Behavior In Online Communities Research Articles

Do inclusive incentive systems encourage prosocial or competitive behavior in online communities?

Platform designers create and implement incentive systems to encourage users to contribute content to online communities. This article examines the effect of a multidimensional incentive hierarchy in motivating users to engage in competitive and prosocial activities. Utilizing an external change observed in the data science community, Kaggle, and applying a quasi-experimental design, we compared users’ engagement levels before and after introducing a multidimensional incentive hierarchy. We found that implementing a multidimensional incentive system directed users from submitting answers to Kaggle competitions to participating in Kaggle’s online forum discussions. However, our additional analyses suggest that the most and the least motivated users may be less likely to be impacted by such incentives.

Shaming behavior in online communities: exploring a new configuration of digital conversations

PurposeThis research aims to conceptualize online shaming discourse in virtual communities and to serve as a practical guide for online community managers and members.Design/methodology/approachThis conceptual study explores the construction of meanings in human interaction in online communities by presenting a conceptual model, “The Triple-Responsibility Model in Online Communities,” that is based on Kantian ethics.FindingsThe model includes characterizing the roles of core participants in online communities: writer, reader and group manager; and delineating four ethical principles – truth, necessity, proportionality and caution – that can help society find the golden mean between social change and respecting human dignity and concern for an individual’s public image and provide a theoretical contribution and practical guidelines.Research limitations/implicationsIt addresses shaming in virtual communities by suggesting a balance of several key principles, including truth, necessity, proportionality and caution. This is a new conceptualization of online shaming relevant to today's digital arena.Practical implicationsThe guidelines can contribute to the ongoing political debate over what constitutes appropriate and justified regulation. Moreover, Facebook community leaders are responsible for formatting the group’s identity, the technical facets of group management and for setting group boundaries and determining the rules of participation. The posited rules may affect social media group managers, as they are called upon to leverage their privileged position and channel their media power into influencing online discourse.Social implicationsThe current study provides insights into how shaming can be used as a legitimate tool in society by implementing an ethical approach, resulting in guidelines that restrict online discourse for participants in virtual communities and affect the work of social media group managers and policymakers.Originality/valueBy presenting a new conceptual model, the authors suggest that ethics are a helpful tool and offer insights into how online communities' participants and managers should use their voice and balance between shaming and maintaining the dignity of the individual.

The Impact of Fake News on Traveling and Antisocial Behavior in Online Communities: Overview

The concept of “fake news” has become widespread in recent years, especially with the rise of the Internet. Fake news has become a worldwide phenomenon in the consumption of online information, as it is often designed to look like real news and is widely shared on social networks. Concerns regarding the possible detrimental effects of fake news on the public’s knowledge of events and topics, as well as on democracy and public discourse in general, have arisen as a result of the rise of social networks. This article aims to provide a summary of a scientific investigation of antisocial behavior from historical research, conceptual analysis, and qualitative research in the form of a case study method. With the aim of analyzing online forums and the concept of disinformation using fake news, its implications have consequences that provoke reflection on this phenomenon. In the results, we propose a framework for investigating and evaluating the concepts of fake news and its interaction with other forms of antisocial behavior, including whether we can achieve satisfactory results with a reduced amount of searched text. The desire is to observe whether we can use our proposed procedure with the application of artificial intelligence with the VADER BERT model in combination with the intensity of individual types of sentiment.

A Mimetic Theory of User Behaviors in Online Communities: A Computational Study of GitHub

A Mimetic Theory of User Behaviors in Online Communities: A Computational Study of GitHub

Modeling User Behavior Online: A Comparison of Pareto/NBD and BG/NBD Models

This study employs user activity data from Steam, which is the largest PC gaming website globally, to compare the effectiveness of two commonly used probabilistic models, the Pareto/NBD and BG/NBD. The primary aim of the research is to evaluate online search engines and assess the vitality of online communities by developing models that simulate customer behavior and calculate the likelihood of customer engagement. The study examines the assumptions and benefits of both models and their limitations. To collect data, user activity data for a six-month period, from January to June 2022, was collected, including user ID, game title, behavior name, and value. The study focuses on the behaviors of "Purchase" and "play," and the value represents the intensity of each action. The research then evaluates the effectiveness of the two models in predicting user behavior, highlighting their strengths and weaknesses. The study concludes by recommending modifications to the BG/NBD model to enhance its accuracy and overcome its limitations. In summary, the study provides valuable insights into the potential applications of the two models and their strengths and limitations in predicting user behavior in online communities.

