Large Online Community Research Articles

Impact of the quality and diversity of reference products on creative activities in online communities

In creativity research, an important unresolved issue relates to identifying the kind of information an individual should be exposed to in order to be highly creative. We aimed to gain insights into this issue; we collected and statistically analyzed three datasets related to three large online communities (namely Cities: Skylines, SCP-wiki, and Archive of Our Own) engaged in mod development and novel writing to examine whether the quality and diversity of other people’s products referred to have a positive effect on product generation. Our analysis revealed the following three findings: (1) the quality diversity of reference products generated by others has the most positive impact on the quality of generated products when it is neither high nor low, (2) the content diversity of reference products generated by others has a negative impact on the quality of generated products, and (3) the quality of reference products generated by others has a negative impact on the quality of generated products when it is extremely high. We conclude by discussing the implications of the findings for creativity research.

Heterogeneous Social Network Location Aware Multi Party Data Protection and Privacy System

Social networks are large online communities that allow users to interact and share information. They can be used to connect with friends, family, or potential romantic partners, build a business, or even find a job. The evolution of social media has led to a trend of posting daily photos on online Social Network Platforms (SNPs). The privacy of online photos is often protected carefully by security mechanisms. However, these mechanisms will lose effectiveness when someone spreads the photos to other platforms. This project proposes a blockchain based secure photo sharing framework that provides powerful dissemination control for heterogeneous social network photo sharing. In contrast to security mechanisms running separately in centralized servers that do not trust each other, this framework achieves consistent consensus on photo dissemination control through carefully designed smart contract-based protocols

Collaborating with Bots and Automation on OpenStreetMap

OpenStreetMap (OSM) is a large online community where users collaborate to map the world. In addition to manual edits, the OSM mapping database is regularly modified by bots and automated edits. In this paper, we seek to better understand how people and bots interact and conflict with each other. We start by analysing over 15 years of mailing list discussions related to bots and automated edits. From this data, we uncover five themes, including how automation results in power differentials between users and how community ideals of consensus clash with the realities of bot use. Subsequently, we surveyed OSM contributors on their experiences with bots and automated edits. We present findings about the current escalation and review mechanisms, as well as the lack of appropriate tools for evaluating and discussing bots. We discuss how OSM and similar communities could use these findings to better support collaboration between humans and bots.

Scalable Spatio-temporal Top-k Interaction Queries on Dynamic Communities

Social media platforms generate massive amounts of data that reveal valuable insights about users and communities at large. Existing techniques have not fully exploited such data to help practitioners perform a deep analysis of large online communities. Lack of scalability hinders analyzing communities of large sizes and requires tremendous system resources and unacceptable runtime. This article proposes a new analytical query that identifies the top- k posts that a given user community has interacted with during a specific time interval and within a spatial range. We propose a novel indexing framework that captures the interactions of users and communities to provide a low query latency. Moreover, we propose exact and approximate algorithms to process the query efficiently and utilize the index content to prune the search space. The extensive experimental evaluation on real data has shown the superiority of our techniques and their scalability to support large online communities.

Social Listening for Product Design Requirement Analysis and Segmentation: A Graph Analysis Approach with User Comments Mining.

This study investigates customers' product design requirements through online comments from social media, and quickly translates these needs into product design specifications. First, the exponential discriminative snowball sampling method was proposed to generate a product-related subnetwork. Second, natural language processing (NLP) was utilized to mine user-generated comments, and a Graph SAmple and aggreGatE method was employed to embed the user's node neighborhood information in the network to jointly define a user's persona. Clustering was used for market and product model segmentation. Finally, a deep learning bidirectional long short-term memory with conditional random fields framework was introduced for opinion mining. A comment frequency-invert group frequency indicator was proposed to quantify all user groups' positive and negative opinions for various specifications of different product functions. A case study of smartphone design analysis is presented with data from a large Chinese online community called Baidu Tieba. Eleven layers of social relationships were snowball sampled, with 14,018 users and 30,803 comments. The proposed method produced a more reasonable user group clustering result than the conventional method. With our approach, user groups' dominating likes and dislikes for specifications could be immediately identified, and the similar and different preferences of product features by different user groups were instantly revealed. Managerial and engineering insights were also discussed.

