUI Y, WANG D, et al.Research on user portrait of online health community based on concept lattice[J]. Journal of the China society for scientific and technical information, 2018, 37(9): 912-922.
[9] 张艳丰, 彭丽徽, 刘金承, 等. 新媒体环境下移动社交媒体倦怠用户画像实证研究——基于SSO理论的因果关系视角[J]. 情报学报, 2019, 38(10): 1092-1101.
ZHANG Y F, PENG L H, LIU J C, et al.An empirical study on burnout user portraits of mobile social media in the new media environment - From the perspective of causality based on SSO theory[J]. Journal of the China society for scientific and technical information, 2019, 38(10): 1092-1101.
[10] 赵辉, 化柏林, 何鸿魏. 科技情报用户画像标签生成与推荐[J]. 情报学报, 2020, 39(11): 1214-1222.
ZHAO H, HUA B L, HE H W.Generation and recommendation of user portrait tags of scientific and technological information[J].Journal of the China society for scientific and technical information, 2020, 39(11): 1214-1222.
[11] 许鹏程, 毕强, 张晗, 等. 数据驱动下数字图书馆用户画像模型构建[J]. 图书情报工作, 2019, 63(3): 30-37.
XU P C, BI Q, ZHANG H, et al.User portrait model construction of digital library under data driven[J]. Library and information work,2019, 63(3): 30-37.
[12] 刘海鸥, 姚苏梅, 黄文娜, 等. 基于用户画像的图书馆大数据知识服务情境化推荐[J]. 图书馆学研究, 2018(24): 57-63, 32.
LIU H O, YAO S M, HUANG W N, et al.Situational recommendation of library big data knowledge service based on user portrait[J]. Library science research, 2018(24): 57-63, 32.
[13] 何娟. 基于用户个人及群体画像相结合的图书个性化推荐应用研究[J]. 情报理论与实践, 2019, 42(1): 129-133, 160.
HE J.Research on the application of personalized book recommen-dation based on user's personal and group portraits[J]. Information theory and practice, 2019, 42(1): 129-133, 160.
[14] 刘速. 浅议数字图书馆知识发现系统中的用户画像——以天津图书馆为例[J]. 图书馆理论与实践, 2017(6): 103-106.
LIU S.User portraits in knowledge discovery system of digital library - Taking Tianjin library as an example[J]. Library theory and practice, 2017(6): 103-106.
[15] 周文博. 活动理论及其在图书馆情报学领域的应用[J]. 情报学报, 2020, 39(3): 274-283.
ZHOU W B.Activity theory and its application in Library and Information Science[J]. Journal of information science, 2020, 39(3): 274-283.
[16] 刘春玲. 基于活动理论的智慧教育案例研究[J]. 新课程, 2020(40): 123.
LIU C L.Case study of smart education based on activity theory[J]. New curriculum, 2020(40): 123.
[17] 王若亭. 活动理论视角下高校图书馆社会服务理论模型构建要素研究[J]. 造纸装备及材料, 2020, 49(4): 85-86.
WANG R T.Research on the construction elements of social service theoretical model of university library from the perspective of activity theory[J]. Paper making equipment and materials, 2020, 49(4): 85-86.
[18] TORAL S L, MARTíNEZ-TORRES M R, BARRERO F. Analysis of virtual communities supporting OSS projects using social network analysis[J]. Information and software technology, 2010, 52(3): 296-303.
[19] BAGOZZI R P, DHOLAKIA U M.Open source software user communities: A study of participation in Linux user groups[M]. Maryland: Informs, 2006.
[20] 谷斌, 徐菁, 黄家良. 专业虚拟社区用户分类模型研究[J]. 情报杂志, 2014, 33(5): 203-207.
GU B, XU J, HUANG J L.Research on user classification model of professional virtual community[J]. Journal of information, 2014, 33(5): 203-207.
[21] 元丛, 吴俊. 用户画像概念溯源与应用场景研究[J]. 重庆交通大学学报(社会科学版), 2017, 17(5): 82-87.
YUAN C, WU J. research on concept traceability and application scenarios of user portrait[J]. Journal of Chongqing Jiaotong university (social science edition), 2017, 17(5): 82-87.
[22] 赵雅慧, 刘芳霖, 罗琳. 大数据背景下的用户画像研究综述: 知识体系与研究展望[J]. 图书馆学研究, 2019(24): 13-24.
ZHAO Y H, LIU F L, LUO L.Review of user portraits in the context of big data: Knowledge system and research prospects[J]. Library science research, 2019(24): 13-24.
[23] 杨双亮. 用户画像在内容推送的研究与应用[D]. 北京: 北方工业大学, 2017.
YANG S L.Research and application of user portrait in content push[D]. Beijing: North China university of technology, 2017.
[24] 沈波, 胡云发. 基于用户行为特征的虚拟品牌社区用户分类研究[J]. 情报探索, 2018(7): 12-18.
SHEN B, HU Y F.User classification of virtual brand community based on user behavior characteristics[J]. Intelligence exploration, 2018(7): 12-18.
[25] 刘伟, 丁志慧. 基于参与行为的兴趣型虚拟社区成员分类研究[J]. 商业研究, 2012(11): 92-95.
LIU W, DING Z H.Research on the classification of interest based virtual community members based on participation behavior[J].
26 Business research, 2012(11): 92-95.