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.     

基于群体行为的社交媒体中水军分析

社交媒体是当下非常热门的一种互联网应用。在发生公共事件时,许多当事人雇佣公关公司在社交媒体上发布虚假信息来影响舆情。这部分为公关公司所服务的社交媒体账号称为水军。水军在当下的中国社交媒体中有泛滥的趋势。基于水军的群体行为分析社交媒体中的水军集团。定义了情感社会网络和情感社会网络中的团的概念;设计了一个分析框架,包括提出了情感社会网络中发现社区,以及从社区中发现对立的派别（称为团）的算法。从微博的评论数据构建情感社会网络,并发现情感社会网络中的团,可以识别水军,而且可以考察社交媒体中的水军集团的特性。采用人工标注的数据集进行了实验。     

An investigation of the impact of media capabilities and extraversion on social presence and user satisfaction

A significant body of research examines media use and user satisfaction, and these studies are mostly focused on the choice of a specific media. The purpose of the present study is to investigate the effects of media capabilities and individual characteristics on social presence, and the subsequent impact on user satisfaction. Drawing on Media Synchronicity Theory, we propose a research model that identifies five physical media capabilities as the determinants of social presence (i.e. the degree to which individuals feel connected to others in online communities), and we then assess the effect of social presence on user satisfaction. Our results suggest that (1) certain media capabilities and (2) extraversion have a positive impact on whether individuals feel connected to others in online communities (i.e. computer-mediated communications). In addition, our moderation analysis shows that extraversion affects social presence differently across communication tasks, suggesting that social presence is a result of the dynamic interaction between media capabilities, the individual, and the task. These results should be of interest to organisations that rely upon virtual meetings to accomplish tasks, as well as to media developers who seek media capabilities that promote a feeling of connected communication between individuals in virtual space.     

Becoming Friends in Online Brand Communities: Evidence From China

With the aid of information technology, consumers have increasingly engaged in social interaction in online brand communities. How can these strangers make friends online? Drawing on embeddedness theory and media richness theory, we examine the antecedents and intermediate mechanisms of online friendship. We theorize that online brand community interactivity aided by instant messaging technology is the main driving force of online friendship, whereas social presence and a sense of yuan (a Chinese concept describing predetermined relations) mediate online friendship development. Online friendship in turn enhances consumer online brand community commitment. We test our conceptual model with a sample of consumers from Chinese online sporting goods forums. The results support our hypotheses and inform online brand community research and practice.     

Using linguistic and topic analysis to classify sub-groups of online depression communities

Depression is a highly prevalent mental health problem and is a co-morbidity of other mental, physical, and behavioural disorders. The internet allows individuals who are depressed or caring for those who are depressed, to connect with others via online communities; however, the characteristics of these discussions have not yet been fully explored. This work aims to explore the textual cues of online communities interested in depression. A total of 5,000 posts were randomly selected from 24 online communities. Five subgroups of online communities were identified: Depression, Bipolar Disorder, Self-Harm, Grief/Bereavement, and Suicide. Psycholinguistic features and content topics were extracted from the posts and analysed. Machine learning techniques were used to discriminate the online conversations in the depression communities from the other subgroups. Topics and psycholinguistic features were found to be highly valid predictors of community subgroup. Clear discrimination between linguistic features and topics, alongside good predictive power is an important step in understanding social media and its use in mental health.     

How media choice affects learner interactions in distance learning classes

In this research we explore aspects of learning, social interaction and community across online learning, also known as distance learning, in higher education. We measure the impact of online social networking (OSN) software versus traditional learning management system (LMS) software. Guided by a theoretical model for how individuals learn and interact within online communities, we measure student perceptions of learning, social interaction and course community before and after our interventions. Survey instruments measure perceived learning, social interaction and community, which we further explore using social network analysis (SNA). Survey results identified that students experienced higher levels of perceived social interaction and course community and, overall, had higher levels of satisfaction with OSN software than those using LMS software. Along this line, SNA results corroborated that OSN software yielded a higher number of interactions, providing a more engaging learning experience.     