Beyond intensive motherhood: Performing online cross-border motherhood on social media

Mamatzhik (Funny Mom) was founded as a closed Israeli maternal community on Facebook, available only to women for dealing with conservative patriarchal social demands. It became the largest online community in Israel, whose main preoccupation is young motherhood. A thematic analysis of in-depth interviews and posts posted on their Facebook page was conducted. Seeking to understand and explain the content characteristics of posts as well as interpretations and experiences of young mothers, our findings show that Mamatzhik offers an alternative and subversive identity for modern mothers, shaping a new liberal feminist maternal identity – that is, online cross-border motherhood. It also provides an online space that allows temporal ventilation from social pressures using online daily carnival entertainment shows. Mamatzhik also uses subversive feminist humor to challenge the ideology of intensive motherhood, which requires mothers to devote their lives to the benefit of their children at their own expense.

A Framework of Environmental, Personal, and Behavioral Factors of Adult Learning in Online Communities of Practice

Adult learning is a complex phenomenon that takes place over an adult’s lifetime and is not limited to a particular age. It includes a set of activities to enhance life through improving skills, knowledge and capabilities. The foundational theories of adult learning, such as andragogy theory, place the individual adult centre stage and differentiate adult learning from formal learning. They also shift the focus from the individuals to the environment in which adult learning takes place. In line with this movement, online communities of practice (OCOPs) have evolved from being considered as online environments for learning to specialised forums that allow practitioners to collaborate around a project of mutual interest. The principles of adult learning are directly applicable to engagement in OCOPs because they include practical methods founded on the belief that adults are self-directed, autonomous learners and that learning is most effective when the environment plays the role of a facilitator, rather than being just a supportive and traditional setting for learning. However, how individual adults engage in OCOPs and benefit from them is not well understood. This paper draws on social cognitive theory to examine: how environmental, personal and behavioural factors shape engagement in OCOPs. To answer this question, twenty-one interviews were conducted with members of GitHub, a large online community of practice for IT professionals. The findings revealed that adults’ engagement in OCOPs involves project-based activities on mutual interests and willingness to help others. The findings also show that engaging in online communities does not only satisfy intrinsic, well-defined, expected outcomes and shape adults’ engagement, but also has an impact on adults’ lifelong learning achievements, such as professional experience and credit recognition. Based on these findings, a revised framework for adults’ engagement in OCOPs is presented and discussed.

PiRATeMC: A highly flexible, scalable, and low-cost system for obtaining high quality video recordings for behavioral neuroscience

With the rapidly accelerating adoption of machine-learning based rodent behavioral tracking tools, there is an unmet need for a method of acquiring high quality video data that is scalable, flexible, and relatively low-cost. Many experimenters use webcams, GoPros, or other commercially available cameras that can be expensive, offer minimal flexibility of recording parameters, and not optimized for recording rodent behavior, leading to suboptimal and inconsistent video quality. Furthermore, commercially available products are not conducive for synchronizing multiple cameras, or interfacing with third-party equipment to allow time-locking of video to other equipment such as microcontrollers for closed-loop experiments. We present a low-cost, customizable ecosystem of behavioral recording equipment, PiRATeMC (Pi-based Remote Acquisition Technology for Motion Capture) based on Raspberry Pi Camera Boards with the ability to acquire high quality recordings in bright/low light, or dark conditions under infrared light. PiRATeMC offers users control over nearly every recording parameter, and can be fine-tuned to produce optimal videos in any behavioral apparatus. This setup can be scaled up for synchronous control of any number of cameras via a self-contained network without burdening institutional network infrastructure. The Raspberry Pi is an excellent platform with a large online community designed for novice and inexperienced programmers interested in using an open-source recording system. Importantly, PiRATeMC supports TTL and serial communication, allowing for synchronization and interfacing of video recording with behavioral or other third-party equipment. In sum, PiRATeMC minimizes the cost-prohibitive nature of conducting and analyzing high quality behavioral neuroscience studies, thereby increasing accessibility to behavioral neuroscience.

