Consumer behavior in online game communities: A motivational factor perspective

The concept of online communities has been used to improve customers’ loyalty in recent years. While studies on transaction community such as online auction have received more attention in the literature, entertainment community such as online game has seldom been addressed. This study applies the theory of reasoned action (TRA) and modifies the technology acceptance model (TAM) to propose a research model. An empirical study involving 356 subjects was conducted to test this model. The results indicate that customer loyalty is influenced by perceived enjoyment, social norms and preference. Perceived cohesion has an indirect impact on loyalty. In addition, the finding’s practical implication suggests that community managers must overcome the problems users encounter, including suffering from an unstable system, malicious players and grief players.     

Personality traits and knowledge sharing in online communities

Adopting diffusion theory and the concept of social value orientation, the effects of personality traits on knowledge sharing in a virtual open content community are investigated. In addition to the main effects of personality, it was hypothesized that intrinsic motivations would moderate the effects on knowledge sharing. A sample of N = 256 active users of Wikipedia provided measures of personality, motivation, and knowledge sharing. Latent regression analyses support the notion that authorship of Wikipedia is associated with higher levels of trendsetting and a prosocial value orientation. Moreover, moderation analyses demonstrate that the effect of the latter is moderated by individual differences in motivations to write. Differences with regard to opinion leadership could not be confirmed.     

Impact of anonymity on roles of personal and group identities in online communities

Extant research on the control of anonymous human behavior is inconclusive because of its focus on partial aspects of the self-concept. Multiple self-concepts are usually effective in any given situation. Hence, a holistic approach is preferred over a fragmented picture of the self. We investigate anonymous online communities to determine whether multiple self-concepts concurrently control human behavior.Data were collected from 1453 users through a web-based survey. The results showed that multiple self-concepts concurrently influenced argument quality through group norm conformity, whereas private-self directly influenced argument quality. Furthermore, online anonymity decreased the influence of group identity, contrary to existing assertions.     

Exploring the effect of user engagement in online brand communities: Evidence from Twitter

Social media such as forums, blogs and microblogs has been increasingly used for public information sharing and opinions exchange nowadays. It has changed the way how online community interacts and somehow has led to a new trend of engagement for online retailers especially on microblogging websites such as Twitter. In this study, we investigated the impact of online retailers' engagement with the online brand communities on users' perception of brand image and service. Firstly, we analysed the overall sentiment trends of different brands and the patterns of engagement between companies and customers using the collected tweets posted on a popular social media platform, Twitter. Then, we studied how different types of engagements affect customer sentiments. Our analysis shows that engagement has an effect on sentiments that associate with brand image, perception and customer service of the online retailers. Our findings indicate that the level, length, type and attitude of retailers' engagement with social media users have a significant impact on their sentiments. Based on our results, we derived several important managerial and practical implications.     

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.     

Understanding lurkers in online communities: A literature review

In internet culture, lurkers are a special group of website users who regularly login to online communities but seldom post. This study aims to provide an overall understanding of lurkers by explaining the definition of lurkers, discussing the reasons for lurking and providing suggestions on de-lurking. To understand the reason for lurking, this study first explains why people participate in online communities by building an integrated model of motivational factors of online behaviors. This model classifies motivational factors into four categories: the nature of the online community, individual characteristics, the degree of commitment and quality requirement. Based on this model, four types of lurking reasons are identified: environmental influence, personal preference, individual-group relationship and security consideration. Finally, several strategies for motivating participation in online communities are provided, including external stimuli, improved user-friendliness, encouragement of participation and guidance for newcomers.     

Community engagement and online word of mouth: An empirical investigation

How customer engagement in a firm’s social media marketing platform ? online brand community ? might affect word-of-mouth behavior is an open research issue as well as a vital business problem in e-commerce. To this end, we collected a set of longitudinal data that include community engagement behavior, e-commerce transactions, and customers’ post-purchase reviews. Using a control function approach, we find that consumer engagement in a brand community not only increases the likelihood of generating post-purchase reviews but also increases the likelihood of posting positive online reviews. Furthermore, we find that customer tenure has a positive moderating effect.     

Knowledge sharing in online health communities: A social exchange theory perspective

Online health communities (OHC) are becoming valuable platforms for patients to communicate and find support. These communities are different from general online communities. The knowledge shared in an OHC can be categorized as either general (public) or specific (private), and each category is shared in vastly different ways. Using the social exchange theory, we propose a benefit vs. cost knowledge sharing model for OHCs. The benefits are mainly based on Maslow's hierarchy of needs, and the cost includes cognitive and executional costs. We use this benefit vs. cost model to examine how OHC members share general and specific knowledge. Data were collected from 323 users of two well-known OHCs in China and were analyzed using the structural equation model. The results demonstrate that three factors positively impact the sharing of both general and specific knowledge: a sense of self-worth, members’ perceived social support, and reputation enhancement. Another factor, face concern, has a negative influence on specific knowledge sharing and a positive influence on general knowledge sharing. Executional cost only negatively impacts general knowledge sharing, and cognitive cost only negatively impacts specific knowledge sharing. This study of OHCs reveals that personal benefits promote knowledge sharing and costs prohibit it. These impacts vary between general knowledge and specific knowledge sharing.     

