期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

社会焦点透视镜系统——大数据视角下的舆情观测平台 被引量：4

Social event sensor: a public opinion platform from the big data perspective
下载PDF
导出
摘要 Web2.0时代的开启和社会媒体的不断发展,使得互联网上的数据规模呈爆炸性增长。网络大数据不仅为社会治理领域带来了新的契机,也对数据处理技术提出了巨大的挑战。构建了一个社会焦点透视镜系统,结合新浪微博数据,不仅能够实时提供每日的焦点事件及其情感分布展示,供舆情分析部门进行检测,还能够深层剖析焦点事件的情感分布原因和人群分布,协助社会治理领域进行策略的提出和实施。以"9·3阅兵"为例,呈现社会焦点透视镜系统深度剖析的结果展示。 The development of Web 2.0 and social media has led to the explosive growth of online user generated content. Big data brings a new opportunity for social governance, but also poses a great challenge for the data processing technology. A social event sensor system was constructed, which not only can automatically extract the daily hot events and their emotion distributions in real time for opinion monitoring, but also can deeply analyze the emotion distribution causations and the population distributions to help policy-making in social governance. Finally, one case study ＂9.3 Parade＂was showed to show the deeply analysis of social event sensor system.
作者 赵妍妍 秦兵 刘挺
机构地区 哈尔滨工业大学机电学院媒体技术与艺术系 哈尔滨工业大学计算机科学与技术学院社会计算与信息检索研究中心
出处 《大数据》 2016年第2期46-55,共10页 Big Data Research
基金 国家自然科学基金资助项目(No.61300113 No.61273321 No.61133012)~~
关键词 网络大数据 社会焦点透视镜 焦点事件抽取 情感分布 big Web data social event sensor hot event extraction sentiment distribution
分类号 TP391.1 [自动化与计算机技术—计算机应用技术]
  • 相关文献

参考文献10

  • 1ZHAO J C, DONG L, WU J J, et al. MoodLens: an emoticon-based sentiment analysis system for Chinese Tweets in Weibo[C]//The 18th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, August 12-16, 2012, Beijing, China. New York: ACM Press, 2012: 1528-1531.
  • 2WANG H, CAN D, KAZEMZADEH A, et al. A system for real-time Twitter sentiment analysis of 2012 U.S. presidential election cycle[C]//The ACL 2012 System Demonstrations, July 8-14, Jeju Island, Korea. New York: ACM Press, 2012: 115-120.
  • 3ClOT M, SONDEREGGER M, RUTHS D Gender inference of Twitter users in non- English contexts[C]//The 2013 Conference on Empirical Methods in Natural Language Processing, October 18-21 2013, Seattle, Washington, USA. Sofia Association for Computational Linguistics 2013:1136-1145.
  • 4DIAO Q M, JIANG J, ZHU F D, et al. Finding bursty topics from microblogs[C]//The 50th Annual Meeting of the Association for Computational Linguistics, July 8-14, Jeju Island, Korea. New York: ACM Press, 2012: 536-544.
  • 5WILLIAMS J, KATZ G Extracting and modeling durations for habits and events from Twitter[C]//The 50th Annual Meeting of the Association for Computational Linguistics, July 8-14, Jeju Island, Korea. New York: ACM Press, 2012: 223-227.
  • 6ZHAO Y Y, QIN B, LIU T, et al. Social sentiment sensor: a visualization system for topic detection and topic sentiment analysis on Microblog[J]. Multimedia Tools and Applications, 2014:1-18.
  • 7MOHAMMAD S M, KIRITCHENKO S, ZHU X D. NRC-Canada: building the state-of-the-art in sentiment analysis of Tweets[C]//The International Workshop on Semantic Evaluation, June 2013, Atlanta, USA. New York: Association for Computational Linguistics, 2013: 321-327.
  • 8SOCHER R, PERELYGIN A, Wu J, et al. Recursive deep models for semantic compositionality over a sentiment treebank[C]//The Conference on Empirical Methods in Natural Language Processing(EMNLP 2013), October 18-21, 2013, Seattle, WA, USA. Sofia: Association for Computational Linguistics, 2013: 1631-1642.
  • 9TANG D Y, WEI F R, YANG N, et al Learning sentiment-specific word embedding for Twitter sentiment classification[C]// The 52th Annual Meeting of the Association for Computational Linguistics (ACL 2014) June 22-27, 2014, Baltimore, MD, USA Baltimore: Association for Computational Linguistics, 2014:1555-1565.
  • 10ZHAO Y Y, QIN B, DONG Z J, et al. What causes different emotion distributions of a hot analysis 4th CCF event? A deep event-emotion system on microblogs[C]//The Conference on Natural LanguageProcessing & Chinese Computing(NLPCC 2015), October 9-13, 2015, Nanchang, China. Berlin: Springer, 2015: 453-464.

同被引文献41

引证文献4

二级引证文献20

大数据
2016年 第2期

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