Don't worry, it won't be fine. Contributions of worry and anxious arousal to startle responses and event-related potentials in threat anticipation.

A widely shared framework suggests that anxiety maps onto two dimensions: anxious apprehension and anxious arousal. Previous research linked individual differences in these dimensions to differential neural response patterns in neuropsychological, imaging, and physiological studies. Differential effects of the anxiety dimensions might contribute to inconsistencies in prior studies that examined neural processes underlying anxiety, such as hypersensitivity to unpredictable threat. We investigated the association between trait worry (as a key component of anxious apprehension), anxious arousal, and the neural processing of anticipated threat. From a large online community sample (N = 1,603), we invited 136 participants with converging and diverging worry and anxious arousal profiles into the laboratory. Participants underwent the NPU-threat test with alternating phases of unpredictable threat, predictable threat, and safety, while physiological responses (startle reflex and startle probe locked event-related potential components N1 and P3) were recorded. Worry was associated with increased startle responses to unpredictable threat and increased attentional allocation (P3) to startle probes in predictable threat anticipation. Anxious arousal was associated with increased startle and N1 in unpredictable threat anticipation. These results suggest that trait variations in the anxiety dimensions shape the dynamics of neural processing of threat. Specifically, trait worry seems to simultaneously increase automatic defensive preparation during unpredictable threat and increase attentional responding to threat-irrelevant stimuli during predictable threat anticipation. The current study highlights the utility of anxiety dimensions to understand how physiological responses during threat anticipation are altered in anxiety and supports that worry is associated with hypersensitivity to unpredictable, aversive contexts.

Temporal Trends in Perceptions of Anti-tumor Necrosis Factor Risks and Benefits in an Online Community of Patients With Crohn's Disease.

Anti-tumor necrosis factor agents (anti-TNFs) have become one of the primary medical therapies for Crohn's disease (CD). We analyzed perceptions of infliximab and adalimumab in a large online community to better understand the information patients receive. Reddit, a vast online community, has several inflammatory bowel disease communities, the largest being /r/CrohnsDisease (rCD), with over 41,000 members. To better understand patient perceptions of biologics, we searched rCD for posts related to "infliximab," "adalimumab," and their relevant trade names. The top 20 yearly posts were extracted from 2011 to 2015 and 2011 to 2017, respectively. Manifest coding was performed. Codes were reassessed every 20 posts, resulting in 6 main sentiments. Total codes and per-comment codes were calculated for each sentiment. Percentages for each category were calculated by dividing by the total number of coded sentiments that year. Trends in rates of each sentiment were assessed using Spearman's correlation coefficients. 4486 comments were analyzed, and 4684 sentiments met our criteria. Negative sentiments decreased for both anti-TNFs over time (infliximab: rho=-0.90, P= .04, adalimumab: rho=-0.79, P= .04). In our primary analysis, adalimumab injection-related posts increased from 2012 to 2017 (rho= 0.83, P= .04). Positive sentiments and sentiments regarding drug costs, loss of efficacy, and diet remained stable. For infliximab and adalimumab, comment volume increased significantly over time (rho 0.90; P= .04, rho 0.89, P= .01). Our analysis of a large online community suggests a growing acceptance of biologic therapies among patients with CD over time. These data provide additional insight into the multifaceted framework shaping patients' perceptions of anti-TNFs.

Governing Generation Z in China: Bilibili, bidirectional mediation, and online community governance

The rise of large online communities in China has gone hand-in-hand with heavy regulation by the Chinese party-state. Caught between the party-state and demanding users, how do online platforms govern online communities to please both, and stay competitive against rivals? Drawing on public documents, interviews, and ethnographic observations, we study Bilibili, a leading online participatory platform for Generation Z. We argue that Bilibili has adopted a “bidirectional mediation” approach to actively mediate between users and the party-state. In this approach, the key to online governance is finding, or even cultivating, common grounds between users and the party-state and proactively facilitating communications between the two sides. We illustrate Bilibili’s bidirectional mediation through its Disciplinary Committee, an organization that enables users to participate in regulating online content on the Bilibili platform. The Bilibili case provides important insights into the evolution of online communities and state-society relations in China.