Framing norms in online communities

One problem many organizations deal with is how to effectively govern their online communities. Unlike employees, online community members often respond poorly to formal control mechanisms. This study develops theory on how moderators can build norms in online communities using frame analysis theory from the social movements literature. Through a case analysis of two communities focused on discussing recreational drugs, our findings demonstrate that norm formation is influenced by two phenomena: (1) norm acceptance, and (2) norm transience. Norm acceptance requires that moderators be consistent in their expression of norms. To a lesser extent, moderators must be credible in their expression of norms. If these things occur, the community will accept the norms. Norm transience, on the other hand, occurs when moderators are not sensitive to the community identity. If accepted norms are not aligned with community identity, they will be dropped by the community within one or two years.     

Examining knowledge contribution from the perspective of an online identity in blogging communities

Knowledge contribution is one of the essential factors behind the success of blogging communities (BCs). This research studies knowledge contribution behavior in a BC from the perspective of knowledge contributors and their characteristics using the lens of social identity theory. Social identity theory asserts that individuals are fundamentally motivated to present or communicate their identities in everyday social life through behavior. A similar line of reasoning can be used to argue that members of a BC would also be motivated to communicate their online identities through their behavior, that is, through knowledge contribution in the BC. Specifically, this study conceptualized the online identity and examined the effects of its personal (online kindness, online social skills, and online creativity) and social aspects (BC involvement) on knowledge contribution. The data was collected using an online survey from the members of Cyworld, a popular BC in South Korea and a few other countries (members from South Korea were included in this study). The results indicate that both the personal and social aspects of online identity and their interactions significantly influenced knowledge contribution. Based on the findings, this study offers suggestions to organizers of BCs to enhance the knowledge contribution from their members.     

Forming relationship commitments to online communities: The role of social motivations

Although administrators of online communities (OCs) may focus on improving their OCs through upgrading technology and enhancing the usability of their OCs to attract additional users, the level of OC participation may be associated with social motives. The purpose of this study is to understand how social motivations (that is, network externalities and social norms) affect members committed to OCs. This study tests the hypotheses on data collected from 396 undergraduate students. Data analyses show that network externalities and social norms directly influence social interaction ties, which subsequently results in commitment toward a community. Social norms also directly influence relationship commitments to a community. The results provide insights into how social motivations lead to commitment to an OC, reminding OC administrators to encourage member commitment to the OC from the perspective of social motivations.     

Convergence of an online gradient method with inner-product penalty and adaptive momentum

In this paper, we study the convergence of an online gradient method with inner-product penalty and adaptive momentum for feedforward neural networks, assuming that the training samples are permuted stochastically in each cycle of iteration. Both two-layer and three-layer neural network models are considered, and two convergence theorems are established. Sufficient conditions are proposed to prove weak and strong convergence results. The algorithm is applied to the classical two-spiral problem and identification of Gabor function problem to support these theoretical findings.     

Design and evaluation of an adaptive incentive mechanism for sustained educational online communities

Most online communities, such as discussion forums, file-sharing communities, e-learning communities, and others, suffer from insufficient user participation in their initial phase of development. Therefore, it is important to provide incentives to encourage participation, until the community reaches a critical mass and “takes off”. However, too much participation, especially of low-quality can also be detrimental for the community, since it leads to information overload, which makes users leave the community. Therefore, to regulate the quality and the quantity of user contributions and ensure a sustainable level of user participation in the online community, it is important to adapt the rewards for particular forms of participation for individual users depending on their reputation and the current needs of the community. An incentive mechanism with these properties is proposed. The main idea is to measure and reward the desirable user activities and compute a user participation measure, then cluster the users based on their participation measure into different classes, which have different status in the community and enjoy special privileges. For each user, the reward for each type of activity is computed dynamically based on a model of community needs and an individual user model. The model of the community needs predicts what types of contributions (e.g. more new papers or more ratings) are most valuable at the current moment for the community. The individual model predicts the style of contributions of the user based on her past performance (whether the user tends to make high-quality contributions or not, whether she fairly rates the contributions of others). The adaptive rewards are displayed to the user at the beginning of each session and the user can decide what form of contribution to make considering the rewards that she will earn. The mechanism was evaluated in an online class resource-sharing system, Comtella. The results indicate that the mechanism successfully encourages stable and active user participation; it lowers the level of information overload and therefore enhances the sustainability of the community.     