Distributed Apprenticeship in Online Communities

Supporting learning in online communities is an important direction for the future of human–computer interaction as people increasingly leverage social technologies to support professional growth and development. However, few have studied how people leverage the socio-technical affordances of online informal workplace communities to develop professional skills in the absence of dedicated expert guidance. We draw from theories of apprenticeship to introduce an emergent theory of distributed apprenticeship, which outlines how community expectations of transparency and mutual support allow for instruction to be directed by a distributed network of nonexperts. We develop distributed apprenticeship through a qualitative study of crowdfunding entrepreneurs, where novices leverage social interactions with community members to develop a wide range of entrepreneurial skills. We then generalize distributed apprenticeship to other workplace contexts and provide design implications for online communities where people develop professional skills with minimal dedicated formal guidance.     

Queer identity online: Informal learning and teaching experiences of LGBTQ individuals on social media

In this study, we explored how social media, particularly social networking sites, serve as informal learning environments for lesbian, gay, bisexual, transgender, questioning, and otherwise-identified (LGBTQ) individuals during formative stages of their evolving LGBTQ identity. We conducted semi-structured interviews (N = 33) probing LGBTQ individuals’ use of social media and identified three educational uses tied to online information seeking: traditional learning (e.g., information seeking about LGBTQ-related issues), social learning (e.g., observing role models or other LGBTQ individuals’ behavior and experiences), and experiential learning (e.g., experimenting with online dating sites and dating apps). These experiences were especially common during the coming out process. Participants also reported a fourth educational function, teaching (e.g., sharing information with others about their experiences as an LGBTQ individual). Teaching was more common among individuals who were out and those with less common identities (e.g., asexual and transgender). Several affordances of social media, including visibility, association, persistence, anonymity, and interactivity enabled these learning experiences.     

Inducing Personalities and Values from Language Use in Social Network Communities

A community in social networks is generally assumed to be composed of a group of individuals with similar characteristics. Although there has been a plethora of work on understanding network topologies (edge density, clustering coefficient, etc.) within an online community, the psycho-sociological compositions of social network communities have hardly been studied. The present paper aims to analyse the communities as composition of induced psycholinguistic and sociolinguistic variables (Personalities, Values and Ethics) across individuals in social media networks. The motivation behind this analysis is to understand the behavioural characteristics at individual as well as societal level in social networks. To this end, three studies were carried out on six different datasets: three Twitter corpora, two Facebook corpora, and an Essay corpus, annotated with Values and Ethics of the users. First, experiments on creating automatic models to determine the Personality and Values of individuals by analysing their language usage and social media behaviour. Second, experiments on understanding the characteristics or blend of characteristics of individuals within an online community. Finally, generation of a map of values and ethics for India, a multi-lingual and multi-cultural country. Striking similarities to general intuitive perception could be observed, i.e., the results obtained in the study resemble our general perception about the cities/towns of India.     

Understanding barriers to online experience for people with physical and sensory disabilities using discursive social psychology

Using social psychology, this study discursively explores barriers limiting the online experiences of people with disabilities. Twenty-one people in New Zealand with physical and sensory disabilities volunteered to participate in an online interview. Data demonstrated a disabling differentials repertoire (pattern), comprising four linguistic resources: negative reactions (when disability was disclosed), exclusion, gatekeeping, and disability costs. In addition to the technology alone, human values embedded in the construction of online technology, and participants’ cultural competency, as well as stereotyped attitudes and economic factors prevalent offline, define and restrain people with disabilities’ online experience. The social identity model of deindividuation is discussed.     

