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基于微博用户的情绪变化分析
Alternative TitleChinese mood variation analysis based on Sina Weibo
汪静莹1; 甘硕秋2; 赵楠2; 刘天俐3; 朱廷劭2
First Author汪静莹
2016
Source Publication中国科学院大学学报
Correspondent Emailtszhu@ psych. ac. cn
ISSN2095-6134
Subtype期刊论文
Volume33Issue:6Pages:815-824
Contribution Rank1
Abstract

通过网络大数据的方法宏观地分析微博用户在不同季节和时间的情绪变化.以195万微博活跃用户为样本,在每个季节下载一周的微博活跃用户数据,利用“中文心理分析系统”计算每个季节积极情绪和消极情绪词的词频.结果显示:1)人们的综合情绪的2个高峰分别在中午和晚8点;2)虽然人们在周末的积极情绪与工作日无异,但消极情绪在周末明显低于工作日;3)人们在夏季的积极情绪和消极情绪最高,在秋季的积极情绪和消极情绪最低;4)两种性别的情绪走势一致,但女性较男性有更多情绪表达、更情绪化,更易感.

Other Abstract

Abstract This study tried to recognize the Chinese mood variations in different seasons and time periods via the big data on Internet. Participants were 1. 95 million active users of Sina Weibo. We downloaded their data of one week selected in each of the four seasons of one year. Then we used TextMind to calculate the ratios of positive affect ( PA) and negative affect ( NA) words. Results are given as follows. 1) Integrated mood had two peaks at noon and 8 o clock in the evening. 2)
Although PA in weekends was not different from that on the weekdays,NA in weekends was lower than that on weekdays. 3) In summer,both PA and NA were the highest. In autumn,both PA and NA were the lowest. 4) The two genders had similar mood variation trends,but females had more mood expressions than males and they were sentimental and susceptive.

Keyword微博 情绪 生物节律 大数据 性别差异
Subject Area网络心理学
DOI10. 7523 / j. issn. 2095-6134. 2016. 06. 014
URL查看原文
Indexed ByCSCD
Language中文
CSCD IDCSCD:5853521
Citation statistics
Document Type期刊论文
Identifierhttp://ir.psych.ac.cn/handle/311026/21049
Collection中国科学院行为科学重点实验室
Corresponding Author朱廷劭
Affiliation1.中国科学院心理研究所中国科学院行为科学重点实验室
2.中国科学院大学
3.北京大学人口研究所
First Author AffilicationKey Laboratory of Behavioral Science, CAS
Recommended Citation
GB/T 7714
汪静莹,甘硕秋,赵楠,等. 基于微博用户的情绪变化分析[J]. 中国科学院大学学报,2016,33(6):815-824.
APA 汪静莹,甘硕秋,赵楠,刘天俐,&朱廷劭.(2016).基于微博用户的情绪变化分析.中国科学院大学学报,33(6),815-824.
MLA 汪静莹,et al."基于微博用户的情绪变化分析".中国科学院大学学报 33.6(2016):815-824.
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