Administrator-users contribute more to online communities

Lack of user participation and contribution has been a long-standing problem for online communities. We proposed and examined new strategies for cultivating opinion leadership and enabling users to post articles outside of the community theme. We used social role theory to propose that online communities should encourage highly committed users to take administrator roles, which will increase their opinion leadership and contributions to both public spaces and their own user-controlled spaces. We collected multiple-wave and multiple-source data from 1,115 users of a large online community. The results indicate that encouraging users to take administrator roles increases their community contributions.

Digital disruption in a state-controlled ecosystem: A sociomaterial perspective of public use of the internet under China's Social Credit System

This paper draws from sociomateriality in explaining how digital user behavior may be shaped by private, individual users of the internet (“netizens”), and how this behavior can be understood as an enactment between social and technological agency. Based on observation of, and interviews with, netizens in a large city in China, we suggest how the design and performance of digital disruption by Chinese netizens reflects the sociomaterial values that embody a collectivist sense of social harmony under China's state-controlled Social Credit System. This research is original in its use of actual user behavior, which we observed in a sample of Chinese netizens. We explain how these netizens created commercial opportunities on the internet by building and marketing their personal profiles. Yet our netizens demonstrated how this opportunity-seeking behavior nonetheless aligned with state rules for maintaining social harmony. The importance of our findings is in the apparent duality of behavior among our sample of netizens who presented their commercial activities as socially harmonious while seeking to build followers and earning income from their online activities. The study contributes to understanding this user behavior by suggesting how netizens may build substantial identities in one of the world's largest online communities that remains politically constrained. Implications for research and governance are suggested in understanding digital user behavior in and beyond China.

"I got a bunch of weed to help me through the withdrawals": Naturalistic cannabis use reported in online opioid and opioid recovery community discussion forums.

A growing body of research has reported on the potential opioid-sparing effects of cannabis and cannabinoids, but less is known about specific mechanisms. The present research examines cannabis-related posts in two large online communities on the Reddit platform ("subreddits") to compare mentions of naturalistic cannabis use by persons self-identifying as actively using opioids versus persons in recovery. We extracted all posts mentioning cannabis-related keywords (e.g., "weed", "cannabis", "marijuana") from December 2015 through August 2019 from an opioid use subreddit and an opioid recovery subreddit. To investigate how cannabis is discussed at-scale, we identified and compared the most frequent phrases in cannabis-related posts in each subreddit using term-frequency-inverse document frequency (TF-IDF) weighting. To contextualize these findings, we also conducted a qualitative content analysis of 200 random posts (100 from each subreddit). Cannabis-related posts were about twice as prevalent in the recovery subreddit (n = 908; 5.4% of 16,791 posts) than in the active opioid use subreddit (n = 4,224; 2.6% of 159,994 posts, p < .001). The most frequent phrases from the recovery subreddit referred to time without using opioids and the possibility of using cannabis as a "treatment." The most frequent phrases from the opioid subreddit referred to concurrent use of cannabis and opioids. The most common motivations for using cannabis were to manage opioid withdrawal symptoms in the recovery subreddit, often in conjunction with anti-anxiety and GI-distress "comfort meds," and to enhance the "high" when used in combination with opioids in the opioid subreddit. Despite limitations in generalizability from pseudonymous online posts, this examination of reports of naturalistic cannabis use in relation to opioid use identified withdrawal symptom management as a common motivation. Future research is warranted with more structured assessments that examines the role of cannabis and cannabinoids in addressing both somatic and affective symptoms of opioid withdrawal.

Whose Advice is Credible? Claiming Lay Expertise in a Covid-19 Online Community.

