Nostalgia, Social Media, and Subjective Wellbeing: The Dualistic and Conditional Effects of Nostalgia During the COVID-19 Pandemic.

Drastic lifestyle changes due to the COVID-19 pandemic have caused many people to undergo nostalgic longing for the past. Drawing on the regulatory model of nostalgia, we built a research model to examine the dualistic effects of nostalgia on subjective wellbeing, using self-continuity as a mediator and social media use as a moderator. The findings from an online survey (N = 373) indicated that when nostalgia is associated with an enhanced sense of self-continuity, it has a positive indirect effect on subjective wellbeing. In contrast, when not mediated by such a restorative function, nostalgia has a direct negative impact on subjective wellbeing. Both of these (positive) indirect and (negative) direct effects were moderated by social media usage, suggesting that social media use is a crucial communication-related boundary condition that reinforces or mitigates the dualistic effects of nostalgia. This study offers contributions to the literature by uncovering distinct pathways through which nostalgia carries differing implications for subjective wellbeing in times of crisis, as well as by identifying social media use as a boundary condition under which such dualistic roles of nostalgia manifest.

The bright and dark sides of social media use during COVID-19 lockdown: Contrasting social media effects through social liability vs. social support.

There exist ongoing discussions regarding whether, when, or why heightened reliance on social media becomes benefits or drawbacks, especially in times of crisis. Using the concepts of social liability, social support, and cognitive appraisal theory, this study examines distinct theoretical pathways through which the relational use of social media has contrasting impacts on cognitive appraisals of and emotional responses to the COVID-19 lockdown. We collected online survey data from 494 social media users in the U.S. during the COVID-19 lockdown. The results based on structural equation modeling (SEM) showed double-edged social media effects. When social media use results in perceived social support, it has a favorable impact on coping appraisals of the COVID-19 lockdown. This, in turn, is associated with lower levels of negative affective responses, such as anger, anxiety, and loneliness. In contrast, when social media use results in increased social liability (i.e., obligation to provide support to others), it negatively impacts cognitive appraisals and affective responses. The study makes significant contributions by unpacking two distinct theoretical mechanisms underlying social media effects: particularly social liability which has been underexplored but was found to be an essential concept to explain the dualistic impact of social media.

The role of uncertainty and affect in decision-making on the adoption of AI-based contact-tracing technology during the COVID-19 pandemic.

Objective: This study explores how negative affect, perceived net equity, and uncertainty influence the public's privacy decision-making regarding the adoption of contact-tracing technology based on artificial intelligence (AI) during the COVID-19 pandemic. Methods: Four hundred and eighteen adults in the US participated in the study via Amazon Mechanical Turk in August 2020. Statistical analyses were performed using the PROCESS macro. Indirect effects and their significance were estimated using bias-corrected bootstrap confidence intervals (CIs) with resampling set to n = 5000. Results: Perceived net equity was positively associated with low levels of perceived uncertainty regarding a COVID-19 contact-tracing application and intention to adopt it. Low levels of perceived uncertainty were positively associated with intentions to adopt such an application, thereby suggesting that a perceived level of uncertainty mediates the association between perceived net equity and adoption intentions. Anxieties regarding AI technology and COVID-19 risks both moderate the associations among perceived net equity, perceived level of uncertainty, and intentions to adopt the contact-tracing technology. Conclusions: Our findings highlight how the differing sources of emotion influence the associations among rational judgment, perceptions, and decision-making about new contact-tracing technology. Overall, the results suggest that both rational judgments and affective reactions to risks are important influencers of individuals' perceptions and privacy-related decision-making regarding a new health technology during the pandemic.

The Role of Moral Foundations, Anticipated Guilt and Personal Responsibility in Predicting Anti-consumption for Environmental Reasons.

In response to the growing importance of environmental issues, more and more consumers are turning to anti-consumption by reducing, rejecting, or avoiding consumption. Covering the intersection of sustainable consumption and anti-consumption, previous studies relied on socio-cognitive models to explain this decision. In order to extend their findings, we consider the moral and emotional perspectives to examine reducing consumption for environmental reasons in a particular context, i.e. air travel. It is against this backdrop that we propose a conceptual model that includes moral foundations as the main antecedent, followed by anticipated guilt and personal responsibility, while intention to reduce consumption (i.e. air travel) for environmental reasons, positive word of mouth about reducing air travel (WOM) and environmental activism represent the outcomes. The proposed model is tested on a sample of 511 respondents from a UK online consumer panel. Our results confirm the importance of moral foundations, anticipated guilt and personal responsibility and their interplay in the prediction of intention to reduce consumption for environmental reasons. Anticipated guilt influences WOM, while personal responsibility influences activism. In addition, intentions to reduce consumption for environmental reasons have a positive impact on WOM and environmental activism. There are several implications for public policy makers and NGOs that fight against climate change that derive from these findings, as well as research opportunities for academics interested in this topic.

Privacy Management and Health Information Sharing via Contact Tracing during the COVID-19 Pandemic: A Hypothetical Study on AI-Based Technologies.