Would you go invisible on social media? An empirical study on the antecedents of users' lurking behavior

With the ubiquity of social networks, users of social network apps are likelier to lurk rather than interact. Accordingly, users' lurking behavior in online communities deserves more attention and research. Our research explores the causes of social media users' lurking behavior through three constructs: refusal to disclose information, social browsing, and social network fatigue and the antecedents of these three constructs. Evidence from 786 valid questionnaire data indicates that the users lurk on social media platforms primarily out of a refusal to disclose information and social network fatigue rather than for social browsing. Notably, social network fatigue was the major contributor to the users' lurking behavior. In summary, our research enhances the understanding of the users' lurking behavior and its antecedent variables and reveals key lurking determinants that provide social media vendors with practical insight.

Measuring the Prevalence of Anti-Social Behavior in Online Communities

With increasing attention to online anti-social behaviors such as personal attacks and bigotry, it is critical to have an accurate accounting of how widespread anti-social behaviors are. In this paper, we empirically measure the prevalence of anti-social behavior in one of the world's most popular online community platforms. We operationalize this goal as measuring the proportion of unmoderated comments in the 97 most popular communities on Reddit that violate eight widely accepted platform norms. To achieve this goal, we contribute a human-AI pipeline for identifying these violations and a bootstrap sampling method to quantify measurement uncertainty. We find that 6.25% (95% Confidence Interval [5.36%, 7.13%]) of all comments in 2016, and 4.28% (95% CI [2.50%, 6.26%]) in 2020, are violations of these norms. Most anti-social behaviors remain unmoderated: moderators only removed one in twenty violating comments in 2016, and one in ten violating comments in 2020. Personal attacks were the most prevalent category of norm violation; pornography and bigotry were the most likely to be moderated, while politically inflammatory comments and misogyny/vulgarity were the least likely to be moderated. This paper offers a method and set of empirical results for tracking these phenomena as both the social practices (e.g., moderation) and technical practices (e.g., design) evolve.

The Impact of Symbolic Award Introductions on Contribution Behavior in Online Communities

Online communities frequently suffer from the under-contribution of knowledge in terms of both quantity as well as quality. A common method to incentivize contribution behavior by members is the use of non-monetary rewards, more specifically performance contingent symbolic awards. However, a nuanced understanding of how performance contingent symbolic awards affect existing community members that differ in their experience, and by extension propensity to contribute, is currently lacking. In this paper we exploit a natural experiment, analyzing a user-week panel data set of 166,000 observations, spanning 48 weeks and over 3000 community members, and show a negative effect of award introduction on contribution quantity and an insignificant effect on contribution quality on average. Moreover, we are able to show how accounting for heterogeneous user characteristics in terms of within-community experience, govern the effect of award introduction and knowledge accumulation. In particular, we find that low experience members significantly reduce their contribution quality while not changing their contribution amount, and high experience members reduce their contribution quantity without decreasing their contribution quality. Thus, this research contributes to the theory on new forms of organizing, in addition to advancing the literature on symbolic awards and online public goods contributions.

From knowledge seeking to knowledge contribution: A social capital perspective on knowledge sharing behaviors in online Q&A communities

Previous research has examined knowledge seeking behaviors and knowledge contribution behaviors in online communities, but it is not clear what is the relationship between knowledge seeking and knowledge contribution, leading to a question on what drives knowledge sharing in online communities. Drawing on the social capital theory, this study proposes that knowledge seeking behaviors lead to knowledge contribution behaviors through online users' social capital which is accumulated as a result of knowledge seeking. Based on the data on >1000 online users' knowledge sharing activities in the Zhihu Community in China, this study provides empirical support for the proposed model and the result show that online community users' knowledge seeking behaviors have a positive impact on their social capital, which is further positively related to their knowledge contribution behaviors – a partially mediated process. This study enriches current research on knowledge sharing in the increasingly digitalized society, and the findings provide important insights on knowledge sharing activities that will help manage knowledge exchange more effectively in online communities.

