The average Twitter user spends 5.1 hours per month on the platform.

This article studies how the feedback that politicians receive from citizens on social media affect the issues they choose to discuss, and hypothesizes that politicians are exposed to different feedback depending on their social group membership, leading to divergence in issue attention. We use a reinforcement learning framework to model how politicians choose policy issues and respond to citizens' feedback by increasing attention to better received issues. We collect 1.5 million tweets published by Spanish MPs over three years, identify gender issue tweets using a deep learning algorithm (BERT) and measure feedback using retweets and likes. We find that citizens provide more positive feedback to female politicians for writing about gender, and that this contributes to their specialization in gender issues. The analysis of mechanisms suggests that female politicians receive more positive feedback because they are treated differently by citizens. To conclude, we discuss implications for representation, misperceptions, and polarization.

Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

Governments may have the capacity to flood social media with fake news, but little is known about the use of flooding by ordinary voters. In this work, we identify 2107 registered US voters that account for 80% of the fake news shared on Twitter during the 2020 US presidential election by an entire panel of 664,391 voters. We find that supersharers are important members of the network, reaching a sizable 5.2% of registered voters on the platform. Supersharers have a significant overrepresentation of women, older adults, and registered Republicans. Supersharers' massive volume does not seem automated but is rather generated through manual and persistent retweeting. These findings highlight a vulnerability of social media for democracy, where a small group of people distort the political reality for many., This dataset contains aggregated information necessary to replicate the results reported in our work on Supersharers of Fake News on Twitter while respecting and preserving the privacy expectations of individuals included in the analysis. No individual-level data is provided as part of this dataset. The data collection process that enabled the creation of this dataset leveraged a large-scale panel of registered U.S. voters matched to Twitter accounts. We examined the activity of 664,391 panel members who were active on Twitter during the months of the 2020 U.S. presidential election (August to November 2020, inclusive), and identified a subset of 2,107 supersharers, which are the most prolific sharers of fake news in the panel that together account for 80% of fake news content shared on the platform. We rely on a source-level definition of fake news, that uses the manually-labeled list of fake news sites by Grinberg et al. 2019 and an updated list based on NewsGuard ratings (commercial..., , # Supersharers of Fake News on Twitter

This repository contains data and code for replication of the results presented in the paper.

The folders are mostly organized by research questions as detailed below. Each folder contains the code and publicly available data necessary for the replication of results. Importantly, no individual-level data is provided as part of this repository. De-identified individual-level data can be attained for IRB-approved uses under the terms and conditions specified in the paper. Once access is granted, the restricted-access data is expected to be located under ./restricted_data.

The folders in this repository are the following:

Preprocessing

Code under the preprocessing folder contains the following:

1. source classifier - the code used to train a classifier based on NewsGuard domain flags to match the fake news labels source definition use in Grinberg et el. 2019 labels.
2. political classifier - the code used to identify political tweets, i...

The number of Instagram users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 2.1 million users (+7.02 percent). After the ninth consecutive increasing year, the Instagram user base is estimated to reach 32 million users and therefore a new peak in 2028. Notably, the number of Instagram users of was continuously increasing over the past years.User figures, shown here with regards to the platform instagram, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

R and R Studio.

The Yahoo Personals Dating Preferences Study sought to examine the dating preferences of online daters in four major metropolitan areas: New York, Los Angeles, Chicago, and Atlanta. Internet daters' profiles of self-identified Asian, Black, Latino, and White men and women seeking opposite-sex dates were collected and coded from Yahoo Personals, which was the most popular national online dating web site in 2004 and 2005. Data were collected on subjects' height, body type, smoking and drinking habits, whether subjects had children, religious service attendance, languages spoken, and miles subjects were willing to travel for a date. Data were also collected on subjects' preferences for dates, including preferred physical appearance, lifestyle behaviors, living situation, employment status, occupation, children, religious service attendance, and languages spoken. Demographic information collected includes subjects' sex, age, ethnicity, marital status, education, political affiliation, and religious affiliation.