In this study, we extended and tested the privacy calculus framework in the context of a hypothetical AI-based contact-tracing technology for application during the COVID-19 pandemic that is based on the communication privacy management and contextual integrity theories. Specifically, we investigated how the perceived privacy risks and benefits of information disclosure affect the public's willingness to opt in and adopt contact-tracing technologies and how social and contextual factors influence their decision-making process. Four hundred eighteen adults in the United States participated in the study via Amazon Mechanical Turk in August 2020. A percentile bootstrap method with 5,000 resamples and bias-corrected 95% confidence intervals in structural equation modeling was used for data analysis. The participants' privacy concerns and perceived benefits significantly influenced their opt-in and adoption intentions, which suggests that the privacy calculus framework applies to the context of COVID-19 contact-tracing technologies. Perceived social, personal, and reciprocal benefits were identified as crucial mediators that link contextual variables to both opt-in and adoption intentions. Although this study was based on a hypothetical AI-based contact-tracing app, our findings provide meaningful theoretical and practical implications for future research investigating the public's technology adoption in contexts where tradeoffs between privacy risks and public health coexist.

(In)consistency matters: An account of understanding the perception of inconsistent expressions on social media.

In their daily use of social media, most people cannot maintain consistency in every message they present, leading observers to experience a feeling of inconsistency. Building on computer-mediated interpersonal theories [i.e., attribution theory, warranting theory, and authenticity model of computer-mediated communication (CMC)], this study aims to explore how people interpret and reconcile perceived inconsistent expressions on social media. Through thematic analysis of data obtained from six focus groups, two main themes were extracted: the origin of perceived inconsistency on social media and the strategies for reconciling perceived inconsistency. Specifically, three forms of perceived inconsistent information were identified: those within the same account; those between public and private accounts; and those between online and offline settings. Additionally, three types of reconciliation strategies were distilled from participants' narratives: relying on authentic representation; engaging in perspective-taking to compensate for situational factors; and inferring inner motives behind acting inconsistently. With these two themes, this study proposes a two-stage model of processing inconsistency (i.e., reasoning from inconsistency to consistency) in CMC. This model suggests that several factors-including perceived authenticity, social categorical cues, and relationship or familiarity between observers and a presenter-are involved in perceiving inconsistent information and determine the outcomes of interpersonal evaluations. These findings enhance our understanding of online interpersonal perceptions.

First Impression Formation Based on Valenced Self-Disclosure in Social Media Profiles.

This study aims to understand how the valence of self-disclosure (operationalized as the dominantly positive vs. balanced vs. dominantly negative social media posts of a future collaborator) influences first impression formation on social media. We also focus on trustworthiness as a mediator and perceived homophily as a moderator to specify the underlying mechanisms through which self-disclosure valence affects first impression formation. The results from an online experiment (N = 204) suggest that self-disclosure valence has a significant effect on perceived trustworthiness and likability when individuals evaluate an unknown future collaborator using the social media profile. Trustworthiness mediates the effect of self-disclosure valence on likability when the individuals feel that they are dissimilar or even slightly similar to strangers. At that time, individuals tend to seek cues from both self-disclosure valence and perceived homophily to form the trustworthiness perception, and the influence of self-disclosure depends on the level of perceived homophily.

Optimistic bias about H1N1 flu: testing the links between risk communication, optimistic bias, and self-protection behavior.

Using two-wave panel survey data (N = 348) collected in South Korea in the context of H1N1 flu, we explored several important aspects of optimistic bias that have been relatively unexplored in previous research, including: (a) the extent to which risk communication and indirect risk experience affect changes in optimistic bias over time; (b) the utility of the concept of optimistic bias to predict subsequent risk behavior; and (c) how optimistic bias moderates the effect of risk communication and indirect risk experience on self-protection behavior. The findings revealed that optimistic bias is rather enduring and resilient, as it changed only under one condition (high indirect risk experience combined with low interpersonal communication). Optimistic bias had a nonsignificant association with self-protection behavior, but played an important moderating role by reducing the effect of interpersonal communication on self-protection behavior.

A social network contagion theory of risk perception.

Risk perceptions have, to a great extent, been studied exclusively as individual cognitive mechanisms in which individuals collect, process, and form perceptions as atomized units unconnected to a social system. These individual-level theories do not, however, help explain how perception of risk may vary between communities or within a single community. One alternative approach is based on a network theory of contagion. This approach, emerging largely from organizational and community social network studies, suggests that it is the relational aspects of individuals and the resulting networks and self-organizing systems that influence individual perceptions and build "groups or communities of like-minded" individuals. These social units, it is argued, behave as attitude, knowledge, or behavioral structures. The study reported in this article tests one aspect of this theoretical perspective. The central hypothesis proposes the existence of risk perception networks--relational groupings of individuals who share, and perhaps create, similar risk perceptions. To test this idea, data were collected from individuals involved in a community environmental conflict over a hazardous waste site cleanup. The statistical analysis used a matrix of relational social linkages to compare with a matrix of individual risk perceptions The analysis confirmed the hypothesis suggesting that social linkages in communities may play an important role in focusing risk perceptions.