The present historical moment may seem a particularly inopportune time to review Bowling Alone, Robert Putnam's latest exploration of civic decline in America. After all, the outpouring of volunteerism, solidarity, patriotism, and self-sacrifice displayed by Americans in the wake of the September 11 terrorist attacks appears to fly in the face of Putnam's central argument: that \"social capital\" -defined as \"social networks and the norms of reciprocity and trustworthiness that arise from them\" (p. 19)'has declined to dangerously low levels in America over the last three decades. However, Putnam is not fazed in the least by the recent effusion of solidarity. Quite the contrary, he sees in it the potential to \"reverse what has been a 30to 40-year steady decline in most measures of connectedness or community.\"' As an example of how the current \"war on terrorism\" could generate a durable civic renewal, Putnam points to the burst in civic practices that occurred during and after World War II, which he says \"permanently marked\" the generation that lived through it and had a \"terrific effect on American public life over the last half-century.\" 3 If Americans can follow this example and channel their current civic

Bowling alone: The collapse and revival of American community

We are in the midst of a technological revolution whereby, for the first time, researchers can link daily word use to a broad array of real-world behaviors. This article reviews several computerized text analysis methods and describes how Linguistic Inquiry and Word Count (LIWC) was created and validated. LIWC is a transparent text analysis program that counts words in psychologically meaningful categories. Empirical results using LIWC demonstrate its ability to detect meaning in a wide variety of experimental settings, including to show attentional focus, emotionality, social relationships, thinking styles, and individual differences.

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The psychological meaning of words: LIWC and computerized text analysis methods

People are capable of thinking about the future, the past, remote locations, another person's perspective, and counterfactual alternatives. Without denying the uniqueness of each process, it is proposed that they constitute different forms of traversing psychological distance. Psychological distance is egocentric: Its reference point is the self in the here and now, and the different ways in which an object might be removed from that point-in time, in space, in social distance, and in hypotheticality-constitute different distance dimensions. Transcending the self in the here and now entails mental construal, and the farther removed an object is from direct experience, the higher (more abstract) the level of construal of that object. Supporting this analysis, research shows (a) that the various distances are cognitively related to each other, (b) that they similarly influence and are influenced by level of mental construal, and (c) that they similarly affect prediction, preference, and action.

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Construal-Level Theory of Psychological Distance

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

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Using social and behavioural science to support COVID-19 pandemic response.

The rapid growth of the literature on neuroimaging in humans has led to major advances in our understanding of human brain function but has also made it increasingly difficult to aggregate and synthesize neuroimaging findings. Here we describe and validate an automated brain-mapping framework that uses text-mining, meta-analysis and machine-learning techniques to generate a large database of mappings between neural and cognitive states. We show that our approach can be used to automatically conduct large-scale, high-quality neuroimaging meta-analyses, address long-standing inferential problems in the neuroimaging literature and support accurate 'decoding' of broad cognitive states from brain activity in both entire studies and individual human subjects. Collectively, our results have validated a powerful and generative framework for synthesizing human neuroimaging data on an unprecedented scale.

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Large-scale automated synthesis of human functional neuroimaging data

Psychologists have long debated whether it is possible to assess how people subjectively feel without asking them. The recent proliferation of online social networks has recently added a fresh chapter to this discussion, with research now suggesting that it is possible to index people's subjective experience of emotion by simply counting the number of emotion words contained in their online social network posts. Whether the conclusions that emerge from this work are valid, however, rests on a critical assumption: that people's usage of emotion words in their posts accurately reflects how they feel. Although this assumption is widespread in psychological research, here we suggest that there are reasons to challenge it. We corroborate these assertions in 2 ways. First, using data from 4 experience-sampling studies of emotion in young adults, we show that people's reports of how they feel throughout the day neither predict, nor are predicted by, their use of emotion words on Facebook. Second, using simulations we show that although significant relationships emerge between the use of emotion words on Facebook and self-reported affect with increasingly large numbers of observations, the relationship between these variables was in the opposite of the theoretically expected direction 50% of the time (i.e., 3 of 6 models that we performed simulations on). In contrast to counting emotion words, we show that judges' ratings of the emotionality of participants' Facebook posts consistently predicts how people feel across all analyses. These findings shed light on how to draw inferences about emotion using online social network data. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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Does counting emotion words on online social networks provide a window into people's subjective experience of emotion? A case study on Facebook.

The impact of social network sites on mental health: distinguishing active from passive use

Several recent studies suggest that placebos administered without deception (i.e., non-deceptive placebos) can help people manage a variety of highly distressing clinical disorders and nonclinical impairments. However, whether non-deceptive placebos represent genuine psychobiological effects is unknown. Here we address this issue by demonstrating across two experiments that during a highly arousing negative picture viewing task, non-deceptive placebos reduce both a self-report and neural measure of emotional distress, the late positive potential. These results show that non-deceptive placebo effects are not merely a product of response bias. Additionally, they provide insight into the neural time course of non-deceptive placebo effects on emotional distress and the psychological mechanisms that explain how they function. There is controversy about whether placebos without deception cause real psychobiological benefits. Here, the authors show that the positive effects of placebos without deception are more than response bias by providing evidence they can reduce self-report and neural measures of emotional distress.

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Placebos without deception reduce self-report and neural measures of emotional distress

Do social networking sites (SNSs) influence well-being? According to the active-passive model of SNS use, the impact of SNSs on well-being depends on how they are used: Using SNSs actively to inter...

https://journals.sagepub.com/doi/pdf/10.1177/09637214211053637

Ethan Kross

Papers

Does counting emotion words on online social networks provide a window into people's subjective experience of emotion? A case study on Facebook.

The impact of social network sites on mental health: distinguishing active from passive use

Placebos without deception reduce self-report and neural measures of emotional distress

Do Social Networking Sites Influence Well-Being? The Extended Active-Passive Model

From Stimulus Control to Self-Control: Toward an Integrative Understanding of the Processes Underlying Willpower