Social media use,community participation and psychological well-being among individuals with serious mental illnesses

BackgroundLittle research exists on social media (e.g., Facebook, Twitter, etc.) use among individuals with serious mental illnesses (SMI). One particular question of interest is the extent to which online social media use is associated with these individuals' community participation, civic engagement and psychosocial outcomes.MethodsTwo-hundred and thirty-two individuals with SMI receiving services at 18 mental health organizations throughout the continental U.S. completed questionnaires on their community participation, civic engagement, quality of life, loneliness, and psychiatric symptoms. They were also asked which social media sites they used; the duration, frequency and importance of, and reasons for, social media use; and the number of contacts they had on social media.ResultsApproximately a third of the sample reported having at least one social media account. Greater frequency, intensity and longevity of social media were associated with higher levels of community participation, and greater intensity of social media use was positively associated with civic engagement. For instance, those who used social media at least 30 min a day had 16.4 more days of participation and voting rates that were higher by 17.4%. Social media use was not found to be significantly associated with loneliness, psychiatric symptoms or quality of life.Discussion and implicationsGreater social media use appears to be associated with greater community engagement without negative repercussions on loneliness, symptoms, or quality of life. Interventions that support social media use among individuals with SMI could have important community integration benefits.     

More Harm Than Good? Online Media Use and Political Disaffection Among College Students in the 2008 Election

This study examines the ways in which online media influenced political disaffection among young adults during the 2008 presidential election campaign. The effects of social media attention, online expression, and traditional Internet sources on political cynicism, apathy, and skepticism were evaluated using data from an online survey of college students. Results show that attention to social media for campaign information is positively related to cynicism and apathy and negatively related to skepticism. Online expression has a positive effect on skepticism. Implications are discussed for the role of social media in bringing a historically disengaged demographic into the political process.     

How good are ideas identified by an automatic idea detection system?

Online communities can be an attractive source of ideas for product and process innovations. However, innovative user‐contributed ideas may be few. From a perspective of harnessing “big data” for inbound open innovation, the detection of good ideas in online communities is a problem of detecting rare events. Recent advances in text analytics and machine learning have made it possible to screen vast amounts of online information and automatically detect user‐contributed ideas. However, it is still uncertain whether the ideas identified by such systems will also be regarded as sufficiently novel, feasible and valuable by firms who might decide to develop them further. A validation study is reported in which 200 posts from an online home brewing community were extracted by an automatic idea detection system. Two professionals from a brewing company evaluated the posts in terms of idea content, idea novelty, idea feasibility and idea value. The results suggest that the automatic idea detection system is sufficiently valid to be deployed for the harvesting and initial screening of ideas, and that the profile of the identified ideas (in terms of novelty, feasibility and value) follows the same pattern identified in studies of user ideation in general.     

在线教育环境中学习共同体研究综述

随着信息技术与教育的深度融合, 蓬勃发展的在线教育已成为教育信息化进程的新常态, 并产生了海量的教育数据, 但也面临辍学率高、课程完成率低、监管不足等问题, 因此如何对海量教育数据进行挖掘和分析是解决这些问题的关键. 学习共同体是以学习者为核心要素的学习组织, 强调学习过程中学习者之间互动交流、资源共享以及协作学习等行为, 从而完成共同的学习任务或目标. 对在线教育环境中学习共同体的研究进行回顾、分析和展望. 首先, 介绍在线教育环境中学习共同体的背景与重要性. 其次, 介绍不同学科中学习共同体的定义. 然后, 总结同质、异质和混合3种类型学习共同体的构建方法. 接着, 从共享、协作和激励3个方面讨论学习共同体的管理机制. 最后, 探讨和展望学习共同体未来的研究方向.     

Exploring and mitigating social loafing in online communities

The motivation to share members’ knowledge is critical to an online community’s survival and success. Previous research has established that knowledge sharing intentions are based on group cohesion. Several studies also suggested that social loafing behavior will seriously corrode group cohesion. Therefore, social loafing is a key obstacle to fostering online community development. Although substantial studies have been performed on the critical factors that affect social loafing in the learning group, those on online communities are still lacking. By integrating two perspectives, social capital and perceived risk, a richer understanding of social loafing behavior can be gained. In the research model, social ties and perceived risk have been driven by anonymity, offline activities, knowledge quality, and media richness. Social ties and perceived risk are hypothesized to affect social loafing in the online community, which, in turn, is hypothesized as negatively affecting group cohesion. Data collected from 323 online users in online communities provide support for the proposed model. The study shows that social loafing is a significant negative predictor of the users’ group cohesion. The study also shows that social ties and perceived risk are important components of social loafing. Anonymity, offline activities, knowledge quality, and media richness all have strong effects on social ties and perceived risk in the online community. Implications for theory and practice and suggestions for future research are discussed.     