The prevalence of a negative body image among women is high. Because of its serious consequences for individuals’ mental health, there is an urgent need to improve current body image interventions. Recent studies using evaluative conditioning to strengthen the association between women’s body and positive (social) stimuli have shown promising results. In two experimental studies, we tested whether incorporating more age appropriate positive social stimuli as unconditioned stimuli (USs) can strengthen the conditioning procedure as a means to enhance women’s body satisfaction. In the experimental condition, participants’ body pictures were systematically followed by the Facebook like-button and youthful smiling faces (study 1, experimental condition: n = 68; control condition: n = 67) or positive Emojis (study 2, experimental condition: n = 64; control condition: n = 67). The results indicated that neither conditioning procedure enhanced participants’ body satisfaction more than a control procedure, and in both studies, there was no valence transfer from the positive USs to the body pictures. Thus, incorporation of age appropriate USs did not result in the anticipated conditioning effects. These findings challenge the utility of current evaluative conditioning procedures as an intervention technique to address a negative body image.

IntroductionPublic discussions in the media (e.g., social media and reality shows) about Black women's mental health have become more common. Notably, celebrities have become more vocal about their own mental health challenges and sought to normalize seeking care. This study aimed to gain a better understanding of Black women's: (1) past and current causes of stress, anxiety, and depression, and coping skills used; (2) their attitudes and perceptions toward mental health and receiving mental health treatment; and (3) times in their life they felt anxious or depressed, and what type of support or resources would have been helpful to have access to.MethodsFocus groups were conducted with 20 women (mean age 36.6 years, SD 17.8 years), with 5 participants per group. Descriptive qualitative content analysis of the focus group transcripts was conducted.ResultsResults consistently showed that intersectional identities of being both Black and a woman resulted in feelings of both hypervisibility and invisibility, representation matters when it comes to mental health providers, an increased openness to therapy across age groups, and a willingness to try digital health tools (e.g., smartphone app) for mental health needs. There is still work to be done to normalize mental health treatment among Black women.DiscussionSubgroups within the community (e.g., young adults) have less stigma around mental health and are acting as catalysts for change. Intentional inclusion of Black women in mental health research and evolving treatment paradigms is important to eliminate inequities in access to culturally relevant mental health care.