During the initial months of the Covid-19 pandemic, credentialed experts—scientists, doctors, public health experts, and policymakers—as well as members of the public and patients faced radical uncertainty. Knowledge about how Covid-19 was spread, how best to diagnose the disease, and how to treat infected patients was scant and contested. Despite this radical uncertainty, however, certain users of Covid-19 Together, a large online community for those who have contracted Covid-19, were able to dispense advice to one another that was seen as credible and trustworthy. Relying on Goffman’s dramaturgical theory of social interaction, we highlight the performative dimension of claims to lay expertise to show how credibility is accrued under conditions of radical uncertainty. Drawing on four months of data from the forum, we show how credible performances of lay expertise necessitated the entangling of expert discourse with illness experience, creating a hybrid interlanguage. A credible performance of lay expertise in this setting was characterized by users' ability to switch freely between personal and scientific registers, finding and creating resonances between the two. To become a credible lay expert on this online community, users had to learn to ask questions and demonstrate a willingness to engage with biomedical knowledge while carefully generalizing their personal experience.

Community Resilience in Belarus and the EU response

Community Resilience in Belarus and the EU response

O-105 High prevalence of obesity and polycystic ovary syndrome in an online community seeking assistance with fertility

Abstract Study question What are the characteristics of a large online community of women trying to conceive and what are the factors that predict infertility in this group? Summary answer The cohort was not characterized by increased age, though age, obesity and PCOS strongly correlated with fertility. PCOS may be under-recognized within some ethnic groups. What is known already Obesity, polycystic ovary syndrome (PCOS), and age are among the primary predictors of infertility in women. However, most studies assessing reproductive health employ populations who have sought medical assistance for infertility or associated disorders, potentially leading to populations more likely to exhibit disorders such as PCOS or to be of increased age. Characterization of factors affecting fertility in a general population may highlight epidemiological influences that should be better addressed to aid women trying to conceive. Study design, size, duration This study employed users of the mobile application, FertilityAnswers, for people searching for answers to fertility problems. Users answered a short survey describing themselves, their fertility history and goals. Recruitment for this study began in March 2017 and ended in January 2021. 61814 participants downloaded the application during this period, and 56878 at least provided their age. The primary inclusion criteria were that study participants be US females over eighteen years of age. Participants/materials, setting, methods Regression models estimated beta coefficients and corresponding confidence intervals. Multivariable models determined independence of variables. To model PCOS, the available data in January 2020 was split randomly into discovery and validation subsets. Missing value imputation using random forests was performed in the discovery dataset. Minimal feature selection used a linear regression model penalized with a lasso and elastic net. The model was then validated on samples collected after the model was trained and tested. Main results and the role of chance Age was a significant predictor of fertility in this study (p &amp;lt; 1x10-10). However, the distribution of age in the cohort was very similar to that of women at first birth in the United States, therefore we did not observe the majority of study participants to be of an age where in a typical clinical setting age-related concerns would be addressed (i.e., approaching 35 years). Using National Center for Health Statistics data, the mean age of 1,433,604 women at first birth in 2018 in the US was younger than the study population (restricted to those without children) by only one month. Obesity was of increased prevalence in this cohort, with 55% being obese, compared to 37% in an age-matched US population. Participants reported a variety of fertility-related disorders, with polycystic ovary syndrome (PCOS) being most prevalent (19.0%), followed by endometriosis (6.0%). Prediction of PCOS, performed by modeling on training and test sets (10476 and 5312 participants) and then validating with an additional 21097 participants collected after the model creation, found that African-Americans and Latino members of this cohort had a lower self-reported rate of the disorder than was anticipated by the model, in contrast to those of Asian or European descent. Limitations, reasons for caution All health data was self-reported. Additionally, as this is the initial survey of this population, no a priori hypotheses were made as to the expected relationships to be observed. Instead, all associations were examined, and measurements of false discovery rate were estimated. Wider implications of the findings We found that women were seeking answers about infertility at ages coincident with that of their peers achieving first pregnancies. ART is often not a first-line treatment for women of this age, but there may be a disconnect between traditional clinical response to this group and their desire for assistance. Trial registration number not applicable

