A Method for Analyzing Influence of Emotions of Posts in SNS Conversations

Marina Fujita, J. Watanabe, Kentaro Kawamoto, Tomoaki Akitomi, Koji Ara
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引用次数: 5

Abstract

We devised a method for analyzing communication, which focuses on influences between two sequential posts in a conversation on a social-network service (SNS). Posts expressed on an SNS are classified into three emotions: positive, negative, or neutral. Two influences were analyzed: the emotion of a person's preceding post on the emotion of a post from another person, and the emotion of a person's post on the emotion of a subsequent post from the same person. To analyze these influences, the basis of the frequency of emotional transitions of two sequential posts in actual conversational data is evaluated by probability and information entropy analysis. Three tendencies were found: first, a person who posted positively before is likely to post positively again, second, a neutral emotion of a person's post is more likely to be induced when both that person and another person expressed a neutral emotion in the past, third, negative posts do not have a strong influence on the emotion of subsequent posts of that person and other persons. These findings may be useful, for example, in promoting positive conversations.
社交网络对话中帖子情绪影响的分析方法
我们设计了一种分析沟通的方法,该方法侧重于社交网络服务(SNS)上对话中两个连续帖子之间的影响。在社交网络上发表的文章分为积极、消极、中性三种情绪。分析了两种影响:一个人的前一个帖子对另一个人的帖子的情绪,以及一个人的帖子对同一个人的后续帖子的情绪。为了分析这些影响,利用概率和信息熵分析对实际会话数据中两个连续帖子的情绪转换频率进行了评估。研究发现了三种倾向:第一,之前积极发帖的人可能会再次积极发帖;第二,当一个人的帖子和另一个人在过去都表达过中性情绪时,一个人的帖子更有可能被诱导出中性情绪;第三,负面帖子对这个人和其他人的后续帖子的情绪没有很强的影响。这些发现可能是有用的,例如,在促进积极的对话。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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