网络社区交流中距离的作用——以新浪微博为例

doi:10.18306/dlkxjz.2016.08.007

Abstract

Abstract:

The rapid development of information and communication technologies has brought numerous electronic communication modes ((mobile) phone, short message service, email, and recently the popular online social networking sites) that have been expected to influence the role of spatial and relational distances in interpersonal interactions. Based on online "traces" of Sina micro-blog users' interactions in the last two weeks, respondents in our questionnaire survey were required to record and answer questions of (1) who did you interact more often, locals or non-locals and (2) who did you interact more often, acquaintances or strangers in real life. Answers were used in our analysis of the role of spatial distance and relational distance in online social networks. Our findings show that (1) there is a clear tendency of respondents interacting with locals and acquaintances in their real life; (2) respondents' tendency to interact with locals and acquaintances is impacted by their socioeconomic traits, living environment, and information and communication technologies use; (3) theoretically online social networking sites enable users to overcome the distance decay effects and thereby to enlarge their social networks. However, spatial and relational distances sustained the social networks in real life in interpersonal interactions in online social networks.

Key words: spatial distance, relational distance, online social network, information and communication technology, Sina micro-blog

Bo WANG, Feng ZHEN. The role of distance in online social networks: A case study of Sina micro-blog[J].PROGRESS IN GEOGRAPHY, 2016, 35(8): 983-989.

Figures/Tables 2

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Tab.2

References 27

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变量	赋值	样本量	比例/%	均值	标准差
性别	男=1	137	50.9	0.51	0.501
性别	女=0	132	49.1	0.51	0.501
年龄	18~19岁,赋值1	43	16.0	2.26	0.814
	21~29岁,赋值2	133	49.4
	30~39岁,赋值3	73	27.1
	≥40岁,赋值4	20	7.4
受教育水平	高中或高中以下=1	24	8.9	2.70	0.835
	大专院校=2	75	27.9
	本科=3	129	48.0
	硕士或以上=4	41	15.2
就业情况	有工作=1	243	90.3	0.90	0.296
就业情况	无工作=0	26	9.7	0.90	0.296
南京户口	有=1	216	80.3	0.80	0.398
南京户口	无=0	53	19.7	0.80	0.398
居住社区类型	单位社区=1	50	18.6	0.19	0.390
居住社区类型	非单位社区=0	219	81.4	0.19	0.390
居住地区位	市区=1	181	67.3	0.67	0.470
居住地区位	郊区=0	88	32.7	0.67	0.470
智能手机拥有	有=1	234	87.0	0.87	0.337
智能手机拥有	无=0	35	13.0	0.87	0.337
每天新浪微博使用时间	<0.5 h,赋值1	146	54.3	1.63	0.764
	0.5~1.0 h,赋值2	76	28.3
	>1 h,赋值3	47	17.5
是否与本地人交流更多	是=1	142	52.8	0.53	0.500
是否与本地人交流更多	否=0	127	47.2	0.53	0.500
是否与熟人交流更多	是=1	188	69.9	0.70	0.460
是否与熟人交流更多	否=0	81	30.1	0.70	0.460

	模型1：与南京本地人交流				模型2：与实际生活熟人交流
	系数(B)		标准误差	Exp(B)	系数(B)	标准误差	Exp(B)
性别(参考指标：女性)	1.262	0.348^***	3.531		1.689	0.378^***	5.413
年龄(参考指标：18~19岁)
20~29岁	1.111	0.611^*	3.038		2.585	0.645^***	13.267
30~39岁	0.498	0.634	1.646		2.737	0.708^***	15.438
≥40岁	-1.063	0.772	0.345		1.927	0.821^**	6.868
受教育水平(参考指标：硕士及以上)
高中或高中以下	0.929	0.786	2.532		-0.298	0.763	0.742
大专院校	1.269	0.543^**	3.599		0.063	0.596	1.065
本科	0.955	0.470^**	2.598		0.108	0.514	1.114
就业情况(参考指标：无工作)	-1.368	0.818^***	0.255		0.614	0.704	1.847
南京户口(参考指标：无南京户口)	3.862	0.652^***	47.58		0.777	0.449^*	2.176
居住社区类型(参考指标：非单位社区)	-0.047	0.445	0.954		0.913	0.532^*	2.491
居住地区位(参考指标：郊区)	0.874	0.353^**	2.397		-0.072	0.374	0.931
智能手机拥有(参考指标：无智能手机)	0.019	0.546	1.019		0.137	0.638	1.147
每天新浪微博使用时间 (参考指标：<0.5 h)
0.5~1.0 h	-1.592	0.401^***	0.203		-2.431	0.486^***	0.088
>1.0 h	-1.854	0.492^***	0.157		-2.946	0.547^***	0.053
常数项	-3.834	1.051^***	0.022		-1.903	1.010^*	0.149
模型卡方值	138.401^***				119.332^***
拟合优度(Nagelkerke R²)	0.537				0.509
解释度/%	80.7				82.9
样本量	269				269
自由度	14				14

The role of distance in online social networks: A case study of Sina micro-blog

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