[1] 王臻皇, 陈思明, 袁晓如. 面向微博主题的可视分析研究[J]. 软件学报, 2018, 29(4):1115-1130.
[2] BEX R T, LUNDGREN L, CRIPPEN K J. Scientific Twitter:the flow of paleontological communication across a topic network[J/OL]. PLoS one, 2019, 14(7).[2021-05-06]. http://doi.org/10.1371/journal.pone.0219688.
[3] BOKAETF M H, SAMETI H, LIU Y. Unsupervised approach to extract summary keywords in meeting domain[C]//DUGELAY J L, SLOCK D. Proceedings of the 23rd European signal processing conference. Piscataway:IEEE, 2015:1406-1410.
[4] CHEN Y H, LU J L, MENG F T. Finding keywords in blogs:efficient keyword extraction in blog mining via user behaviors[J]. Expert systems with applications, 2014, 41(2):663-670.
[5] 谷莹, 李贺, 李叶叶, 等. 基于在线评论的企业竞争情报需求挖掘研究[J]. 现代情报, 2021, 41(1):24-31.
[6] 安璐, 李倩. 基于热点主题识别的突发事件次生衍生事件探测[J]. 情报资料工作, 2020, 41(6):26-35.
[7] ZHANG Y H, MAO W J, ZENG D, et al. Topic evolution modeling in social media short texts based on recurrent semantic dependent CRP[C]//BENJAMIN V, LI W F. Proceedings of 2017 IEEE international conference on intelligence and security informatics. Piscataway:IEEE.2017:119-124.
[8] 廖海涵, 王曰芬, 关鹏. 微博舆情传播周期中不同传播者的主题挖掘与观点识别[J]. 图书情报工作, 2018, 62(19):77-85.
[9] 梁晓贺, 田儒雅, 吴蕾, 等. 微博主题发现研究方法述评[J]. 图书情报工作, 2017, 61(14):141-148.
[10] 梁晓贺, 田儒雅, 吴蕾, 等. 基于超网络的微博相似度及其在微博舆情主题发现中的应用[J]. 图书情报工作, 2020, 64(11):77-86.
[11] SASAKI K, YISHIKAWA T, FURUHASHI T. Online topic model for Twitter considering dynamics of user Interests and topic trends[C]//MARTON Y. Proceedings of 2014 conference on empirical methods in natural language processing. Stroudsburg:ACL, 2014:1977-1985.
[12] LIU Y P, PENG H, LI J X, et al. Event detection and evolution in multi-lingual social streams[J/OL]. Frontiers of computer science, 2020, 14(5).[2021-05-06]. http://doi.org/10.1007/s11704-019-8201-6.
[13] DEHGHANI N, ASADPOUR M. SGSG:semantic graph-based storyline generation in Twitter[J]. Journal of information science, 2019, 45(3):304-321.
[14] GOYAL P, KAUSHIK P, GUPTA P, et al. Multilevel event detection, storyline generation, and summarization for Tweet streams[J]. IEEE transactions on computational social systems, 2020, 7(1):8-23.
[15] HUANG J J, PENG M, WANG H, et al. A probabilistic method for emerging topic tracking in microblog stream[J]. World Wide Web, 2017, 20(2):325-350.
[16] CAI H Y, HUANG Z, SRIVASTAVA D, et al. Indexing evolving events from Tweet streams[J]. IEEE transactions on knowledge and data engineering, 2015, 27(11):3001-3015.
[17] ABULAISH M, FAZIL M. Modeling topic evolution in Twitter:an embedding-based approach[J/OL]. IEEE access, 2018, 6.[2021-05-06]. http://doi.org/10.1109/ACCESS.2018.2878494.
[18] PRUSS D, FUJINUMA Y, DAUGHTON AR, et al. Zika discourse in the Americas:a multilingual topic analysis of Twitter[J/OL]. Plos one, 2019, 14(5).[2021-05-06]. http://doi.org/10.1371/journal.pone.0216922.
[19] 王臻皇, 陈思明, 袁晓如. 面向微博主题的可视分析研究[J]. 软件学报, 2018, 29(4):1115-1130.
[20] 刘雅姝, 张海涛, 徐海玲, 等. 多维特征融合的网络舆情突发事件演化话题图谱研究[J]. 情报学报, 2019, 38(8):798-806.
[21] SACKS H, SCHEGLOFF E A, JEFFORSON G. Simplest systematics for the organization of turn-talking for conversation[J]. Language, 1974, 50(4):696-735.
[22] 吴亚欣, 于国栋. 为会话分析正名[J]. 山西大学学报(哲学社会科学版), 2017, 40(1):85-90.
[23] 赵焱, 张旗伟, 徐蕊, 等. 超语及认同建构作为双语者的学习手段[J]. 现代外语, 2021(2):258-270.
[24] STOMMEL W, VAN GOOR H, SYOMMEL M. Other-attentiveness in video consultation openings:a conversation analysis of video-mediated versus face-to-face consultations[J]. Journal of computer-mediated communication, 2019, 24(6):275-292.
[25] AVISON D, BANKS P. Cross-cultural (mis)communication in IS offshoring:understanding through conversation analysis[J]. Journal of information technology, 2008, 23(4):249-268.
[26] 吴亚欣, 刘蜀. 请求行为之微妙性的序列组织研究[J]. 现代外语, 2020, 43(1):32-43.
[27] 彭欣, 张惟. 日常交谈中故事讲述的会话分析[J]. 山西大学学报(哲学社会科学版), 2019, 42(4):137-144.
[28] 卢恒, 张向先, 张莉曼, 等. 会话分析视角下虚拟学术社区用户交互行为特征研究[J]. 图书情报工作, 2020, 64(13):80-89.
[29] 巴志超, 李纲, 毛进, 等.微信群内部信息交流的网络结构、行为及其演化分析——基于会话分析视角[J]. 情报学报, 2018, 37(10):1009-1021.
[30] GU Y, LI X Y, HUANG K X, et al. Human conversation analysis using attentive multimodal networks with hierarchical encoder-decoder[C]//ACM. Proceedings of the 26th ACM multimedia conference. New York:ACM, 2018:537-545.
[31] HOUSLEY W, ALBERT S, STOKOE E. Natural action processing:conversation analysis and big interactional data[C]//ACM. Proceedings of the halfway to the future symposium. New York:ACM, 2019:1-4.
[32] KONO S, AIHARA K. Prototype of decision support based on estimation of group status using conversation analysis[C]//YAMAMOTO S. Proceedings of the 18th international conference on human-computer interaction. Berlin:Springer, 2016:40-49.
[33] 张星, 魏淑芬, 王莉, 等. 危机事件中的微博意见领袖影响因素实证研究[J]. 情报学报, 2015, 34(1):66-75.
[34] CUI L, PI D C. Identification of micro-blog opinion leaders based on user features and outbreak nodes[J]. International journal of emerging technologies in learning, 2017, 12(1):141-154.
[35] 安璐, 胡俊阳, 李纲. 突发事件情境下社交媒体高影响力用户画像研究[J]. 情报资料工作, 2020, 41(6):6-16.
[36] 郭晓利, 周自岚, 刘耀伟, 等. 基于DTS-ILDA模型和关联过滤的新闻话题演化分析[J]. 应用科学学报, 2017, 35(5):634-646.