Emergence Of Online Communities Research Articles

How online inhibition fuels incivility through moral disengagement

This study aimed to investigate the mediating role of moral disengagement in the link between online disinhibition and cyber incivility, against the backdrop of digital technology’s profound impact on human communication and the emergence of online communities. This transformation has highlighted a range of behaviors, including the negative spectrum of cyber incivility, necessitating an exploration of its underlying dynamics. Utilizing a mediation analysis approach, the research examined the interplay among online disinhibition, moral disengagement, and cyber incivility. The participant consisted of 780 Indonesian students, with an average age of 20.3 years, who reported spending 4-7 hours daily on social media. The study was conducted via an online survey distributed to participants. Moral disengagement was assessed using a Moral Disengagement Scale, cyber incivility was measured with a purpose-built scale, and online disinhibition was evaluated using the Online Disinhibition Scale to measure levels of online disinhibition. Findings indicated a significant correlation among the variables, with a substantial portion of participants exhibiting moderate to high levels of online disinhibition, moral disengagement, and cyber incivility. Mediation analysis further revealed that online disinhibition mediated the relationship between moral disengagement and cyber incivility, suggesting that the lowering of inhibitions online facilitates the manifestation of uncivil behavior, influenced by moral disengagement. This study underscores the complex mechanisms driving cyber incivility, highlighting the crucial mediating role of online disinhibition between moral disengagement and cyber incivility. These insights contribute to the broader understanding of digital communication’s impact on behavior, emphasizing the need to address online disinhibition and moral disengagement to mitigate cyber incivility.

Between comments and repeat visit: capturing repeat visitors with a hybrid approach

PurposeUnderstanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation platform, and explores their postbehaviors from their reviews.Design/methodology/approachThe authors employ two different approaches and compare the accuracy of predicting customers' post behavior: (1) using several machine learning classifiers based on sentimental dimensions of customers' reviews and (2) conducting the experiment consisted of two subsections. In the experiment, the first subsection is designed for participants to predict whether customers who wrote reviews would visit the hotel again (referred to as Prediction), while the second subsection examines whether participants want to visit one of the particular hotels when they read other customers' reviews (dubbed as Decision).FindingsThe accuracy of the machine learning approaches (73.23%) is higher than that of the experimental approach (Prediction: 58.96% and Decision: 64.79%). The key reasons of users' predictions and decisions are identified through qualitative analyses.Originality/valueThe findings reveal that using machine learning approaches show the higher accuracy of predicting customers' repeat visits only based on employed sentimental features. With the novel approach of integrating customers' decision processes and machine learning classifiers, the authors provide valuable insights for researchers and providers of hospitality services.

Male and Female Users' Differences in Online Technology Community Based on Text Mining.

With the emergence of online communities, more and more people are participating in online technology communities to meet personalized learning needs. This study aims to investigate whether and how male and female users behave differently in online technology communities. Using text data from the Python Technology Community, through the LDA (Latent Dirichlet Allocation) model, sentiment analysis, and regression analysis, this paper reveals the different topics of male and female users in the online technology community, their sentimental tendencies and activity under different topics, and their correlation and mutual influence. The results show the following: (1) Male users tend to provide information help, while female users prefer to participate in the topic of making friends and advertising. (2) When communicating in the technology community, male and female users mostly express positive emotions, but female users express positive emotions more frequently. (3) Different emotional tendencies of male and female users under different topics have different effects on their activity in the community. The activity of female users is more susceptible to emotional orientation.

Identification of regression function and distribution model for denial of service attack in Second Life online community using simple network management protocol

The evolution of internet results in the emergence of online communities. Numerous communities exist today with millions of users. Security, privacy and availability are the top constraints to be focussed in online communities. Among the other security violations, denial of service (DoS) ranks first as it disrupts the availability of services. DoS attack is reported in a popular virtual world, Second Life which made the complete portal inaccessible to legitimate users. As TCP-SYN is the more prevalent attack strategy of DoS, our solution is aimed to provide efficient detection of DoS in the Second Life community. Detection and differentiation of attack traffic from the legitimate is achieved through simple network management protocol (SNMP) and machine learning algorithms. In spite of the 'n' number of solutions, an efficient outperforming strategy with accurate attack detection is the critical requirement. This paper focuses on the DoS attack detection, classification using SNMP MIB variables and linear regression model. Experimental observation proves the detection accuracy of the method under DoS.

Identification of Regression function and distribution model for Denial of Service attack in Second Life online community using Simple Network Management Protocol

The evolution of internet results in the emergence of online communities. Numerous communities exist today with millions of users. Security, privacy and availability are the top constraints to be focussed in online communities. Among the other security violations, denial of service (DoS) ranks first as it disrupts the availability of services. DoS attack is reported in a popular virtual world, Second Life which made the complete portal inaccessible to legitimate users. As TCP-SYN is the more prevalent attack strategy of DoS, our solution is aimed to provide efficient detection of DoS in the Second Life community. Detection and differentiation of attack traffic from the legitimate is achieved through simple network management protocol (SNMP) and machine learning algorithms. In spite of the 'n' number of solutions, an efficient outperforming strategy with accurate attack detection is the critical requirement. This paper focuses on the DoS attack detection, classification using SNMP MIB variables and linear regression model. Experimental observation proves the detection accuracy of the method under DoS.

