More Like this

1. What Makes Online Communities ‘Better’? Measuring Values, Consensus, and Conflict across Thousands of Subreddits

   https://doi.org/10.1609/icwsm.v16i1.19363  

   Weld, Galen ; Zhang, Amy X. ; Althoff, Tim ( June 2022 , Proceedings of the International AAAI Conference on Web and Social Media)

   Making online social communities ‘better’ is a challenging undertaking, as online communities are extraordinarily varied in their size, topical focus, and governance. As such, what is valued by one community may not be valued by another.However, community values are challenging to measure as they are rarely explicitly stated.In this work, we measure community values through the first large-scale survey of community values, including 2,769 reddit users in 2,151 unique subreddits. Through a combination of survey responses and a quantitative analysis of publicly available reddit data, we characterize how these values vary within and across communities.Amongst other findings, we show that community members disagree about how safe their communities are, that longstanding communities place 30.1% more importance on trustworthiness than newer communities, and that community moderators want their communities to be 56.7% less democratic than non-moderator community members.These findings have important implications, including suggesting that care must be taken to protect vulnerable community members, and that participatory governance strategies may be difficult to implement.Accurate and scalable modeling of community values enables research and governance which is tuned to each community's different values. To this end, we demonstrate that a small number of automatically quantifiable features capture a significant yet limited amount of the variation in values between communities with a ROC AUC of 0.667 on a binary classification task.However, substantial variation remains, and modeling community values remains an important topic for future work.We make our models and data public to inform community design and governance. 

   more » « less
2. Differential Overlap in Human and Animal Fecal Microbiomes and Resistomes in Rural versus Urban Bangladesh

   https://doi.org/10.1128/aem.00759-22  

   Swarthout, Jenna M. ; Fuhrmeister, Erica R. ; Hamzah, Latifah ; Harris, Angela R. ; Ahmed, Mir A. ; Gurley, Emily S. ; Satter, Syed M. ; Boehm, Alexandria B. ; Pickering, Amy J. ( July 2022 , Applied and Environmental Microbiology)

   Elkins, Christopher A. (Ed.)

   ABSTRACT Low- and middle-income countries (LMICs) bear the largest mortality burden of antibiotic-resistant infections. Small-scale animal production and free-roaming domestic animals are common in many LMICs, yet data on zoonotic exchange of gut bacteria and antibiotic resistance genes (ARGs) in low-income communities are sparse. Differences between rural and urban communities with regard to population density, antibiotic use, and cohabitation with animals likely influence the frequency of transmission of gut bacterial communities and ARGs between humans and animals. Here, we determined the similarity in gut microbiomes, using 16S rRNA gene amplicon sequencing, and resistomes, using long-read metagenomics, between humans, chickens, and goats in a rural community compared to an urban community in Bangladesh. Gut microbiomes were more similar between humans and chickens in the rural (where cohabitation is more common) than the urban community, but there was no difference for humans and goats in the rural versus the urban community. Human and goat resistomes were more similar in the urban community, and ARG abundance was higher in urban animals than rural animals. We identified substantial overlap of ARG alleles in humans and animals in both settings. Humans and chickens had more overlapping ARG alleles than humans and goats. All fecal hosts from the urban community and rural humans carried ARGs on chromosomal contigs classified as potentially pathogenic bacteria, including Escherichia coli , Campylobacter jejuni , Clostridioides difficile , and Klebsiella pneumoniae . These findings provide insight into the breadth of ARGs circulating within human and animal populations in a rural compared to urban community in Bangladesh. IMPORTANCE While the development of antibiotic resistance in animal gut microbiomes and subsequent transmission to humans has been demonstrated in intensive farming environments and high-income countries, evidence of zoonotic exchange of antibiotic resistance in LMIC communities is lacking. This research provides genomic evidence of overlap of antibiotic resistance genes between humans and animals, especially in urban communities, and highlights chickens as important reservoirs of antibiotic resistance. Chicken and human gut microbiomes were more similar in rural Bangladesh, where cohabitation is more common. Incorporation of long-read metagenomics enabled characterization of bacterial hosts of resistance genes, which has not been possible in previous culture-independent studies using only short-read sequencing. These findings highlight the importance of developing strategies for combatting antibiotic resistance that account for chickens being reservoirs of ARGs in community environments, especially in urban areas. 

   more » « less
3. Integrated community occupancy models: A framework to assess occurrence and biodiversity dynamics using multiple data sources

   https://doi.org/10.1111/2041-210X.13811  

   Doser, Jeffrey W. ; Leuenberger, Wendy ; Sillett, T. Scott ; Hallworth, Michael T. ; Zipkin, Elise F. ( February 2022 , Methods in Ecology and Evolution)

   1. The occurrence and distributions of wildlife populations and communities are shifting as a result of global changes. To evaluate whether these shifts are negatively impacting biodiversity processes, it is critical to monitor the status, trends and effects of environmental variables on entire communities. However, modelling the dynamics of multiple species simultaneously can require large amounts of diverse data, and few modelling approaches exist to simultaneously provide species and community‐level inferences.

   2. We present an ‘integrated community occupancy model’ (ICOM) that unites principles of data integration and hierarchical community modelling in a single framework to provide inferences on species‐specific and community occurrence dynamics using multiple data sources. The ICOM combines replicated and nonreplicated detection–nondetection data sources using a hierarchical framework that explicitly accounts for different detection and sampling processes across data sources. We use simulations to compare the ICOM to previously developed hierarchical community occupancy models and single species integrated distribution models. We then apply our model to assess the occurrence and biodiversity dynamics of foliage‐gleaning birds in the White Mountain National Forest in the northeastern USA from 2010 to 2018 using three independent data sources.