4chan and /b/: An Analysis of Anonymity and Ephemerality in a Large Online Community

We present two studies of online ephemerality and anonymity based on the popular discussion board /b/ at 4chan.org: a website with over 7 million users that plays an influential role in Internet culture. Although researchers and practitioners often assume that user identity and data permanence are central tools in the design of online communities, we explore how /b/ succeeds despite being almost entirely anonymous and extremely ephemeral. We begin by describing /b/ and performing a content analysis that suggests the community is dominated by playful exchanges of images and links. Our first study uses a large dataset of more than five million posts to quantify ephemerality in /b/. We find that most threads spend just five seconds on the first page and less than five minutes on the site before expiring. Our second study is an analysis of identity signals on 4chan, finding that over 90% of posts are made by fully anonymous users, with other identity signals adopted and discarded at will. We describe alternative mechanisms that /b/ participants use to establish status and frame their interactions.

Social Support and Well-being among Relocating Women: The Mediating Roles of Resilience and Optimism

The relative lack of research on the relocation of women to foreign assignments prompted this study that focused on a large online community of women in relocation. We examined the relationship between two support types, perceived social support (PSS) and online support, and well-being measures (meaning in life, depression, and loneliness) in the new setting. Based on the literature, we hypothesized that (a) PSS and online support positively relate to personal resilience and optimism, (b) resilience and optimism positively associate with well-being levels, and (c) resilience and optimism mediate the association between both types of support and well-being. Two waves of data (T1 & T2) were collected in the current study. The results largely reflected the propositions, with some deviations from the expected model, and indicated that resilience was the more prominent mediator at both T1 and T2. A complex pattern of relationships was documented between various types of virtual support and well-being. Women who received social support could foster a positive, optimistic future perspective experience and an increased sense of meaning in their lives. This study engendered implications for organizations’ appropriate preparation of relocating staff, in general, and the relocation of women employees, in particular.

Entrepreneurial learning in online communities

New digital technologies possess the potential to transform entrepreneurial processes, such as how entrepreneurs pursue opportunities and access funding and how they learn. How entrepreneurs learn may be transformed as digital technologies provide new spaces for learning, such as online communities. Online communities can gather thousands of participants and provide entrepreneurs with new opportunities for learning that are not limited by time, space, or social class. Yet, we know little about how entrepreneurs take advantage of the new digital opportunities of learning. To remedy this, we studied a large online community of entrepreneurs on Reddit (r/startups), where we qualitatively analyzed the top-voted 100 threads from 2018 to 2019 (10,277 comments in total). By drawing on coactive vicarious learning, a theory that describes how learning is socially constructed through discursive interactions, we outline how entrepreneurial learning is socially constructed through conversations, which are taking place in different micro-learning contexts. Through identifying distinct entrepreneurial learning conversations, we build new theory on entrepreneurial learning in online communities. Our theorizing contributes to (1) the growing research on how entrepreneurial learning is socially constructed in communities, (2) the current debate on knowledge creation in online communities, and (3) the knowledge on how coactive vicarious learning unfolds in communities.Plain English SummaryWhen entrepreneurs go online to learn, new research shows how online communities provide entrepreneurs with diverse learning spaces for developing ideas, learning new skills, and coping with the uncertainties of being an entrepreneur. Entrepreneurs increasingly use social media for doing business, but can they also use it to learn about doing business? In this article, we investigate this question by studying an online community of entrepreneurs on Reddit called r/startups, in which entrepreneurs exchange experiences and help each other with questions and issues. We show that entrepreneurial learning is taking place in five forms of learning conversations, which are situated in four learning contexts that differ from each other, from a classroom with a student–teacher dynamic, a collab space where entrepreneurs collect ideas and develop new skills and knowledge, a club context in which they challenge each other, and a care context in which they can bring their fears and uncertainties. Our findings show how entrepreneurship practitioners can make use of online communities, encouraging teaching and policy to pay more attention to how entrepreneurs work digitally.