Variation in social media sensitivity across people and contexts.

Social media impacts people's wellbeing in different ways, but relatively little is known about why this is the case. Here we introduce the construct of "social media sensitivity" to understand how social media and wellbeing associations differ across people and the contexts in which these platforms are used. In a month-long large-scale intensive longitudinal study (total n = 1632; total number of observations = 120,599), we examined for whom and under which circumstances social media was associated with positive and negative changes in social and affective wellbeing. Applying a combination of frequentist and Bayesian multilevel models, we found a small negative average association between social media use AND subsequent wellbeing, but the associations were heterogenous across people. People with psychologically vulnerable dispositions (e.g., those who were depressed, lonely, not satisfied with life) tended to experience heightened negative social media sensitivity in comparison to people who were not psychologically vulnerable. People also experienced heightened negative social media sensitivity when in certain types of places (e.g., in social places, in nature) and while around certain types of people (e.g., around family members, close ties), as compared to using social media in other contexts. Our results suggest that an understanding of the effects of social media on wellbeing should account for the psychological dispositions of social media users, and the physical and social contexts surrounding their use. We discuss theoretical and practical implications of social media sensitivity for scholars, policymakers, and those in the technology industry.

From 65 to 103, Older Adults Experience Virtual Reality Differently Depending on Their Age: Evidence from a Large-Scale Field Study in Nursing Homes and Assisted Living Facilities.

There is growing interest in applications of virtual reality (VR) to improve the lives of older adults, but the limited research on older adults and VR largely treats older adults as a monolith, ignoring the substantial differences across 65 to 100+ year olds that may affect their experience of VR. There are also few existing studies examining the experiences and challenges facing those who facilitate VR for older adults (e.g., caregiving staff). We address these limitations through two studies. In study 1, we explore variation within older adults' experiences with VR through a field study of VR use among a large (N = 245) and age-diverse (Mage = 83.6 years, SDage = 7.9, range = 65-103 years) sample of nursing home and assisted living facility residents across 10 U.S. states. Age was negatively associated with the extent to which older adults enjoyed VR experiences. However, the negative relationship between age and older adults' attitudes toward VR was significantly less negative than the relationship between age and their attitudes toward other technologies (cell phones and voice assistants). In study 2, we surveyed caregiving staff (N = 39) who facilitated the VR experiences for older adult residents and found that the caregiving staff generally enjoyed the activity relative to other activities and felt it to be beneficial to their relationship with residents.

Exposure to untrustworthy websites in the 2020 US election.

Research using large-scale data on individuals' internet use has provided vital information about the scope and nature of exposure to misinformation online. However, most prior work relies on data collected during the 2016 US election. Here we examine exposure to untrustworthy websites during the 2020 US election, using over 7.5 million website visits from 1,151 American adults. We find that 26.2% (95% confidence interval 22.5% to 29.8%) of Americans were exposed to untrustworthy websites in 2020, down from 44.3% (95% confidence interval 40.8% to 47.7%) in 2016. Older adults and conservatives continued to be the most exposed in 2020 as in 2016, albeit at lower rates. The role of online platforms in exposing people to untrustworthy websites changed, with Facebook playing a smaller role in 2020 than in 2016. Our findings do not minimize misinformation as a key social problem, but instead highlight important changes in its consumption, suggesting directions for future research and practice.

Human heuristics for AI-generated language are flawed.

Human communication is increasingly intermixed with language generated by AI. Across chat, email, and social media, AI systems suggest words, complete sentences, or produce entire conversations. AI-generated language is often not identified as such but presented as language written by humans, raising concerns about novel forms of deception and manipulation. Here, we study how humans discern whether verbal self-presentations, one of the most personal and consequential forms of language, were generated by AI. In six experiments, participants (N = 4,600) were unable to detect self-presentations generated by state-of-the-art AI language models in professional, hospitality, and dating contexts. A computational analysis of language features shows that human judgments of AI-generated language are hindered by intuitive but flawed heuristics such as associating first-person pronouns, use of contractions, or family topics with human-written language. We experimentally demonstrate that these heuristics make human judgment of AI-generated language predictable and manipulable, allowing AI systems to produce text perceived as "more human than human." We discuss solutions, such as AI accents, to reduce the deceptive potential of language generated by AI, limiting the subversion of human intuition.