Online communities and offline sales: considerations on visiting behavior dimensions and online community types

PurposeAs an increasingly popular tool for product exploration, online communities have an important impact on consumers’ purchasing decisions. The purpose of this study is to gain a deeper understanding of how visiting behaviors in online communities affect consumers’ offline purchasing behavior. The moderating role of two dimensions of consumer visiting behaviors (visiting depth and visiting breadth) also receives attention. Moreover, the impact of consumer visiting behaviors on offline sales for different types of online communities is also the focus of this paper.Design/methodology/approachTo test the empirical model, the authors collected data on consumers’ visits to an online real estate platform with local housing sales data. In addition to the baseline regression analysis of the data with the help of Stata 17.0, the study also analyzes the robustness of the results through several methods.FindingsThe authors focus on an online community for newly-built housing and find that consumer visits to the focal online community have a positive impact on offline sales. Visiting breadth has a negative moderating effect on this relationship, and no statistically significant moderating effect is found for visiting depth. Further, our empirical exploration finds that consumer visits to competitive online communities have a positive impact on offline focal product sales, but visits to complementary online communities have no statistically significant effect on offline sales.Originality/valueOur findings contribute to the understanding of consumers’ cross-channel purchasing behavior and provide new insights into how visiting behaviors in online communities affect consumers’ purchasing decisions.

Managing trolling in online communities: an organizational perspective

PurposeThe literature lacks knowledge on how organizations can manage trolling behaviors in online communities. Extant studies tend to either focus on user responses to trolling behaviors (i.e. a micro-level perspective) or how the trolling infrastructure is governed by platforms (i.e. a macro-level perspective), paying less attention to the organizational community host. With more organizations hosting online communities on social media networks and trolling behaviors increasingly disrupting user engagement within these communities, the current understanding of trolling management practices has become inapt. Given the commercial and social damage caused by trolling behaviors, it is important to understand how these can be best managed. The purpose of this study, therefore, is to examine the meso-level perspective of trolling management by focusing on organizational practice.Design/methodology/approachThe research design consists of an in-depth non-participatory netnography based on a case study of PETA’s (“People for the Ethical Treatment of Animals”) Facebook community.FindingsSix distinct trolling management strategies are identified and categorized by their direct versus indirect communication approach: non-engaging, educating, bolstering, expurgating, asserting and mobilizing. Some strategies are deemed to be more successful than others in generating positive community outcomes such as reduced trolling frequency or further support from like-minded community members.Originality/valueThe findings contribute to the meso-level perspective in the trolling management literature by introducing a novel, empirically informed typology of organizational trolling management strategies.

Strategic Behavior in Online Communities: Evidence from Peer Evaluations on Wikipedia

Online communities that typically defy traditional forms of hierarchy often rely on lateral authority delegated to peer evaluators. While peer evaluations are supposed to be meritocratic, we theorize that people engaged in peer evaluation are often motivated to behave strategically. Processes that make evaluations transparent also motivate actors to consider how their evaluation of a peer will be perceived, and how they themselves will be perceived and evaluated in turn. This creates a dilemma with respect to evaluating peers negatively. Evaluating at least some peers negatively is important to be perceived as an honest, capable member of a meritocratic community, yet negative evaluations can provoke retaliation. We theorize that strategic actors reserve their negative evaluations for peers who are unlikely or unable to retaliate. We find support for our arguments in a unique dataset of peer evaluations in elections for Wikipedia administrators in 2003–14, plus detailed qualitative interviews with 24 Wikipedia peer evaluation participants and administrators. We elaborate our results with implications for research on peer evaluation in online communities and beyond as well as on novel forms of organizing where meritocratic, peer-based ideals persist.

How context and attention shape behaviors in online communities: a modified garbage can model

AbstractOnline communities have emerged as important organizational forms, but there are many gaps in our understanding. In particular, researchers have mainly focused on individual-level drivers of behaviors in communities, while downplaying (formal, informal) context at various levels. We theorize that different dimensions of context (i.e. omnibus and discrete context) influence decision-making in online communities through mechanisms involving community members’ attention. Specifically, context influences which problems members perceive and which solutions they retrieve and apply, thereby shaping the process of matching solutions and problems. We derive four hypotheses about contribution behaviors in online communities and how such behaviors are influenced by context. The empirical setting for our study is the open-source software community. We find support for our hypotheses in a unique dataset that captures the behavior of 24,057 community members who used the SourceForge.net online platform from 2000 to 2002.