Emergence of online communities: Empirical evidence and theory.

Online communities, which have become an integral part of the day-to-day life of people and organizations, exhibit much diversity in both size and activity level; some communities grow to a massive scale and thrive, whereas others remain small, and even wither. In spite of the important role of these proliferating communities, there is limited empirical evidence that identifies the dominant factors underlying their dynamics. Using data collected from seven large online platforms, we observe a relationship between online community size and its activity which generally repeats itself across platforms: First, in most platforms, three distinct activity regimes exist—one of low-activity and two of high-activity. Further, we find a sharp activity phase transition at a critical community size that marks the shift between the first and the second regime in six out of the seven online platforms. Essentially, we argue that it is around this critical size that sustainable interactive communities emerge. The third activity regime occurs above a higher characteristic size in which community activity reaches and remains at a constant and higher level. We find that there is variance in the steepness of the slope of the second regime, that leads to the third regime of saturation, but that the third regime is exhibited in six of the seven online platforms. We propose that the sharp activity phase transition and the regime structure stem from the branching property of online interactions.

Emergence of Online Communities: Empirical Evidence and Theory

Online communities, which have become an integral part of the day-to-day life of people and organizations, exhibit much diversity in both size and activity level; some communities grow to a massive scale and thrive, whereas others remain small, and even wither. In spite of the important role of these proliferating communities, there is limited empirical evidence that identifies the dominant factors underlying their dynamics. Using data collected from seven large online platforms, we observe a universal relationship between online community size and its activity: First, three distinct activity regimes exist, one of low-activity and two of high-activity. Further, we find a sharp activity phase transition at a critical community size that marks the shift between the first and the second regime. Essentially, it is around this critical size that sustainable interactive communities emerge. Finally, above a higher characteristic size, community activity reaches and remains at a constant and high level to form the third regime. We propose that the sharp activity phase transition and the regime structure stem from the branching property of online interactions. Branching results in the emergence of multiplicative growth of the interactions above certain community sizes.

Consumer Involvement in New Product Development: A Case Study from the Online Virtual Community

ABSTRACTIn current dynamic networking era, firms face more pressure, such as increasing market competition, the shortening product development cycle, and consumers’ diverse needs. In the social media context, the emergence of online community provides a platform for consumer involvement in firms’ new product development (NPD). Accordingly, working with consumers via online community has become increasingly important to the development of new products and the improvement of firms’ innovativeness. This paper aims to explore the motivations for consumer involvement in firms’ NPD via online community and to examine the relationships between different combinations of motivations and NPD using the method of fuzzy set quality comparative analysis (fsQCA). The motivations for consumer involvement in firms’ NPD identified by the grounded theory method are as follows: (1) consumers’ needs, (2) compensation, (3) personal interest, (4) an open and flexible online community network, and (5) firms’ trustworthiness. In this study, the authors collect data through the MIUI community (the online community network of Xiaomi, a high‐tech company). The findings reveal a close link between the NPD performance of firms and the motivations for consumer involvement. The findings also have implications for practitioners concerned with the management of consumer resources.

Impacts of Community Commitment on Brand Equity Creation in Company-Initiated Online Brand Communities

With the emergence of online communities, the role of online communities in establishing brand equity has been greatly emphasized. In order to enhance our understanding of commitment in online brand communities, the present study attempts to investigate how three dimensions of community commitment (continuance, affective, and normative commitment) influence each component of brand equity (brand awareness, brand association, perceived quality, and brand loyalty) in the context of company-initiated online brand community. An online survey was conducted with a sample of online brand community members. The results found differential impacts of three types of community commitment on brand equity components, emphasizing the role of continuance and affective commitment. Continuance community commitment positively influenced brand awareness and brand association. Affective community commitment positively affected perceived quality, while among the three, only continuance and affective community commitment influenced the enhancement of brand loyalty. The results suggest that brand marketers need to focus on continuance and affective commitment factors in their online communities to effectively enhance brand equity possessed by consumers. Theoretical and managerial implications are provided.

Developing online health communities through digital media

Twenty-first century's advancement in information technologies and the emergence of online communities have considerably influenced the online communication channels between patients and health service providers. Online health communities are now popular venues for health information sharing, yet little is known about the benefits in developing countries such as Iran. The aim of this case is to investigate on online health communities in Iran and to have a better understanding of consumer's behaviour using health services. The case integrates social support theory and social media concepts with traditional consumer behaviour theory, notably satisfaction. Using a content analysis of three online health communities indicates the value of social media in developing service quality in health industry.

A Statistical Measure of a Population’s Propensity to Engage in Post-Purchase Online Word-of-Mouth

The emergence of online communities has enabled firms to monitor consumer-generated online word-of-mouth (WOM) in real-time by mining publicly available information from the Internet. A prerequisite for harnessing this new ability is the development of appropriate WOM metrics and the identification of relationships between such metrics and consumer behavior. Along these lines this paper introduces a metric of a purchasing population's propensity to rate a product online. Using data from a popular movie website we find that our metric exhibits several relationships that have been previously found to exist between aspects of a product and consumers' propensity to engage in offline WOM about it. Our study, thus, provides positive evidence for the validity of our metric as a proxy of a population's propensity to engage in post-purchase online WOM. Our results also suggest that the antecedents of offline and online WOM exhibit important similarities.