Contextual considerations for deception production and detection in forensic interviews.

Most deception scholars agree that deception production and deception detection effects often display mixed results across settings. For example, some liars use more emotion than truth-tellers when discussing fake opinions on abortion, but not when communicating fake distress. Similarly, verbal and nonverbal cues are often inconsistent predictors to assist in deception detection, leading to mixed accuracies and detection rates. Why are lie production and detection effects typically inconsistent? In this piece, we argue that aspects of the context are often unconsidered in how lies are produced and detected. Greater theory-building related to contextual constraints of deception are therefore required. We reintroduce and extend the Contextual Organization of Language and Deception (COLD) model, a framework that outlines how psychological dynamics, pragmatic goals, and genre conventions are aspects of the context that moderate the relationship between deception and communication behavior such as language. We extend this foundation by proposing three additional aspects of the context - individual differences, situational opportunities for deception, and interpersonal characteristics - for the COLD model that can specifically inform and potentially improve forensic interviewing. We conclude with a forward-looking perspective for deception researchers and practitioners related to the need for more theoretical explication of deception and its detection related to the context.

A digital media literacy intervention for older adults improves resilience to fake news.

Older adults are especially susceptible to fake news online, possibly because they are less digitally literate compared to younger individuals. Interventions for older adults have emerged to improve digital literacy, although there has been little evaluation of their effectiveness in improving older adults' resilience to fake news. We report the results of a digital literacy intervention for older adults administered during the 2020 U.S. election. The intervention was a 1-hour, self-directed series of interactive modules designed to teach concepts and skills for identifying misinformation online. Consistent with our pre-registered hypothesis, older adults (Mage = 67) in the treatment condition (N = 143) significantly improved their likelihood of accurately discerning fake from true news from 64% pre-intervention to 85% post-intervention. In contrast, older adults in the control condition (N = 238) did not significantly improve (from 55% to 57%). The treated older adults were also more likely to employ strategies for identifying misinformation online compared to pre-intervention and the control group.

Effects of Using Artificial Intelligence on Interpersonal Perceptions of Job Applicants.

Text-based artificial intelligence (AI) systems are increasingly integrated into a host of interpersonal domains. Although decision-making and person perception in hiring and employment opportunities have been an area of psychological interest for many years, only recently have scholars begun to investigate the role that AI plays in this context. To better understand the impact of AI in employment-related contexts, we conducted two experiments investigating how the use of AI by applicants influences their job opportunities. In our preregistered Study 1, we examined how a prospective job applicants' use of AI, as well as their language status (native English speaker or non-native English speaker), influenced participants' impressions of their warmth, competence, social attractiveness, and hiring desirability. In Study 2, we examined how receiving assistance impacted interpersonal perceptions, and how perceptions might change whether the help was provided by AI or by another human. The results from both experiments suggest that the use of AI technologies can negatively influence perceptions of jobseekers. This negative impact may be grounded in the perception of receiving any type of help, whether it be from a machine or a person. These studies provide additional evidence for the Computers as Social Actors framework and advance our understanding of AI-Mediated Communication. The results also raise questions about transparency and deception related to AI use in interpersonal contexts.

Identifying Silver Linings During the Pandemic Through Natural Language Processing.