The study aimed to gain insight into the ways that narratives of self-responsibility were taken up and embodied - or alternatively, resisted - within economically disadvantaged communities; the ways that these narratives and associated welfare reforms impacted on mental distress; and the way that these narratives interconnected with the medicalisation and pathologisation of poverty-related distress. (1) The study involved sixteen focus groups with ninety-seven participants (aged 18-65) from economically disadvantaged communities to establish the source and impact of narratives of self-responsibility within people’s everyday lives (36 men, 61 women). (2)Fifty-seven low-income residents (aged 18-65) who had experienced poverty-related mental distress were also interviewed (26 men, 31 women) to understand the cause(s) of their distress, and their responses to this. Participants who were receiving mental health treatment at the time of the study, and participants who wanted more time to discuss their experiences were interviewed on two occasions (total interviews n=80), enabling us to track responses over time and facilitating the triangulation of data. All lived on low-incomes. Whilst not specifically asked to define their status in terms of class, people commonly defined themselves through characteristics or inferences usually associated with being ‘working class.’ (3) Interviews with General Practitioners (n=10) working in low income areas were undertaken to understand their experiences and the challenges they faced supporting mental health amongst patients experiencing poverty, and their perceptions of current treatment options. The provision of effective treatment and support for mental distress is a stated aim of the Department of Health and civil society organisations e.g. Mind. Yet despite a stated need to tackle health inequalities, current strategies e.g. Closing the Gap: Priorities for Essential Change in Mental Health (DoH 2014), frame mental distress as a psychological problem that lies within the individual concerned. This not only suggests that distress can be 'corrected' through medical treatment, but also masks the factors that often underlie the root causes of suffering e.g. poor living conditions, unemployment. At the same time, policies in place to restrict welfare support, and popular media e.g. Benefits Street, draw on moralising narratives that promote the idea that people are responsible for their own actions and circumstances. This research aims to explore how these moralising narratives impact on the ways that people in low-income communities perceive and respond to mental distress caused by material deprivation and social disadvantage, and to examine the impacts of this on their wellbeing. This was achieved through in-depth research in two low-income communities in the South West, which sought to understand: i) the way that moral narratives are defined and used or resisted in people's everyday lives in relation to mental distress; ii) the influence of moral narratives on people's decisions to seek medical support for distress; iii) how moral narratives manifest within GP consultations and influence treatment decisions and patient wellbeing; iv) which responses to mental distress have the potential to effectively support vulnerable populations, and to inform ethical debates on the medicalisation of distress in a way that benefits patients, and assists practitioners and policy makers seeking to support low-income communities. The DeStress Project was a two and half-year research project with two very low-income urban communities (one post-industrial, one coastal with a seasonal employment structure) in the UK’s south-west region. Ethics permission was obtained from the NHS Cambridgeshire and Hertfordshire Research Ethics Committee. The study aimed to gain insight into the ways that narratives of self-responsibility were taken up and embodied - or alternatively, resisted - within economically disadvantaged communities; the ways that these narratives and associated welfare reforms impacted on mental distress; and the way that these narratives interconnected with the medicalisation and pathologisation of poverty-related distress. (1) The study involved sixteen focus groups with ninety-seven participants (aged 18-65) from economically disadvantaged communities to establish the source and impact of narratives of self-responsibility within people’s everyday lives (36 men, 61 women). (2) Fifty-seven low-income residents (aged 18-65) who had experienced poverty-related mental distress were also interviewed (26 men, 31 women) to understand the cause(s) of their distress, and their responses to this. Of these participants, eighty one per cent had been prescribed antidepressants, whilst a further seven per cent had refused the prescription offered. The remaining thirteen per cent had been advised to self-refer to talking therapy, or had chosen to avoid interaction with health services. Potential participants were alerted to the study by community and health practitioners, social media and word-of-mouth and recruited through community groups and GP surgeries. Participants who were receiving mental health treatment at the time of the study, and participants who wanted more time to discuss their experiences were interviewed on two occasions (total interviews n=80), enabling us to track responses over time and facilitating the triangulation of data. In almost all cases, study participants had lived in an economically disadvantaged area throughout their lives, though older participants in one area had also lived there at a time when it was more prosperous. All lived on low-incomes. Whilst not specifically asked to define their status in terms of class, people commonly defined themselves through characteristics or inferences usually associated with being ‘working class.’ (3) Interviews with General Practitioners (n=10) working in low income areas were undertaken to understand their experiences and the challenges they faced supporting mental health amongst patients experiencing poverty, and their perceptions of current treatment options. Informal discussions with key service providers from health, education and social sectors were also undertaken to gain insight into their experiences of working with people living with the stresses of poverty. Sixteen focus groups with a total of ninety-seven participants, aged 18-65, from the two study sites (36 men and 61 women), with the gender ratio reflecting reported rates of common mental disorders in England (NHS Digital 2016) . Participants were recruited via community groups and settings, word of mouth and advertising on posters and social media. Participants were asked about the main health issues and stresses faced by local residents, how people respond to those stresses and their impact on wellbeing. In addition, eighty interviews were undertaken with fifty-seven residents (aged 18-65) who had experienced poverty-related distress (26 men, 31 women) to gain a more in-depth understanding of the source(s) of this distress, and their responses to it. Interviewees were recruited via the focus groups and word of mouth but also via GP surgeries to capture a broad range of views and experiences (including those who may be socially isolated). In the majority of cases, people had sought medical support for their distress, although two had chosen not to. Participants who were engaged in the health system for their distress at the time of the study, and participants who wanted more time to discuss their experiences were interviewed on two occasions, enabling us to capture any changes over time and understand the ongoing dynamic interaction between mental ill-health and welfare reform. The interviews and focus groups generated a rich body of narrative data that gives prominence to the voices and experiences of people living in low-income communities. This data has been supplemented with interviews with General Practitioners (n=10) to understand the challenges they face supporting people experiencing poverty-related distress.

