Individual characteristics influencing the sharing of knowledge on social networking services: online identity,self-efficacy,and knowledge sharing intentions

ABSTRACT

Social media have become an important place for individuals with similar interests to exchange opinions and share resources. Ubiquitous collaborative learning environments in SNS have great educational and organisational potential and offer a platform for sharing knowledge. Rising interest in personal factors in knowledge management research calls for a better understanding of how knowledge is shared in SNS-based collaborative learning. Grounded on the theories of planned behaviour and social identity, this study investigates individual characteristics that affect the sharing of knowledge in SNS learning communities. The study also examines whether intent to share knowledge mediates those personal characteristics and sharing of knowledge. Eighty individuals from five active Facebook groups participated in this study. The findings indicate that individual characteristics, such as online personal identity, web-specific self-efficacy, and knowledge-creation self-efficacy significantly predict sharing of knowledge. In addition, intent to share knowledge mediates between the sharing of knowledge and online identity, web-specific self-efficacy, or knowledge-creation self-efficacy. The results reveal a need for customised support and environmental design focusing on online personal identity, web-specific self-efficacy, knowledge-creation self-efficacy, and intent to share knowledge in a knowledge-sharing community on SNS. Implications for the SNS communities and suggestions for further research are discussed.     

Students and social networking sites: the posting paradox

This article reports the results of a field study in which undergraduate students were questioned about their use of social networking sites and the appropriateness of the content that they post. The responses indicate that students routinely post content that they realise is not appropriate for all audiences, especially potential employers. Considering how extensively the press has covered the negative impacts of inappropriate posting, the fact that students are knowingly continuing the practice is surprising. The article discusses the implications of these results and proposes areas for future research.     

Keeping our network safe: a model of online protection behaviour

The objective of this study is to develop and test a model of online protection behaviour, particularly regarding the use of virus protection. Hypotheses are proposed concerning the predictors of the intention to engage in virus protection behaviour. Using a survey of 273 college students who use the Internet, a test of the hypotheses is conducted using multiple regression analysis. The result suggests that perceived self-efficacy in using virus protection measures, perceived response efficacy of virus protective measures, positive outcome expectations of virus protection measures, perceived vulnerability to virus threats and prior virus infection experiences were the most important predictors of the intention to adopt virus protection behaviour. The conclusion is that those who are in charge of information security management should not only concentrate their efforts into increasing individuals' awareness of the likelihood of virus attacks, but also conduct interventions aimed at increasing self-efficacy and response efficacy beliefs.     

Users' Satisfaction with Social Network Sites: A Self-Determination Perspective

When the online social networking market is no longer a “blue ocean,” retaining existing users and maintaining their satisfaction with the current social network site (SNS) become SNS providers' most important tasks. This study applies Self-Determination Theory and examines the relationship between trust, relatedness need, and users' satisfaction with SNSs. Using Facebook as the context, we tested our hypotheses with the student sample from a large state university in U.S. The results show that competence and benevolence trust beliefs positively influence relatedness need satisfaction; relatedness need satisfaction and relatedness need level significantly influence uses' satisfaction with SNSs. The theoretical and practical implications of this study are also discussed.     

Examining online citizenship behaviours in social network sites: a social capital perspective

As users have flocked to social network sites (SNSs), these sites have gained tremendous scale and concomitant social influence. This growth has come at the cost of social disruption caused by the posting of abusive comments and rumours that turn out to be false. To combat these negative phenomena, this study proposes SNS citizenship behaviour and examines it from the perspective of social capital theory. This study further examines how the key characteristics of SNS in terms of the concept of customer value affect social capital development in an SNS context. The test results explain that the structural, relational, and cognitive dimensions of social capital have significant direct and indirect effects on the SNS citizenship behaviour. These findings also explain that four key characteristics (exploration, communication support, playfulness, and responsiveness) of SNS affect the three dimensions of social capital. This study contributes to the literature in its establishment of the concept of SNS citizenship behaviour and examines it from the social capital theory perspective. Its findings have practical implications through its guidance on how to develop SNS features and manage these sites for the citizenship behaviour of their users, which are achievements for the harmonious and effective functioning of SNS.     

有限节点驱动的微博社会网络话题推荐方法

针对微博在线社会网络中的话题推荐问题,研究了如何选取多个驱动用户节点使得推荐话题能够得到大的传播广度,提出了一种新的信息推荐方法,可以求得次优的驱动节点集合使得推荐话题得到近似最大的传播广度。通过三个环节进行计算：通过修正的PageRank算法求得影响力大的节点;计算第一步得到的每个节点引起的话题传播广度;计算多个节点联合驱动时话题传播的广度,选择使传播广度最大的驱动节点集合。实验结果表明选取的近似最优驱动节点集合能够使得推荐信息得到更大广度的传播。     

Building Stronger Ties With Alumni Through Facebook to Increase Volunteerism and Charitable Giving

This research explores how strength of network ties, as fostered by the use of a social network site, Facebook, (a) influences alumni attitudes toward volunteering for and making charitable gifts to their alma mater, and (b) fortifies consistency between attitude and behavior. After exploratory interviews and participant observation, a survey of 3,085 alumni was conducted for hypothesis testing. Structural equation modeling analysis revealed: First, active participation in Facebook groups positively predicted strength of network ties along 2 dimensions: frequency of communication and emotional closeness. Second, both dimensions of tie strength influenced actual behavior, albeit via different routes. The paper also contributes to attitude change research in showing that strength of network ties can help ensure consistencies between attitude and behavior.     

大学生在线学习效果调查研究

疫情爆发以来,为响应中央"停课不停教、停课不停学"的指导意见,在线学习在大学生间真正普及。虽然现已基本的资源平台、通讯渠道、设备要求等等外部条件得到满足,但在内部真正影响大学生在线学习效果的因素仍然存在。本文将从大学生在线学习的效果、对在线学习的态度以及影响在线学习效果的各种因素进行分析,得到启示,并由此给相关方面的完善提供参考意见。     

Campaigning on Twitter: Microblogging and Online Social Networking as Campaign Tools in the 2010 General Elections in the Netherlands

The present study focuses on how candidates in the Dutch general elections of 2010 use Twitter, a popular microblogging and social networking service. Specifically the study focuses on explaining why some candidates are more likely to adopt Twitter, have larger networks, and show more reciprocation than other candidates. The innovation hypothesis, predicting that candidates from less established and smaller parties will use Twitter more extensively, is unsupported. This suggests that normalization of campaign practices is present on Twitter, not changing existing communication practices. The findings do show that being an early adopter of these new technologies is more effective than adoption shortly before Election Day.     

成本控制下的快速影响最大化算法

针对成本控制下影响最大化时间复杂度高的问题,提出一种快速的最大化算法BCIM。首先提出对初始节点进行多次传播的传播模型;其次选择高影响力节点作为备用种子,并基于近距离影响减少计算节点影响范围的工作量;最后利用动态规划方法在每组备用种子中最多选择一个种子。仿真实验表明,与随机算法Random、每轮取影响力增量最大的节点的贪心算法Greedy_MII、每轮取影响力增量与成本比值最大的节点的贪心算法Greedy_MICR相比,在影响范围上,BICM接近或优于Greedy_MICR及Greedy_MII,远次于Random;在种子集合的质量上,BCIM、Greedy_MICR、Greedy_MII三者差距较小,但都远远好于Random;在运行时间上,BCIM是Random的几倍,而两个贪心算法都是BCIM的几百倍。BCIM算法能在较短时间内找到更有效的种子集合。