COVID-19 has presented an unprecedented challenge to human welfare. Indeed, we have witnessed people experiencing a rise of depression, acute stress disorder, and worsening levels of subclinical psychological distress. Finding ways to support individuals' mental health has been particularly difficult during this pandemic. An opportunity for intervention to protect individuals' health & well-being is to identify the existing sources of consolation and hope that have helped people persevere through the early days of the pandemic. In this paper, we identified positive aspects, or "silver linings," that people experienced during the COVID-19 crisis using computational natural language processing methods and qualitative thematic content analysis. These silver linings revealed sources of strength that included finding a sense of community, closeness, gratitude, and a belief that the pandemic may spur positive social change. People's abilities to engage in benefit-finding and leverage protective factors can be bolstered and reinforced by public health policy to improve society's resilience to the distress of this pandemic and potential future health crises.

Age-Related Differences in Experiences With Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language From a Social Media Survey.

BACKGROUND: As COVID-19 poses different levels of threat to people of different ages, health communication regarding prevention measures such as social distancing and isolation may be strengthened by understanding the unique experiences of various age groups. OBJECTIVE: The aim of this study was to examine how people of different ages (1) experienced the impact of the COVID-19 pandemic and (2) their respective rates and reasons for compliance or noncompliance with social distancing and isolation health guidance. METHODS: We fielded a survey on social media early in the pandemic to examine the emotional impact of COVID-19 and individuals' rates and reasons for noncompliance with public health guidance, using computational and content analytic methods of linguistic analysis. RESULTS: A total of 17,287 participants were surveyed. The majority (n=13,183, 76.3%) were from the United States. Younger (18-31 years), middle-aged (32-44 years and 45-64 years), and older (≥65 years) individuals significantly varied in how they described the impact of COVID-19 on their lives, including their emotional experience, self-focused attention, and topical concerns. Younger individuals were more emotionally negative and self-focused, while middle-aged people were other-focused and concerned with family. The oldest and most at-risk group was most concerned with health-related terms but were lower in anxiety (use of fewer anxiety-related terms) and higher in the use of emotionally positive terms than the other less at-risk age groups. While all groups discussed topics such as acquiring essential supplies, they differentially experienced the impact of school closures and limited social interactions. We also found relatively high rates of noncompliance with COVID-19 prevention measures, such as social distancing and self-isolation, with younger people being more likely to be noncompliant than older people (P<.001). Among the 43.1% (n=7456) of respondents who did not fully comply with health orders, people differed substantially in the reasons they gave for noncompliance. The most common reason for noncompliance was not being able to afford to miss work (n=4273, 57.3%). While work obligations proved challenging for participants across ages, younger people struggled more to find adequate space to self-isolate and manage their mental and physical health; middle-aged people had more concerns regarding childcare; and older people perceived themselves as being able to take sufficient precautions. CONCLUSIONS: Analysis of natural language can provide insight into rapidly developing public health challenges like the COVID-19 pandemic, uncovering individual differences in emotional experiences and health-related behaviors. In this case, our analyses revealed significant differences between different age groups in feelings about and responses to public health orders aimed to mitigate the spread of COVID-19. To improve public compliance with health orders as the pandemic continues, health communication strategies could be made more effective by being tailored to these age-related differences.

Experience with Social Distancing Early in the COVID-19 Pandemic in the United States: Implications for Public Health Messaging.