The Identification and Influence of Social Roles in a Social Media Product Community

This research focuses on the identification of social roles and an investigation of their influence in online context. Relying on a systemic approach for role conceptualization, we investigate member's activity, shared content and position in the network within a consumer to consumer social media‐based community (SMC) around a product. This investigation led to the identification of ten core roles, based on three key elements: object of interest (product, practice, and community), main contribution type (sharing information and seeking information), individual orientation (factual, emotional). We propose an explanation about how these roles, through their positioning, participate in the community dynamics and how they contribute to the creation and diffusion of cookery as a social practice, shaping the periphery around this practice.     

Guidelines for facilitating the development of learning communities in online courses

Online learning has grown exponentially in recent years; however, dropout problem remains challenging for some online programmes. The dropout problem can be attributed to a number of reasons, with a lack of interaction between learners and the instructor constituting one of the main reasons. The lack of interaction also leads to learners' feeling of isolation. Learning communities can provide learners with an environment conducive to increased interactions and alleviate their feeling of isolation. Unfortunately, there are no clear rules that instructors can follow to help learners create learning communities. In this paper, we propose guidelines for online instructors to facilitate the development of learning communities in online courses. We first review the definition of a learning community, importance of a learning community and factors affecting the development of a learning community. Afterwards, based on a review of the existing guidelines and other relevant literature, we propose guidelines for facilitating the development of learning communities in online courses.     

Product recommendation in online social networking communities: An empirical study of antecedents and a mediator

Intention to facilitate individual voluntary product recommendation in online social networking communities has attracted increased attention. However, it is not obvious why individuals recommend products in a community composed of non-transactional users. What are the critical factors influencing such a behavior? To attempt to provide insights into the product recommendation behavior in online social networking communities, we develop a model to investigate the effects of community atmospheric cues on affective social distance and subsequent product recommendations based on the stimulus–organism–response paradigm. By analyzing the results of a survey using a questionnaire, we found that community reciprocity and community receptivity have a direct influence on product recommendation, while community atmospheric cues have an indirect influence through affective social distance. Theoretical and managerial implications are discussed.     

Security alert: Generalized deep multi-view representation learning for crime forecasting

Crime is a focal problem in modern society, affecting social stability, public safety, economic development, and life quality of residents. Promptly predicting crime occurrence places in a relatively high accuracy is a very important and meaningful research direction. Via the rapid development of social media (e.g., Twitter), the online information can act as a strong supplement for the offline information (crime records). Additionally, the geographic information and taxi flow between communities can model the spatial relationship between communities, which has already been confirmed effective in previous work. In order to efficiently solve crime prediction problem, we propose a generalized deep multi-view representation learning framework for crime forecasting. Our extensive experiments on a 4-month city-wide dataset that consists of 77 communities and 22 crime types show our model improve the prediction accuracy on most crime types.     

The questionable promise of social media for education: connective learning and the commercial imperative

Facebook and other social media have been hailed as delivering the promise of new, socially engaged educational experiences for students in undergraduate, self‐directed, and other educational sectors. A theoretical and historical analysis of these media in the light of earlier media transformations, however, helps to situate and qualify this promise. Specifically, the analysis of dominant social media presented here questions whether social media platforms satisfy a crucial component of learning – fostering the capacity for debate and disagreement. By using the analytical frame of media theorist Raymond Williams, with its emphasis on the influence of advertising in the content and form of television, we weigh the conditions of dominant social networking sites as constraints for debate and therefore learning. Accordingly, we propose an update to Williams' erudite work that is in keeping with our findings. Williams' critique focuses on the structural characteristics of sequence, rhythm, and flow of television as a cultural form. Our critique proposes the terms information design, architecture, and above all algorithm, as structural characteristics that similarly apply to the related but contemporary cultural form of social networking services. Illustrating the ongoing salience of media theory and history for research in e‐learning, the article updates Williams' work while leveraging it in a critical discussion of the suitability of commercial social media for education.