[1]付 琳,张 媛.文本数据事件检测的研究热点及趋势分析[J].计算机技术与发展,2023,33(02):24-31.[doi:10. 3969 / j. issn. 1673-629X. 2023. 02. 004]
　FU Lin,ZHANG Yuan.Research Hotspots and Trend Analysis of Text Data Event Detection[J].,2023,33(02):24-31.[doi:10. 3969 / j. issn. 1673-629X. 2023. 02. 004]
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文本数据事件检测的研究热点及趋势分析()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年02期
页码:
24-31
栏目:
大数据与云计算
出版日期:
2023-02-10

文章信息/Info

Title:
Research Hotspots and Trend Analysis of Text Data Event Detection
文章编号:
1673-629X(2023)02-0024-08
作者:
付 琳; 张 媛
首都师范大学 管理学院,北京 100048
Author(s):
FU Lin; ZHANG Yuan
School of Management,Capital Normal University,Beijing 100048,China
关键词:
事件检测; CiteSpace; 研究热点; 研究趋势; 可视化分析
Keywords:
event detection; CiteSpace; research hotspot; research trends; visual analysis
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 02. 004
摘要:
随着科学技术的发展,人们发布信息、表达观点的渠道越来越多,且最常见的信息载体就是文本。 文本数据事件检测能够从海量数据中识别和检测当前正在发生的热点或突发事件,可以很好地支持应急管理、舆情监控、信息安全等领域的工作。 为了掌握文本数据事件检测的研究状况,揭示该领域的研究热点和发展趋势,该文以中国知网作为文献数据库,2003 年-2021 年的 440 篇期刊论文作为样本,借助科学计量软件 CiteSpace,从发文时间分布、基金支持、主要研究力量、主要刊载平台、高被引文献分布、研究热点以及演化路径等方面,对文本数据事件检测研究进行计量分析。 研究表明,事件检测研究发文量趋于稳定,且研究质量正在不断提高。 研究热点为突发事件与热点话题的文本事件检测应用研究、基于微博数据的事件检测研究和以聚类为主要方法的事件检测方法研究。 研究发展分为概念形成和工具开发两个阶段,并已经出现了领域扩散的现象。 现阶段的研究重点集中在事件检测技术,社交媒体事件检测和事件检测在突发事件中的应用等方面。 基于深度学习的文本数据检测方法、在社交媒体中的突发事件检测逐渐成为本领域研究的发展趋势。
Abstract:
With the development of science and technology,people have more and more channels to publish information and express theiropinions. The most common information carrier is text. Text data event detection identifies and detects hot or unexpected events that arecurrently occurring from massive amounts of data,and it can well support emergency management,public opinion monitoring,informationsecurity and other fields. In order to grasp the research status of text data event detection and reveal the research hotspots anddevelopment trends in this field,we use CNKI as a literature database,440 journal articles from 2003 - 2021 as a sample,econometricanalysis of text data event detection research in terms of distribution of publication time,funding support,major research power,majorpublication platforms,distribution of highly cited literature,research hotspots and evolutionary paths. The results show that the number ofevent detection research publications is stabilizing and the quality of research is improving. The research hotspots are the applicationresearch of text event detection for breaking news and hot topics,research on event detection based on twitter data and research on eventdetection method based on clustering. Research development is divided into two phases:concept formation and tool development,anddomain proliferation has already occurred. At this stage,the research focus is divided into three categories,event detection technology,event detection research in social media and event detection research in emergent events. Text data detection methods based on deeplearning and emergency detection in social media have gradually become the development trend of this field.

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[1]赵晓芳 刘智勇.基于支持向量数据描述的高速公路事件检测[J].计算机技术与发展,2008,(12):248.
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[3]王冰玉,吴振宇,沈苏彬,等.社交媒体事件检测研究综述[J].计算机技术与发展,2018,28(09):105.[doi:10．3969/j．issn．1673－629X．2018．09．022]
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更新日期/Last Update: 2023-02-10