Our goal is to inform ongoing public health policy on the design and communication of COVID-19 social distancing measures to maximize compliance. We assessed the US publics early experience with the COVID-19 crisis during the period when shelter-in-place orders were widely implemented to understand non-compliance with those orders, sentiment about the crisis, and to compare across age categories associated with different levels of risk. We posted our survey on Twitter, Facebook, and NextDoor on March 14th to March 23rd that included 21 questions including demographics, impact on daily life, actions taken, and difficulties faced. We analyzed the free-text responses to the impact question using LIWC, a computational natural language processing tool, and performed a thematic content analysis of the reasons people gave for non-compliance with social distancing orders. Stanford Universitys IRB approved the study. In 9 days, we collected a total of 20,734 responses. 6,573 individuals provided a response (≥30 words) to the question, Tell us how the coronavirus crisis is impacting your life. Our data (Figure 1) show that younger people (18-31) are more emotionally negative, self-centered, and less concerned with family, while middle-aged people are group-oriented (32-44) and focused on family (32-64) (all p values < .05 corrected for multiple comparisons). Unsurprisingly, the oldest and most at-risk group (65+) are more focused on biological terms (e.g., health-related topics), but were surprisingly low in anxiety and high in emotionally positive terms relative to those at lower risk. We also content-analyzed 7,355 responses (kappas > .75) to the question, What are the reasons you are not self-isolating more? Of these participants, 39.8% reported not being compliant, with the youngest group (18-31) having the lowest compliance rate (52.4%) compared to the other age groups (all > 60%; all p values < .01). Table 1 describes the seven primary themes for non-compliance. Non-essential work requirements, concerns about mental and physical health, and the belief that other precautions were sufficient were the most common reasons, although other rationales included wanting to continue everyday activities and beliefs that society is over-reacting. Childcare was an important concern for a subset of respondents. Overall, our findings suggest that public health messages should focus on young people and 1) address their negative affect, 2) refocus their self-orientation by emphasizing the importance of individual behavior to group-level health outcomes, and 3) target the specific rationales that different people have regarding the pandemic to maximize compliance with social distancing.

Self-disclosure and social media: motivations, mechanisms and psychological well-being.

Self-disclosure is pervasive on social media and has significant implications for psychological well-being. In this review we synthesize recent research on the motivations, mechanisms and effects of self-disclosure on well-being and then propose a framework that highlights the bidirectional relationship between self-disclosure and well-being. The framework details the mechanisms by which self-disclosure on social media can influence well-being and how self-disclosure fulfills particular needs of individuals with different well-being characteristics. We call for future research to examine the proposed bi-directional relationship, especially studies designed to tease out causal effects.

Psychological and physiological effects of applying self-control to the mobile phone.

This preregistered study examined the psychological and physiological consequences of exercising self-control with the mobile phone. A total of 125 participants were randomly assigned to sit in an unadorned room for six minutes and either (a) use their mobile phone, (b) sit alone with no phone, or (c) sit with their device but resist using it. Consistent with prior work, participants self-reported more concentration difficulty and more mind wandering with no device present compared to using the phone. Resisting the phone led to greater perceived concentration abilities than sitting without the device (not having external stimulation). Failing to replicate prior work, however, participants without external stimulation did not rate the experience as less enjoyable or more boring than having something to do. We also observed that skin conductance data were consistent across conditions for the first three-minutes of the experiment, after which participants who resisted the phone were less aroused than those who were without the phone. We discuss how the findings contribute to our understanding of exercising self-control with mobile media and how psychological consequences, such as increased mind wandering and focusing challenges, relate to periods of idleness or free thinking.

Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data.

