期刊文献+

网络健康社区中的主题特征研究 被引量:48

Research on Theme Features in Online Health Community
原文传递
导出
摘要 [目的/意义]探究不同类型网络社区中健康主题特征分布,促使各网站平台能够更好地提供在线健康信息服务。[方法/过程]以糖尿病为例,选取来自健康论坛的社会化标签和社会化问答社区的问答记录作为研究对象;通过数据编码和文本处理的方法,得到八大类主题,并比较两种网络社区中该八大主题分布情况的异同。[结果/结论]两种网络社区中糖尿病主题冷热分布大体趋于一致。在最为用户所关注的主题上,两类社区各有侧重,分别是"诊断和检查"、"社会生活"。以上探讨和发现对在线健康信息服务质量的提升有诸多启示。 [ Purpose/significance] This paper aims to explore health themes features distribution in different types of online community, and prompt websites to provide better online health information services. [ Method/process ] Taking Dia- betes as an example, this paper chooses the social tags from health forums and the Q&A records from social Q&A platforms as the research object. It gets eight themes by the methods of data coding and text processing, and compares the similarities and differences of the distribution of eight major themes in two kinds of online health communities. [ Result/conclusion] The result shows that the distribution of the hot or cold themes from two online communities tend to be consistent, but the theme in most concern differs from each other. All these finds are benefit to improve online health information service.
作者 金碧漪 许鑫
出处 《图书情报工作》 CSSCI 北大核心 2015年第12期100-105,共6页 Library and Information Service
关键词 论坛社区 社会化问答社区 健康信息服务 健康主题 糖尿病 forum social Q&A platform health information service health theme diabetes
  • 相关文献

参考文献22

  • 1Fox S. The social life of health information, 2011 [ EB/OL]. [ 2014 - 06 - 20]. http ://www. pewinternet, org/2011/05/12/ the - social - life - of - health - information - 2011/.
  • 2Arden M A, Duxbury A M S, Soltani H. Responses to gestational weight management guidance: A thematic analysis of comments made by women in online parenting forums[ J/OL]. [2015 -03 - 10 ]. http ://www. biomedcentral, com/1471 - 2393/14/216.
  • 3Coulson N S. Sharing, supporting and sobriety: A qualitative anal- ysis of messages posted to alcohol - related online discussion fo- rums in the United Kingdom [ J ]. Journal of Substance Use, 2014, 19(1 -2) : 176 -180.
  • 4Attard A, Coulson N S. A thematic analysis of patient communica- tion in Parkinson' s disease online support group discussion forums [J]. Computers in Human Behavior, 2012, 28(2) : 500 -506.
  • 5Rodgers S, Chen Qimei. Intemet community group participation: Psychosocial benefits for women with breast cancer[ J/OL]. [ 2015 -03 - 10 ]. http://onlinelibrary, wiley, com/doi/10. 1111/j. 1083 - 6101. 2005. tb00268, x/full.
  • 6Zhang Yang. Contextualizing consumer health information search- ing: An analysis of questions in a social Q&A community[ C/OL]. [2015 -04 -02]. http://dl, acre. org/citation, cfm? id = 1883023.
  • 7Chiu M H P, Wu C C. Integrated ACE model for consumer health information needs: A content analysis of questions in Yahoo! An- swers [ J ]. Proceedings of the American Society for Information Science and Technology, 2012, 49( 1 ) : 1 -10.
  • 8Oh J S, He D, Jeng W, et al. Linguistic characteristics of eating disorder questions on Yahoo ! Answers - Content, style, and emo- tion[ J]. Proceedings of the American Society for Information Sci- ence and Technology, 2013, 50 ( 1 ) : 1 - 10.
  • 9Zhang Jin, Zhao Yiming. A user term visualization analysis based on a social question and answer log[ J ]. Information Processing & Management, 2013, 49 (5) : 1019 - 1048.
  • 10Griffiths T L, Steyvers M. Finding scientific topics [ J ]. Proceed- ings of the National Academy of Sciences, 2004, 101 ( suppl 1 ) : 5228 - 5235.

二级参考文献64

  • 1安璐,李纲.基于自组织映射的期刊主题可视化组织[J].情报学报,2011,30(2):183-191. 被引量:3
  • 2朱靖波,叶娜,罗海涛.基于多元判别分析的文本分割模型[J].软件学报,2007,18(3):555-564. 被引量:15
  • 3石晶,戴国忠.基于PLSA模型的文本分割[J].计算机研究与发展,2007,44(2):242-248. 被引量:25
  • 4Kehagias A, Nicolaou A, Petridis V, Fragkou P. Text segmentation by product partition models and dynamic programming. Mathematical and Computer Modeling, 2004, 39(2-3): 209-217.
  • 5Gina-Anne L. Prosody-based topic segmentation for mandarin broadcast news. In: Proceedings of the 9th American Chapter of the Association for Computational Linguistics- Human Language Technologies. Boston, USA: Association for Computational Linguistics, 2004. 137-140.
  • 6Olivier F. Using collocations for topic segmentation and link detection. In: Proceedings of the 19th International Conference on Computational Linguistics. Taipei, China: Association for Computational Linguistics, 2002. 1-7.
  • 7Li H, Yamanishi K. Topic analysis using a finite mixture model. Information Processing and Management, 2003, 39(4): 521-541.
  • 8Hofmann T. Probabilistic latent semantic analysis. In: Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence. Stockholm, Sweden: Morgan Kaufmann, 1999. 289-296.
  • 9Blei D M, Ng A Y, Jordan M I. Latent dirichlet allocation. Journal of Machine Learning Research, 2003, 3:993-]022.
  • 10Steyvers M, Griffiths T. Probabilistic topic models. Handbook of Latent Semantic Analysis. New Jersey: Springer, 2007.

共引文献245

同被引文献510

引证文献48

二级引证文献459

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部