Professional Peer Support in Online Health Communities

This paper investigates whether and what kind of social support exchange in Professional-only Online Health Communities (POHC). Focusing on the recent fast-growing outbreak—Coronavirus Disease 2019 (COVID-19)— we find that healthcare professionals benefit from peer social support in POHCs, particularly by exchanging emotional support and learning from collective experience-based knowledge. Using the Reddit/r/medicine data, we show that posts’ popularity varies depending on the authors’ emotions and informativeness. In particular, a post’s negative emotion and narrative tone have a significant and positive association with the post’s popularity. These findings speak to the important role of POHC associated with healthcare professionals’ integrity during the pandemic

Can Social Disconnectedness Inhibit Online Trade? Examining the Effects of Digital Distance on Peer-to-peer Lending

The extant literature has shown that offline group proximity manifests in online peer-to-peer lending platforms, inhibiting online transactions in those markets. The findings of this research suggest that digital distance, as measured by the rate of Facebook friendship between country pairs, can also influence lending actions in bi-country lending. Building on a dataset from Kiva.org, we show that digital distance significantly and negatively affects bi-country lending actions, on top of other distance-related barriers discussed in the literature. The results also shed light on the role of government policies regarding local IT infrastructure and Internet freedom, revealing that greater levels of IT infrastructure and Internet freedom can compensate for the negative effect of digital distance on prosocial lending

An Improved Continuous-Action Extended Classifier Systems for Function Approximation

AbstractDue to their structural simplicity and superior generalization capability, Extended Classifier Systems (XCSs) are gaining popularity within the Artificial Intelligence community. In this study an improved XCS with continuous actions is introduced for function approximation purposes. The proposed XCSF uses “prediction zones,” rather than distinct “prediction values,” to enable multi-member match sets that would allow multiple rules to be evaluated per training step. It is shown that this would accelerate the training procedure and reduce the computational cost associated with the training phase. The improved XCSF is also shown to produce more accurate rules than the classical classifier system when it comes to approximating complex nonlinear functions

The Role of Religion in Online Prosocial Lending

The Internet has long been argued to have “flattened” the world. A variety of work, however, has shown that cross-border frictions continue to manifest through various individual level differences, e.g., cultural, demographic, and geographic. We extend this literature here, offering a novel consideration of religious differences as a significant barrier to online peer-to-peer transactions in the context of prosocial lending. Specifically, we propose a measure of religious distance between any given pair of countries. We then incorporate this measure into a standard gravity model of trade, which we use to explain country-to-country lending volumes between 2006 and 2017 at kiva.org. We demonstrate the negative and significant effects of religious differences on lending activity over and above other established factors. Moreover, we demonstrate that the effects of religious differences vary a great deal, being moderated by the social environment characterizing both a lender country and borrower country in a given time period. That is, we show that increases in the degree of social hostilities within a lender country amplifies the baseline (negative) effects of religious differences on lending activity. At the same time, we demonstrate that diversity of religion and greater physical distances attenuate the role of religious differences

Design and Fabrication of a Universal Soft Gripper

Inspired from nature, soft robots capable of actively tuning their mechanical rigidity can rapidly transition between a broad range of motor tasks, from lifting heavy loads to dexterous manipulation of delicate objects. Reversible rigidity tuning also enables soft roboticactuators to reroute their internal loading and alter their mode of deformation in response to intrinsic activation. In this study, we demonstrate this principle with a three-fingered pneumatic gripper that contains programmable ligaments that change stiness when activated with electrical current. The ligaments are composed of a conductive thermoplastic elastomer composite that reversibly softens under resistive heating. Depending on which ligaments are activated, the gripper will bend inward to pick up an object, bend laterally totwist it, or bend outward to release it.Each finger consists of three PDMS phalanges that are attached with two Ecoflex joints. Three ligaments (strips of a cPBE-PDMS composite layer) are attached along the finger and are stimulated with electricity individually. When the high pressure air is injected inthe hollow middle part of the finger, the finger will be bent in the opposite direction of the stimulated cPBE-PDMS element (softer wall). This enables the gripper’s fingers to grab and twist objects with dierent sizes and shapes.All of the gripper motions are generated with a single pneumatic source of pressure and are controlled with an electrical board. The ability to incorporate electrically programmable ligaments in pneumatic or hydraulic actuators has the potential to enhance versatility andreduce dependency on tubing and valves. In this study, an activation/deactivation cycle can be completed within 15 s

People Don\u27t Change, Their Priorities Do: Evidence of Value Homophily for Disaster Relief

Earlier studies on crowdfunding markets show that a crisis increases the charitable funding for people affected by the crisis. However, these studies fail to explain whether such an increase is purely because of the awareness of need, or, otherwise, there are some behavioral mechanisms associated with disaster relief fundraising. To address this gap, we theoretically and empirically explore the role of value homophily in shifting lending priorities in online prosocial platforms. Considering the full spectrum of cultural influences, we develop the concept of culturalist choice homophily, where value-based similarities emerge based on the culturally-motivated behaviors and historicist choice homophily, where value-based similarities emerge based on similarities in historical-cultural barriers. We hinge on the Arab Spring crisis in a Difference-in-Difference (DID) setting to test our hypotheses. We show that the Arab Spring crisis increased charitable funding from lenders with high emancipative values and similar colonial histories

Putting Religious Bias in Context: How Offline and Online Contexts Shape Religious Bias in Online Prosocial Lending

Biases on online platforms pose a threat to social inclusion. We examine the influence of a novel source of bias in online philanthropic lending, namely that associated with religious differences. We first propose religion distance as a probabilistic measure of differences between pairs of individuals residing in different countries. We then incorporate this measure into a gravity model of trade to explain variation in country-to-country lending volumes. We further propose a set of contextual moderators that characterize individuals’ offline (local) and online social contexts, which we argue combine to determine the influence of religion distance on lending activity. We empirically estimate our gravity model using data from Kiva.org, reflecting all lending actions that took place between 2006 and 2017. We demonstrate the negative and significant effect of religion distance on lending activity, over and above other established factors in the literature. Further, we demonstrate the moderating role of lenders’ offline social context (diversity, social hostilities, and governmental favoritism of religion) on the aforementioned relationship to online lending behavior. Finally, we offer empirical evidence of the parallel role of online contextual factors, namely those related to community features offered by the Kiva platform (lending teams), which appear to amplify the role of religious bias. In particular, we show that religious team membership is a double-edged sword that has both favorable and unfavorable consequences, increasing lending in general but skewing said lending toward religiously similar borrowers. Our findings speak to the important frictions associated with religious differences in individual philanthropy; they point to the role of governmental policy vis-à-vis religious tolerance as a determinant of citizens’ global philanthropic behavior, and they highlight design implications for online platforms with an eye toward managing religious bias