Effects of user behaviors on accumulation of social capital in an online social network
Effects of user behaviors on accumulation of social capital in an online social network
复制标题
在线社交网络中用户行为对社会资本积累的影响
作者：
Yu. M. Rykov;Olessia Koltsova;Yadviga Sinyavskaya
社交网站的使用帮助人们建立和维持社会关系，积累社会资本，这对个人成功越来越重要。在线联系的数量和结构存在很大差异，在某种程度上，这种差异取决于特定的在线用户行为，而这些行为迄今为止还没有得到充分的研究。在这项工作中，我们研究了从VK社交网站中提取的整个以城市为边界的友谊网络（N = 194,601），以探索在地理上接近的关系网络中，特定的在线用户行为如何与结构性社会资本相关。运用社会网络分析对个人社会资本作为网络资产进行评估，并运用多元回归分析来确定和估计网络用户行为对社会资本的影响。分析表明，该图表既聚集又高度集中，这表明存在分层结构：一组由城市级枢纽联合起来的子社区。在此背景下，更多在线群组的成员资格与用户在位置有限网络中的经纪关系呈正相关。此外，本地朋友的比例、收到的点赞数量和使用SNS的持续时间与社会资本指标相关。这有助于在线社会资本形成的文献，在一个大的和地理上本地化的人口水平上进行检查。
The use of social network sites helps people to make and maintain social ties accumulating social capital, which is increasingly important for individual success. There is a wide variation in the amount and structure of online ties, and to some extent this variation is contingent on specific online user behaviors which are to date under-researched. In this work, we examine an entire city-bounded friendship network (N = 194,601) extracted from VK social network site to explore how specific online user behaviors are related to structural social capital in a network of geographically proximate ties. Social network analysis was used to evaluate individual social capital as a network asset, and multiple regression analysis–to determine and estimate the effects of online user behaviors on social capital. The analysis reveals that the graph is both clustered and highly centralized which suggests the presence of a hierarchical structure: a set of sub-communities united by city-level hubs. Against this background, membership in more online groups is positively associated with user’s brokerage in the location-bounded network. Additionally, the share of local friends, the number of received likes and the duration of SNS use are associated with social capital indicators. This contributes to the literature on the formation of online social capital, examined at the level of a large and geographically localized population.
影响因子：
12.7
作者：
Cobb NK;Graham AL;Abrams DB
通讯作者：
Abrams DB
影响因子：
56.9
作者：
J. House;Karl R. Landis;Debra J Umberson
通讯作者：
J. House;Karl R. Landis;Debra J Umberson
SAGE 在线研究方法手册
DOI：
10.4135/9781473957992.n18
发表时间：
2017
期刊：
--
影响因子：
--
作者：
Kennedy H
通讯作者：
Kennedy H