BACKGROUND: Substance use-related communication for drug use promotion and its prevention is widely prevalent on social media. Social media big data involve naturally occurring communication phenomena that are observable through social media platforms, which can be used in computational or scalable solutions to generate data-driven inferences. Despite the promising potential to utilize social media big data to monitor and treat substance use problems, the characteristics, mechanisms, and outcomes of substance use-related communications on social media are largely unknown. Understanding these aspects can help researchers effectively leverage social media big data and platforms for observation and health communication outreach for people with substance use problems. OBJECTIVE: The objective of this critical review was to determine how social media big data can be used to understand communication and behavioral patterns of problematic use of prescription drugs. We elaborate on theoretical applications, ethical challenges and methodological considerations when using social media big data for research on drug abuse and addiction. Based on a critical review process, we propose a typology with key initiatives to address the knowledge gap in the use of social media for research on prescription drug abuse and addiction. METHODS: First, we provided a narrative summary of the literature on drug use-related communication on social media. We also examined ethical considerations in the research processes of (1) social media big data mining, (2) subgroup or follow-up investigation, and (3) dissemination of social media data-driven findings. To develop a critical review-based typology, we searched the PubMed database and the entire e-collection theme of "infodemiology and infoveillance" in the Journal of Medical Internet Research / JMIR Publications. Studies that met our inclusion criteria (eg, use of social media data concerning non-medical use of prescription drugs, data informatics-driven findings) were reviewed for knowledge synthesis. User characteristics, communication characteristics, mechanisms and predictors of such communications, and the psychological and behavioral outcomes of social media use for problematic drug use-related communications are the dimensions of our typology. In addition to ethical practices and considerations, we also reviewed the methodological and computational approaches used in each study to develop our typology. RESULTS: We developed a typology to better understand non-medical, problematic use of prescription drugs through the lens of social media big data. Highly relevant studies that met our inclusion criteria were reviewed for knowledge synthesis. The characteristics of users who shared problematic substance use-related communications on social media were reported by general group terms, such as adolescents, Twitter users, and Instagram users. All reviewed studies examined the communication characteristics, such as linguistic properties, and social networks of problematic drug use-related communications on social media. The mechanisms and predictors of such social media communications were not directly examined or empirically identified in the reviewed studies. The psychological or behavioral consequence (eg, increased behavioral intention for mimicking risky health behaviors) of engaging with and being exposed to social media communications regarding problematic drug use was another area of research that has been understudied. CONCLUSIONS: We offer theoretical applications, ethical considerations, and empirical evidence within the scope of social media communication and prescription drug abuse and addiction. Our critical review suggests that social media big data can be a tremendous resource to understand, monitor and intervene on drug abuse and addiction problems.

Optimistic bias and Facebook use: self-other discrepancies about potential risks and benefits of Facebook use.

Despite the accumulating evidence on the positive and negative outcomes of Facebook use, how people perceive themselves to be subject to these outcomes as well as the consequences and mechanisms of these perceptions are underexplored. According to optimistic bias, Facebook users may perceive that bad things are more likely to happen to others than to themselves, while good things are more likely to happen to them than to others. The findings from an online survey among Facebook users indicate that the negative psychological and social outcomes of using Facebook were perceived to be more likely to happen to other Facebook users than to themselves, p<0.001. These self-other discrepant perceptions toward negative social events (e.g., Facebook cyberbullying and scams) significantly mediated one's willingness to support Internet regulation, Sobel z=2.49, p=0.01. For positive outcomes of Facebook use, the direction of optimistic bias was reversed, t(235) = -5.52, p<0.01, indicating that people minimized the likelihoods of experiencing positive events from Facebook while assessing that other Facebook users are prone to encounter those positive events. This reversal pattern emerged among those with negative attitudes toward, and low involvement with, Facebook. These findings demonstrate important and novel self-other discrepant perceptions concerning the risks and benefits of Facebook use.

A linguistic analysis of grooming strategies of online child sex offenders: Implications for our understanding of predatory sexual behavior in an increasingly computer-mediated world.

There is a large body of evidence to suggest that child sex offenders engage in grooming to facilitate victimization. It has been speculated that this step-by-step grooming process is also used by offenders who access their underage victims online; however, little research has been done to examine whether there are unique aspects of computer-mediated communication that impact the traditional face-to-face grooming process. This study considered the similarities and differences in the grooming process in online environments by analyzing the language used by online offenders when communicating with their victims. The transcripts of 44 convicted online offenders were analyzed to assess a proposed theory of the online grooming process (O'Connell, 2003). Using a stage-based approach, computerized text analysis examined the types of language used in each stage of the offender-victim interaction. The transcripts also were content analyzed to examine the frequency of specific techniques known to be employed by both face-to-face and online offenders, such as flattery. Results reveal that while some evidence of the strategies used by offenders throughout the grooming process are present in online environments, the order and timing of these stages appear to be different. The types (and potential underlying pattern) of strategies used in online grooming support the development of a revised model for grooming in online environments.