Increasing participation in online communities: A framework for human–computer interaction

Online communities are becoming an accepted part of the lives of Internet users, although participation in these communities is dependent on the types of people that form them. Some of the online community’s members do not participate, people referred to as lurkers, whereas others who have been in the community for a long time, referred to as elders, participate regularly and support others. Understanding what drives these individuals and how they chose whether or not to participate will lead to online communities that thrive. This paper proposes a conceptual framework to describe what drives such individuals to carry out actions such as posting messages and adding content (level 1), the cognitions they use to determine whether or not to take such actions (level 2) and the means by which they go about carrying out the action in the environment (level 3). Finally, the framework is applied to the problem of encouraging members to participate by discussing the methods by which people can be persuaded to participate by changing the way they interpret their desires and their environment.     

Reciprocity norms and information-sharing behavior in online consumption communities: An empirical investigation of antecedents and moderators

This study seeks a better understanding of information-sharing behavior in online consumption communities by investigating both the antecedents and moderating mechanisms of such behavior. Using self-reported data collected over two periods, along with objective behavioral data, the authors show that a reciprocity norm functions as a proximal determinant of information-sharing behavior. This norm also channels the effects of social, hedonic, and utilitarian community values on sharing behavior. The results reveal that the conversion of reciprocity norms into information-sharing behavior depends on individual and contextual conditions. These significant insights reflect the integration of consumer resource allocation theory with a reciprocity framework to establish an explanatory platform for members’ information-sharing behavior in online communities. Both theoretical and practical implications are discussed.     

Bilingual language supports in online science inquiry environments

Research over the past fifteen years has investigated and developed online science inquiry environments to support students engaging in authentic scientific inquiry practices. This research has focused on developing activity structures and tools to scaffold students in engaging in different aspects of these practices, but relatively little of this research has explored linguistic supports for language minority students studying science in their non-native language. These students are simultaneously learning science and the surrounding academic language in their second language. This study investigates the potential value of providing 8th grade Spanish-speaking English language learners access to content and supports in both English and Spanish as opposed to an English-only format in an online science inquiry environment. Learning outcomes are compared between the two conditions on an immediate post-test in English, a delayed post-test in English, a delayed post-test in Spanish, and a written essay in English in the form of a letter to the governor. The outcomes suggest significant benefits for providing ELL students with access to content and supports in both English and Spanish as opposed to the English-only format. The findings of this study carry important policy implications in light of the growing English-only political movements in the United States and similar political movements in other countries.     

Who to follow recommendation in large-scale online development communities

ContextOpen source development allows a large number of people to reuse and contribute source code to the community. Social networking features open opportunities for information discovery, social collaborations, and improved recommendations of potential collaborators.ObjectiveOnline community and development platforms rely on social network features to increase awareness and attention among community members for improved collaborations. The objective of this work is to introduce an approach for recommending relevant users to follow. Follower networks provide means for informal information propagation. The efficiency and effectiveness of such information flows is impacted by the network structure. Here, we aim to understand the resilience of networks against random or strategic node removal.MethodSocial network features of online software development communities present a new opportunity to enhance online collaboration. Our approach is based on the automatic analysis of user behavior and network structure. The proposed ‘who to follow’ recommendation algorithm can be parametrized for specific contexts. Link-analysis techniques such as PageRank/HITS provide the basis for a novel ‘who to follow’ recommendation model.ResultsWe tested the approach using a GitHub-based dataset. Currently, users follow popular community members to get updates regarding their activities instead of maintaining personal relations. Thus, social network features require further improvements to increase reciprocity. The application of our ‘who to follow’ recommendation model using the GitHub dataset shows excellent results with respect to context-sensitive following recommendations. The sensitivity of GitHub’s follower network to random node removal is comparable with other social networks but more sensitive to follower authority based node removal.ConclusionLink-based algorithm can be used for context-sensitive ‘who to follow’ recommendations. GitHub is highly sensitive to authority based node removal. Information flow established through follower relations will be strongly impacted if many authorities are removed from the network. This underpins the importance of ‘central’ users and the validity of focusing the ‘who to follow’ recommendations on those users.     

The ties that bind: Social network principles in online communities

In a Web 2.0 environment, the online community is fundamental to the business model, and participants in the online community are often motivated and rewarded by abstract concepts of social capital. How networks of relationships in online communities are structured has important implications for how social capital may be generated, which is critical to both attract and govern the necessary user base to sustain the site. We examine a popular website, Slashdot, which uses a system by which users can declare relationships with other users, and also has an embedded reputation system to rank users called ‘Karma’. We test the relationship between user's Karma level and the social network structure, measured by structural holes, to evaluate the brokerage and closure theories of social capital development. We find that Slashdot users develop deep networks at lower levels of participation indicating value from closure and that participation intensity helps increase the returns. We conclude with some comments on mechanism design which would exploit these findings to optimize the social networks and potentially increase the opportunities for monetization.