The number of Pinterest users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 0.3 million users (+3.14 percent). After the ninth consecutive increasing year, the Pinterest user base is estimated to reach 9.88 million users and therefore a new peak in 2028. Notably, the number of Pinterest users of was continuously increasing over the past years.User figures, shown here regarding the platform pinterest, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

Background Around one in five women will experience depression in the perinatal period. This is a period of transition for women’s identities, social networks and relationships. Growing evidence suggests that loneliness, isolation and lack of social support are risk factors for depression. However, little research has explored pathways between these and perinatal depression, or whether women themselves connect loneliness and isolation to their mental health. Methods This project involved secondary data analysis only. We analysed qualitative interviews with fourteen women diagnosed with perinatal depression to see whether they described isolation and loneliness as contributing to their distress. We also examined the relationship between social support and depression, using quantitative data from 525 women interviewed in pregnancy and postnatally. We analysed all data collaboratively with a group of women with lived experience of perinatal mental health difficulties. Findings Qualitatively, we found that motherhood interacted with other aspects of women’s identities, such as being young, single, deprived, or a woman of colour, to result in isolation and feelings of 'dislocated' self and relationships, particularly for some mothers. Women felt confined to their homes by the mothering role, isolated from wider social networks, and unsupported by their partners/families. Fears of being seen as ‘bad mothers’ provoked feelings of inadequacy and made it hard to make authentic connections with others, increasing isolation and depression. Quantitatively, we found that a lack of social support antenatally was related to postnatal depression, and this relationship was stronger for women who were not living with a partner. Conclusions Our findings suggest that isolation, loneliness and social support are important in relation to perinatal depression. Our analysis highlights a need to: develop support which addresses interpersonal/social networks; advocate for social change to lessen pressures on perinatal women and their families; and challenge the social constructions of the ‘good mother’.Background Around one in five women will experience depression in the perinatal period. This is a period of transition for women’s identities, social networks and relationships. Growing evidence suggests that loneliness, isolation and lack of social support are risk factors for depression. However, little research has explored pathways between these and perinatal depression, or whether women themselves connect loneliness and isolation to their mental health. Methods This project consisted of secondary data analysis. We analysed qualitative interviews with fourteen women diagnosed with perinatal depression to see whether they described isolation and loneliness as contributing to their distress. We also examined the relationship between social support and depression, using quantitative data from 525 women interviewed in pregnancy and postnatally. We analysed all data collaboratively with a group of women with lived experience of perinatal mental health difficulties. Findings Qualitatively, we found that motherhood interacted with other aspects of women’s identities, such as being young, single, deprived, or a woman of colour, to result in isolation and feelings of 'dislocated' self and relationships, particularly for some mothers. Women felt confined to their homes by the mothering role, isolated from wider social networks, and unsupported by their partners/families. Fears of being seen as ‘bad mothers’ provoked feelings of inadequacy and made it hard to make authentic connections with others, increasing isolation and depression. Quantitatively, we found that a lack of social support antenatally was related to postnatal depression, and this relationship was stronger for women who were not living with a partner. Conclusions Our findings suggest that isolation, loneliness and social support are important in relation to perinatal depression. Our analysis highlights a need to: develop support which addresses interpersonal/social networks; advocate for social change to lessen pressures on perinatal women and their families; and challenge the social constructions of the ‘good mother’. Qualitative and quantitative secondary data analysis.

The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

This study consists of information from all four surveys of the 1989-95 cohort. In 2012 and 2013, 17,069 18-23 year old women were enrolled in this "New Young" cohort. Women were mainly recruited using the internet and social media platforms. Consistent with the other cohorts, women were required to have a Medicare card. Women completed the online survey and provided consent to linkage of survey data with administrative databases such as Medicare. This particular dataset is participant data. It has information for each participant from Survey 1 to Survey 4 of the 1989-1995 (New Young) cohort.