SocialHelix: visual analysis of sentiment divergence in social media

Nan Cao; Lu Lu; Yu-Ru Lin; Fei Wang; Zhen Wen

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SocialHelix: visual analysis of sentiment divergence in social media

机译：SocialHelix：社交媒体中情感差异的可视化分析

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Social media allow people to express and promote different opinions, on which people's sentiments to a subject often diverge when their opinions conflict. An intuitive visualization that unfolds the process of sentiment divergence from the rich and massive social media data will have far-reaching impact on various domains including social science, politics and economics. In this paper, we propose a visual analysis system, SocialHelix, to achieve this goal. SocialHelix is a novel visual design which enables the users to detect and trace topics and events occurring in social media, and to understand when and why divergences occurred and how they evolved among different social groups. We demonstrate the effectiveness and usefulness of SocialHelix by conducting in-depth case studies on tweets related to the national political debates.

机译：社交媒体允许人们表达和促进不同的观点，当他们的观点发生冲突时，人们对主题的看法往往会有所不同。直观的可视化展现了情感与丰富而庞大的社交媒体数据之间的分歧过程，将对包括社会科学，政治和经济学在内的各个领域产生深远影响。在本文中，我们提出了一种视觉分析系统SocialHelix，以实现此目标。 SocialHelix是一种新颖的视觉设计，使用户能够检测和跟踪社交媒体中发生的主题和事件，并了解何时，为什么发生分歧以及分歧如何在不同的社会群体中发生。通过对与国家政治辩论有关的推文进行深入的案例研究，我们证明了SocialHelix的有效性和有用性。

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来源
《Journal of visualization》 |2015年第2期|221-235|共15页
作者
Nan Cao; Lu Lu; Yu-Ru Lin; Fei Wang; Zhen Wen;
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作者单位

IBM T. J. Watson Research Center, Yorktown Heights, USA;

Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong;

School of Information Science, University of Pittsburgh, Pittsburgh, USA;

Department of Computer Science and Engineering, University of Connecticut, Storrs, USA;

IBM T. J. Watson Research Center, Yorktown Heights, USA;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Information visualization; Social media;

机译：信息可视化;社交媒体;

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SocialHelix: visual analysis of sentiment divergence in social media

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