Text messaging reduces analgesic requirements during surgery.

OBJECTIVE: This study aims to determine whether communicating via short message service text message during surgery procedures leads to decreased intake of fentanyl for patients receiving regional anesthesia below the waist compared with a distraction condition and no intervention. METHODS: Ninety-eight patients receiving regional anesthesia for minor surgeries were recruited from a hospital in Montreal, QC, between January and March 2012. Patients were randomly assigned to text message with a companion, text message with a stranger, play a distracting mobile phone game, or receive standard perioperative management. Participants who were asked to text message or play a game did so before receiving the anesthetic and continued until the end of the procedure. RESULTS: The odds of receiving supplemental analgesia during surgery for patients receiving standard perioperative management were 6.77 (P=0.009; N=13/25) times the odds for patients in the text a stranger condition (N=22/25 of patients), 4.39 times the odds for those in the text a companion condition (P=0.03; N=19/23), and 1.96 times the odds for those in the distraction condition (P=0.25; N=17/25). CONCLUSION: Text messaging during surgery provides analgesic-sparing benefits that surpass distraction techniques, suggesting that mobile phones provide new opportunities for social support to improve patient comfort and reduce analgesic requirements during minor surgeries and in other clinical settings.

Linguistic traces of a scientific fraud: the case of Diederik Stapel.

When scientists report false data, does their writing style reflect their deception? In this study, we investigated the linguistic patterns of fraudulent (N  =  24; 170,008 words) and genuine publications (N  =  25; 189,705 words) first-authored by social psychologist Diederik Stapel. The analysis revealed that Stapel's fraudulent papers contained linguistic changes in science-related discourse dimensions, including more terms pertaining to methods, investigation, and certainty than his genuine papers. His writing style also matched patterns in other deceptive language, including fewer adjectives in fraudulent publications relative to genuine publications. Using differences in language dimensions we were able to classify Stapel's publications with above chance accuracy. Beyond these discourse dimensions, Stapel included fewer co-authors when reporting fake data than genuine data, although other evidentiary claims (e.g., number of references and experiments) did not differ across the two article types. This research supports recent findings that language cues vary systematically with deception, and that deception can be revealed in fraudulent scientific discourse.

Experimental evidence of massive-scale emotional contagion through social networks.

Emotional states can be transferred to others via emotional contagion, leading people to experience the same emotions without their awareness. Emotional contagion is well established in laboratory experiments, with people transferring positive and negative emotions to others. Data from a large real-world social network, collected over a 20-y period suggests that longer-lasting moods (e.g., depression, happiness) can be transferred through networks [Fowler JH, Christakis NA (2008) BMJ 337:a2338], although the results are controversial. In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred. These results indicate that emotions expressed by others on Facebook influence our own emotions, constituting experimental evidence for massive-scale contagion via social networks. This work also suggests that, in contrast to prevailing assumptions, in-person interaction and nonverbal cues are not strictly necessary for emotional contagion, and that the observation of others' positive experiences constitutes a positive experience for people.

Self-affirmation underlies Facebook use.

Social network sites, such as Facebook, have acquired an unprecedented following, yet it is unknown what makes them so attractive to users. Here we propose that these sites' popularity can be understood through the fulfillment of ego needs. We use self-affirmation theory to hypothesize why and when people spend time on their online profiles. Study 1 shows that Facebook profiles are self-affirming in the sense of satisfying users' need for self-worth and self-integrity. Study 2 shows that Facebook users gravitate toward their online profiles after receiving a blow to the ego, in an unconscious effort to repair their perceptions of self-worth. In addition to illuminating some of the psychological factors that underlie Facebook use, the results provide an important extension to self-affirmation theory by clarifying how self-affirmation operates in people's everyday environments.