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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (4): 99-109    DOI: 10.11925/infotech.2096-3467.2017.1256
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Analyzing Information Behaviors of Mobile Social Network Users
Wang Feifei, Zhang Shengtai()
School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing100876, China
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Abstract  

[Objective] This paper aims to explore the information behaviors of mobile social network (WeChat) users. [Methods] We crawled the WeChat users’ published posts in the past 5 years, and analyzed their information behaviors based on their characteristics, information contents, WeChat message posted time, WeChat Like and comment numbers. [Results] User-generated contents were affected by the user’s characteristics. There were significant differences among the numbers of Like and comments on different contents. WeChat users’ information posting intervals showed that most WeChat behaviors occurred within a short period of time. [Limitations] The sample size needs to be expanded to generalize our conclusions. [Conclusions] This study provides theoretical foundations for analyzing the behaviors of mobile social network users.

Key wordsMobile Social Network      WeChat Users      Information Release      Statistical Characteristics     
Received: 12 December 2017      Published: 11 May 2018
ZTFLH:  G206  

Cite this article:

Wang Feifei,Zhang Shengtai. Analyzing Information Behaviors of Mobile Social Network Users. Data Analysis and Knowledge Discovery, 2018, 2(4): 99-109.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.1256     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2018/V2/I4/99

用户 消息数 时间跨度(月)
A 417 24
B 468 49
C 1 062 45
D 488 27
E 426 63
F 2 807 35
G 474 23
H 1 199 30
I 1 641 57
变量 赋值 含义
内容类型 1 非日志类
2 日志类
评论数 1 0
2 1-10
3 11-20
4 21以上
点赞数 1 0
2 1-10
3 11-20
4 21以上
性别 1
2
年龄 1 20以下
2 21-30
3 31-40
4 41-50
5 51-60
6 61以上
受教育程度 1 研究生学历
2 大学(本科和大专)
3 高中或中专及以下
职业 1 全日制学生
2 企业公司职员
3 党政机关事业单位
4 专业人士(会计、律师、建筑师、
医护人员、记者)
5 教师
6 其他
统计变量 类型 频次 百分比(%)
性别 5 123 42.3
6 982 57.7
年龄 20以下 116 1.0
21-30 9 353 77.3
31-40 1 562 12.9
41-50 478 3.9
51-60 328 2.7
61以上 268 2.2
教育程度 硕士及以上 4 009 33.1
大学(本科和大专) 6 479 53.5
高中或中专及以下 1 617 13.4
职业 全日制学生 5 862 48.4
企业公司职员 2 525 20.9
党政机关事业单位 209 1.7
专业人士(会计、律师、
建筑师、医护人员、记者)
446 3.7
教师 1 596 13.2
其他 1 466 12.1
统计变量 类型 频次 百分比(%)
评论数 0 10 263 79.2
1-10 2 595 20.0
11-20 96 0.7
21以上 10 0.1
点赞数 0 5 681 72.8
1-10 2 079 26.6
11-20 38 0.5
21以上 7 0.1
信息发布内容 非日志 4 997 38.7
日志 7 931 61.3
用户 B M
A 0.9033 -0.0081
B 0.8953 -0.0044
C 0.9359 -0.0127
D 0.9097 -0.0225
E 0.9072 -0.0057
F 0.9608 -0.0105
H 0.9091 0.007
I 0.9412 -0.0103
J 0.9469 -0.0033
内容分类 点赞分类 卡方检验 LR检验
0 1-10 11-20 21以上
非日志 计数 4 480 514 2 1 391.705*** 422.652***
所占比例% 89.7 10.3 0 0
日志 计数 6 007 1 882 36 6
所占比例% 75.7 23.7 0.5 0.1
内容分类 评论分类 卡方检验 LR检验
0 1-10 11-20 21以上
非日志 计数 4 528 466 3 0 657.607*** 731.75***
所占比例% 90.6 9.3 0.1 0
日志 计数 5 706 2 122 93 10
所占比例% 71.9 26.8 1.2 0.1
因子 -2倍对数似然值 卡方 df 显著水平
截距 1112.095 .000 0 .
性别 1201.663 89.568 1 .000
年龄 1418.631 306.536 5 .000
教育 1173.425 61.330 2 .000
职业 1149.166 37.071 5 .000
类型 变量 日志 显著性水平
常数项 截距 -1.504 .000
性别 性别=男 (对照组=性别女) -.385 .000
年龄 [年龄=1] (对照组=年龄6) 2.338 .000
[年龄=2] (对照组=年龄6) 2.543 .000
[年龄=3] (对照组=年龄6) 2.280 .000
[年龄=4] (对照组=年龄6) 1.529 .000
[年龄=5] (对照组=年龄6) 1.183 .000
教育 [教育=1] (对照组=教育3) -.309 .001
[教育=2] (对照组=教育3) .050 .552
职业 [职业=1] (对照组=职业6) -.238 .004
[职业=2] (对照组=职业6) -.046 .584
[职业=3] (对照组=职业6) -.781 .000
[职业=4] (对照组=职业6) .015 .901
[职业=5] (对照组=职业6) -.075 .475
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