文本情感可视分析技术及其在人文领域的应用

张伶俐; 褚琦凯; 王桂娟; 张巍瀚; 蒲慧; 宋振金; 吴亚东

doi:10.11959/j.issn.2096-0271.2022050

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文本情感可视分析技术及其在人文领域的应用

专题：面向人文领域的大数据技术和方法 | 更新时间：2024-06-03

- 文本情感可视分析技术及其在人文领域的应用
- Text sentiment visual analysis technology and its application in humanities
- 大数据 2022年8卷第6期页码：56-73
- 作者机构：
  
  1. 四川轻化工大学计算机科学与工程学院，四川自贡 643000
  2. 四川轻化工大学自动化与信息工程学院，四川自贡 643000
  3. 西南科技大学计算机科学与技术学院，四川绵阳 621000
  4. 西南科技大学计算机信息工程学院，四川绵阳 621000
- 作者简介：
  
  [ "张伶俐（1998- ），女，四川轻化工大学计算机科学与工程学院硕士生，主要研究方向为可视化与可视分析、自然语言处理等" ]
  [ "褚琦凯（1996- ），男，四川轻化工大学自动化与信息工程学院硕士生，主要研究方向为可视化与可视分析等" ]
  [ "王桂娟（1981- ），女，西南科技大学计算机科学与技术学院教师，西南科技大学信息工程学院博士生，主要研究方向为城市可视化、自动可视化" ]
  [ "张巍瀚(1994- )，男，四川轻化工大学计算机科学与工程学院助教，主要研究方向为人机交互、数据可视化与可视分析" ]
  [ "蒲慧（1997- ），女，四川轻化工大学计算机科学与工程学院硕士生，主要研究方向为可视化与可视分析、大数据分析与处理、深度学习" ]
  [ "宋振金（1997- ），男，四川轻化工大学计算机科学与工程学院硕士生，主要研究方向为可视化与可视分析、大数据分析与处理、机器学习" ]
  [ "吴亚东（1979- ），男，博士，四川轻化工大学计算机科学与工程学院教授、博士生导师，主要研究方向为可视化、可视分析、人机交互、虚拟现实" ]
- 基金信息：
  
  四川轻化工大学人才引进项目;Talent Introduction Project of Sichuan University of Science and Engineering(2020RC20)
- DOI：10.11959/j.issn.2096-0271.2022050
  中图分类号： TP311
- 网络首发：2022-11，
  
  纸质出版：2022-11-15
- 稿件说明：
移动端阅览
张伶俐, 褚琦凯, 王桂娟, 等. 文本情感可视分析技术及其在人文领域的应用[J]. 大数据, 2022,8(6):56-73.

Lingli ZHANG, Qikai CHU, Guijuan WANG, et al. Text sentiment visual analysis technology and its application in humanities[J]. Big data research, 2022, 8(6): 56-73.
张伶俐, 褚琦凯, 王桂娟, 等. 文本情感可视分析技术及其在人文领域的应用[J]. 大数据, 2022,8(6):56-73. DOI： 10.11959/j.issn.2096-0271.2022050.

Lingli ZHANG, Qikai CHU, Guijuan WANG, et al. Text sentiment visual analysis technology and its application in humanities[J]. Big data research, 2022, 8(6): 56-73. DOI： 10.11959/j.issn.2096-0271.2022050.

摘要

情感分析是对信息情感倾向的挖掘，主要用于舆情监测、商品评论分析以及信息检索等方面。随着社交媒体的快速发展，文本数据量呈现爆炸性增长，文本情感分析成为自然语言处理领域重要的研究热点之一。与此同时，由于情感数据具有海量、时变、非结构性、强关联性的特点，能够直观高效地呈现情感倾向的可视分析技术在这个领域得到广泛应用。回顾了近年来的情感可视分析研究，从表现形式——“主题词”“关联”“演变”“时空分布”4个方面阐述文本情感可视分析方法，并对未来情感分析技术及文本情感可视分析研究进行展望。

Abstract

Sentiment analysis is the mining of information sentiment tendency

which is mainly used for public opinion monitoring

commodity review analysis

and information retrieval.With the rapid development of social media

the volume of text data has shown explosive growth

and text sentiment analysis has become one of the important research hotspots in the field of natural language processing.At the same time

due to the characteristics of massive

time-varying

unstructured and strongly correlated sentiment data

visual analysis techniques that can present sentiment tendencies intuitively and efficiently are widely used in this field.The recent research on visual analysis of sentiment was reviewed

and according to the presentation form “topic words”

“association”

“evolution”

“spatial and temporal distribution” four aspects of text sentiment visual analysis methods were described

and future sentiment analysis techniques as well as text sentiment visual analysis research were foreseen.

关键词

Keywords

references

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