YouTube Video Comments on Healthy Eating: Descriptive and Predictive Analysis.

BackgroundPoor nutrition and food selection lead to health issues such as obesity, cardiovascular disease, diabetes, and cancer. This study of YouTube comments aims to uncover patterns of food choices and the factors driving them, in addition to exploring the sentiments of healthy eating in networked communities.ObjectiveThe objectives of the study are to explore the determinants, motives, and barriers to healthy eating behaviors in online communities and provide insight into YouTube video commenters’ perceptions and sentiments of healthy eating through text mining techniques.MethodsThis paper applied text mining techniques to identify and categorize meaningful healthy eating determinants. These determinants were then incorporated into hypothetically defined constructs that reflect their thematic and sentimental nature in order to test our proposed model using a variance-based structural equation modeling procedure.ResultsWith a dataset of 4654 comments extracted from YouTube videos in the context of Malaysia, we apply a text mining method to analyze the perceptions and behavior of healthy eating. There were 10 clusters identified with regard to food ingredients, food price, food choice, food portion, well-being, cooking, and culture in the concept of healthy eating. The structural equation modeling results show that clusters are positively associated with healthy eating with all P values less than .001, indicating a statistical significance of the study results. People hold complex and multifaceted beliefs about healthy eating in the context of YouTube videos. Fruits and vegetables are the epitome of healthy foods. Despite having a favorable perception of healthy eating, people may not purchase commonly recognized healthy food if it has a premium price. People associate healthy eating with weight concerns. Food taste, variety, and availability are identified as reasons why Malaysians cannot act on eating healthily.ConclusionsThis study offers significant value to the existing literature of health-related studies by investigating the rich and diverse social media data gleaned from YouTube. This research integrated text mining analytics with predictive modeling techniques to identify thematic constructs and analyze the sentiments of healthy eating.

How Context and Attention Shape Behaviors in Online Communities: A Modified Garbage Can Model

Online communities have emerged as important organizational forms, but there are many gaps in our understanding. In particular, researchers have mainly focused on individual-level drivers of behaviors in communities, while downplaying (formal, informal) context at various levels. We theorize that different dimensions of context (i.e., omnibus and discrete context) influence decision-making in online communities through mechanisms involving community members’ attention. Specifically, context influences which problems members perceive and which solutions they retrieve and apply, thereby shaping the process of matching solutions and problems. We derive four hypotheses about contribution behaviors in online communities and how such behaviors are influenced by context. The empirical setting for our study is the open-source software community. We find support for our hypotheses in a unique dataset that captures the behavior of 24,057 community members who used the SourceForge.net online platform from 2000 to 2002.

РЕЧЕВАЯ ЭТИКЕТНОСТЬ СЕТЕВОГО ОБЩЕНИЯ: СЕМАНТИКА И ПРАГМАТИКА НОМИНАЦИЙ ПОЛЬЗОВАТЕЛЕЙ

The article is devoted to the research of one of the most relevant aspects of etiquette in network communication–nominations participants of communication use to refer to each other. Based on a broad understanding of speech etiquette in social networks–as a means of harmonization of speech activity in various communication situations, the authors consider users’ nominations in social networks as markers of constructive or destructive verbal behavior in online communities. The research is based on linguistic and stylistic analysis, which allows: (1) describing the linguistic characteristics of nominations as lexical units in terms of word formation, grammar, and semantics; (2) revealing the peculiarities of the pragmatics of using the nominations in network communication taking into account the linguistic parameters of these nominations; (3) characterizing their stylistic properties that correlate with the goals of communication (common interests, problem solving, tips, causticity) and the selected manner of verbal behavior (solidarity, outrageous behavior, verbal aggression). To guarantee representativeness, the authors took the material for the research from resources created for groups with different principles of formation: gender (“Strana mam”), age (“4chan”) and territorial ones (“Yubileyniy Kvartal i Shuvalovsky”). The analysis shows that the users’ nominations in online communities demonstrate the participants’ solidarity within the relatively closed we-communities as the dominant setting of communication. Within each community, there is a focus on live communication, which activates the use of the phatic speech genres of everyday communication: appeal (generalized or personal), request, advice, comment, call, offer, insult, and so on. The variety of nominations from the point of view of the addressee (generalizing and personal), as well as in terms of communicative orientation (contactestablishing and contact-destroying), is determined by the set of situations of communication, frequent in different communities, and by communicants’ value orientations. In “Strana mam”, a women’s forum focused on the preservation of family values, solidarity is manifested in the desire for a more intimate communication; this activates the use of diminutives, language play, and vocabulary with a positive connotation. In the territorial “Yubileyniy Kvartal i Shuvalovsky” group, the value of community is cultivated, and solidarity is manifested in the imitation of respectful, often close to business, communication, which entails frequent generalizing nominations with a positive attributive component and the use of interlocutors’ full names as personal nominations. In the teenage “4chan” community, solidarity is manifested in the intentional outrageous communication (by using nominations with obscene words), which demonstrates an open violation of family, moral, spiritual, and other values.

