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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (5): 77-87    DOI: 10.11925/infotech.2096-3467.2017.1316
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Review of Online Sentiment Visualization Techniques
Yang Sinan1, Xu Jian1(), Ye Pingping2
1 School of Information Management, Sun Yat-Sen University, Guangzhou 510006, China
2 Shenzhen LEXIN Holdings Limited, Shenzhen 518000, China
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Abstract  

[Objective] The paper reviews the main techniques for sentiment analysis of online reviews, and then discusses their major development trends. [Methods] First, we surveyed relevant scientific literature on sentiment analysis of web reviews published in recent years. Then, we summarized the characteristics of visualization methods and analyzed features of visualization tools. [Results] We could visualize the sentiment of web reviews from the perspectives of contents, space-time, and topics. The visualization tools include static, interactive and programming ones. [Conclusions] This paper reviews the major methods and tools for online contents visualization and indicates three major development trends. It could promote the progress of future research and new visualization tools.

Key wordsSentiment Visualization      Sentiment Analysis      Visualization Tools     
Received: 25 December 2017      Published: 20 June 2018
ZTFLH:  G350  

Cite this article:

Yang Sinan,Xu Jian,Ye Pingping. Review of Online Sentiment Visualization Techniques. Data Analysis and Knowledge Discovery, 2018, 2(5): 77-87.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1316     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I5/77

分类 数据模型 可视化技术
词汇层次 词袋、N-Gram、
词频向量
词云图、散点图、气泡图、雷达图等
句法层次 树图模型 单词树图、网络图
语义层次 面向网络数据模型 TextFlow[10]、网络图
多面实体关系数据模型 桑基图、主题河流图、
IN-SPIRE[11]
数据可视化类别 关键任务 主要特点 相关工具
静态可视化类 进行数据静态呈现, 使数据具有
更强的可读性
快速、图表资源丰富、应用广 Excel、iCharts、Wordle、Tableau、
Visually等
交互式可视化类 实现交互功能, 使数据更加生动 界面与数据融为一体, 同步更新 Crossfilter、D3、Prefuse、EChart、
Many Eyes等
支持编程可视化类 处理大规模数据 同时满足数据分析和可视化需求 Weka、R、Processing、Google Chart、
iCharts[38]
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