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Understanding social relationships and organization in colonial bat species can provide valuable insight into species ecology and potentially aid in conservation efforts of rare bat species. We applied social network analysis to describe social relationships and organization in 3 colonies of Rafinesque's big-eared bats {Corynorhinus rafinesquU) roosting in bottomland hardwood forests in Kentucky. We radiotracked 48 adult big-eared bats to 64 day-roosts over 549 bat-days during the summers of 2009-2011. We measured homophily, network centralization, density, transitivity, and core-periphery structure of networks of bats sharing common roosts, and we measured degree centrality of nodes (bats or roosts) within networks. Pattems of ties within each colony were homophilous by sex (E-I index = -0.87). Males were consistently the least central nodes in bat networks. Bat network centralization ranged from 1.2% to 40% among colonies, and roost network centralization ranged from 17% to 40%. The colony exhibiting the least centralized and most dense bat network also occupied habitat with low roost availability. This roost network was highly centralized, with bats frequently aggregating at a single roost. The colony with the most centralized and least dense bat network occupied habitat with a greater availability of roosts, resulting in diffuse networks of bats and roosts. Transitivity decreased after young became volant in the colony with highest roost availability. Our findings suggest that social structure in colonies of Rafinesque's big-eared bats is affected by the sex of individuals in colonies, reproductive season, and tbe preponderance of available day-roosting habitat.

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Collective feedback can support an individual's decision-making process. For instance, individuals often seek the advice of friends, family, and co-workers to help them make privacy decisions. However, current technologies often do not provide mechanisms for this type of collaborative interaction. To address this gap, we propose a novel model of Community Oversight for Privacy and Security ("CO-oPS"), which identifies mechanisms for users to interact with people they trust to help one another make digital privacy and security decisions. We apply our CO-oPS model in the context of mobile applications ("apps"). To interrogate and refine this model, we conducted participatory design sessions with 32 participants in small groups of 2-4 people who know one another, with the goal of designing a mobile app that facilitates collaborative privacy and security decision-making. We describe and reflect on the opportunities and challenges that arise from the unequal motivation and trust in seeking support and giving support within and beyond a community. Through this research, we contribute a novel framework for collaborative digital privacy and security decision-making and provide empirical evidence towards how researchers and designers might translate this framework into design-based features.

Older adults are increasingly becoming adopters of digital technologies, such as smartphones; however, this population remains particularly vulnerable to digital privacy and security threats. To date, most research on technology used among older adults focuses on helping individuals overcome their discomfort or lack of expertise with technology to protect them from such threats. Instead, we are interested in how communities of older adults work together to collectively manage their digital privacy and security. To do this, we surveyed 67 individuals across two older adult communities (59 older adults and eight employees or volunteers) and found that the community's collective efficacy for privacy and security was significantly correlated with the individuals' self-efficacy, power usage of technology, and their sense of community belonging. Community collective efficacy is a group's mutual belief in its ability to achieve a shared goal. Using social network analysis, we further unpacked these relationships to show that many older adults interact with others who have similar technological expertise, and closer-knit older adult communities that have low technology expertise (i.e., low power usage and self-efficacy) may increase their community collective efficacy for privacy and security by embedding facilitators (e.g., employees or volunteers) who have more technical expertise within their communities. Our work demonstrates how both peer influence and outside expertise can be leveraged to support older adults in managing their digital privacy and security.