The use of nondialogic trolling to disrupt online communication

Trolling, a uniquely common antisocial behavior in online communities, has traditionally been conceptualized as a phenomenon based in group dialogue. Yet it is possible for trolling to occur without any actual dialogue between the troll and the intended targets. In this paper, several methods of trolling are presented, each of which is performed through engagement with user-generated media artifacts rather than through back-and-forth conversation among users. These are broadly grouped into four categories based on the type of media engagement that is exploited: content creation, content curation, content evaluation, and content refinement. This manuscript therefore fills a significant gap in the literature on this topic and helps to resolve a limitation in existing explications of the construct by showing its applicability to a wider range of behaviors than previously acknowledged.

Exploring Behavior of People with Suicidal Ideation in a Chinese Online Suicidal Community.

People with suicidal ideation (PSI) are increasingly using social media to express suicidal feelings. Researchers have found that their internet-based communication may lead to the spread of suicidal ideation, which presents a set of challenges for suicide prevention. To develop effective prevention and intervention strategies that can be efficiently applied in online communities, we need to understand the behavior of PSI in internet-based communities. However, to date there have been no studies that specifically focus on the behavior of PSI in Chinese online communities. A total of 4489 postings in which users explicitly expressed their suicidal ideation were labeled from 560,000 postings in an internet-based suicidal community on Weibo (one of the biggest social media platforms in China) to explore their behavior. The results reveal that PSI are significantly more active than other users in the community. With the use of social network analysis, we also found that the more frequently users communicate with PSI, the more likely that users would become suicidal. In addition, Chinese women may be more likely to be at risk of suicide than men in the community. This study enriches our knowledge of PSI’s behavior in online communities, which may contribute to detecting and assisting PSI on social media.

Factors Affecting Participants’ Knowledge-Sharing Behaviors in Online Communities: a Systematic Review

In the current competitive economy, knowledge considered as a valuable source of competitive advantage. Online Communities (OCs) became accepted online popular platforms for exchanging and sharing knowledge between groups or individuals with common needs and interest. How to motivate users to contribute their knowledge is one of the most challenges in OCs. The factors that influence members to exchange their knowledge in OCs have not fully explored in the context of knowledge sharing. This systematic literature review aimed to examine the previous quantitative/qualitative studies from 2006 to 2017 to identify the most frequently cited factors that influence participants’ knowledge sharing behavior in OCs. The current study classified those factors into three main categories: individual, community, and technological factors. The study also examined different theories, constructs, and models that used in the selected articles. The findings from this study could be applied in future empirical research to construct a conceptual framework for members’ knowledge sharing behavior in OCs.

Did they login?

Researchers studying user behaviors in online communities often conduct analyses of user interaction data recorded in system logs e.g., an edit in Wikipedia. Such analysis relies on collating interactions by a unique identifier such as a user ID. However, if users can contribute without being logged-in (i.e., anonymously) analysis of interaction data omit part of a user's experience. Problematically, anonymous traces are unlikely to be randomly distributed, so their omission can change statistical conclusions, with implications for both research and practice. To understand the impacts on conclusions of leaving out anonymous traces, we conducted an analysis of system logs from two online citizen science projects. Attributing anonymous traces with user IDs, we found that (1) many users contribute anonymously, though with varied patterns; and (2) attributing anonymous traces diminishes empirical evidence used to support theory and change the results of system algorithms. These results suggest anonymous traces have implications for research on user behaviors and the practices associated with using such data to tailor user experiences in online communities.