   3. Simulations reveal that integrating multiple data sources in the ICOM increased precision and accuracy of species and community‐level inferences compared to single data source models, although benefits of integration were dependent on the information content of individual data sources (e.g. amount of replication). Compared to single species models, the ICOM yielded more precise species‐level estimates. Within our case study, the ICOM had the highest out‐of‐sample predictive performance compared to single species models and models that used only a subset of the three data sources.

   4. The ICOM provides more precise estimates of occurrence dynamics compared to multi‐species models using single data sources or integrated single‐species models. We further found that the ICOM had improved predictive performance across a broad region of interest with an empirical case study of forest birds. The ICOM offers an attractive approach to estimate species and biodiversity dynamics, which is additionally valuable to inform management objectives of both individual species and their broader communities.

    

   more » « less
4. Social capital dimensions are differentially associated with COVID-19 vaccinations, masks, and physical distancing

   https://doi.org/10.1371/journal.pone.0260818  

   Ferwana, Ibtihal ; Varshney, Lav R. ( December 2021 , PLOS ONE)

   Patel, Sanjay Kumar (Ed.)

   Background Social capital has been associated with health outcomes in communities and can explain variations in different geographic localities. Social capital has also been associated with behaviors that promote better health and reduce the impacts of diseases. During the COVID-19 pandemic, social distancing, face masking, and vaccination have all been essential in controlling contagion. These behaviors have not been uniformly adopted by communities in the United States. Using different facets of social capital to explain the differences in public behaviors among communities during pandemics is lacking. Objective This study examines the relationship among public health behavior—vaccination, face masking, and physical distancing—during COVID-19 pandemic and social capital indices in counties in the United States. Methods We used publicly available vaccination data as of June 2021, face masking data in July 2020, and mobility data from mobile phones movements from the end of March 2020. Then, correlation analysis was conducted with county-level social capital index and its subindices (family unity, community health, institutional health, and collective efficacy) that were obtained from the Social Capital Project by the United States Senate. Results We found the social capital index and its subindices differentially correlate with different public health behaviors. Vaccination is associated with institutional health: positively with fully vaccinated population and negatively with vaccination hesitancy. Also, wearing masks negatively associates with community health, whereases reduced mobility associates with better community health. Further, residential mobility positively associates with family unity. By comparing correlation coefficients, we find that social capital and its subindices have largest effect sizes on vaccination and residential mobility. Conclusion Our results show that different facets of social capital are significantly associated with adoption of protective behaviors, e.g., social distancing, face masking, and vaccination. As such, our results suggest that differential facets of social capital imply a Swiss cheese model of pandemic control planning where, e.g., institutional health and community health, provide partially overlapping behavioral benefits. 

   more » « less
5. Using Social Network Analysis to Study the Social Structures of Inclusion

   Pearson, Nelson ; Major, Justin ; Godwin, Allison ; Kirn, Adam ( January 2018 , ASEE annual conference & exposition)

   The purpose of this research paper is to understand how diverse students are incorporated into the social structure of a large enrollment first-year engineering design course. Despite previous work demonstrating the benefits of diverse individuals in engineering, little work has examined how diverse students are incorporated into the social networks that exist within engineering classrooms. Social interactions are one of the most influential sources for integration into communities of practice. Through understanding how students interact and the structure of these interactions, we can elucidate how the engineering community includes members of underrepresented populations. Previous social network analysis (SNA) studies have scrutinized student classroom interactions. These studies typically attempt to link classroom interactions to academic outcomes (i.e., grades). In this study, we start to shift the focus away from connecting student interactions to academic outcomes and examine how the structure of student interactions can encourage an inclusive environment in a formal engineering environment. SNA data was collected via an online survey (n = 502, 74% response rate) one month into the semester at a Western land-grant institution. The survey asked first-year engineering students to indicate with whom they had interacted using a pre-populated list of the class roster and open-ended questions. The number of students that were mentioned by a participant (out-degree) is interpreted as a proxy of their sociableness. Whereas, the number of times a student was mentioned by others (in-degree) is interpreted as popularity. We posit that in an inclusive network structure the social behaviors (i.e., in and out-degree) will be independent of students’ demographic characteristics (e.g., race and gender). Nonparametric hypothesis testing (i.e., Kruskal-Wallis and Dunn’s test) was used to investigate the effects of gender and race on both in and out-degree. Results indicate that the social structure of the first-year engineering community is inclusive of both gender and race. Specifically, results indicated no significant differences for in-degree based on measures of race and gender, for students who provided race and gender information. Out-degree was not significantly different based on race. However, women did demonstrate significantly higher out-degree scores (i.e., greater sociableness) than their peers. Building on previous SNA literature, the increased connections expressed by women may lead to increased learning gains or performance within engineering. Results indicated that the social structure of this first-year engineering course, as indicated by in-degree and out-degree, is not significantly different for underrepresented groups. This result begins to illustrate a more complex story than the existing literature has documented of engineering as an unwelcoming environment for underrepresented students. Future work will explore how these structures do or do not persist over time and how individuals develop attitudes towards diverse individuals as a result of these interactions. We hope that the results of this work will provide practical ways to improve engineering climate for underrepresented students. 

   more » « less