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Automatically inferring user demographics from social media posts is useful for both social science research and a range of downstream applications in marketing and politics. We present the first extensive study where user behaviour on Twitter is used to build a predictive model of income. We apply non-linear methods for regression, i.e. Gaussian Processes, achieving strong correlation between predicted and actual user income. This allows us to shed light on the factors that characterise income on Twitter and analyse their interplay with user emotions and sentiment, perceived psycho-demographics and language use expressed through the topics of their posts. Our analysis uncovers correlations between different feature categories and income, some of which reflect common belief e.g. higher perceived education and intelligence indicates higher earnings, known differences e.g. gender and age differences, however, others show novel findings e.g. higher income users express more fear and anger, whereas lower income users express more of the time emotion and opinions.

This report explores the emergence of a skills-first approach in labour markets in OECD countries, and what opportunities and challenges arise from the adoption of skills-first approaches in light of demographic shifts and the green and digital transition. Through original data analysis and the examination of case studies from OECD countries, the report illustrates when and how individuals signal their skills, and to what extent employers adopt skills-based hiring practices, and whether these efforts allow them to reach a broader and diverse talent pool. A skills-first approach can lead to better job matching and adaptability, but barriers to its successful adoption remain. These include unequal access to digital tools, challenges in validating skills, and employers’ reluctance to trust non-traditional credentials. Its novelty also raises questions about accessibility and potential impacts on job quality and workplace conditions. The report highlights key policy actions to support the adoption of skills-first practices, calling on governments to standardise skills recognition, invest in lifelong learning, improve labour market intelligence, and lead by example by adopting skills-first practices in the management of the public sector workforce.

Online media offer unprecedented access to digital public spheres, largely enhancing users’ opportunities for participation and providing new means for strengthening democratic discourse. At the same time, the last decades have demonstrated that online discourses are often characterised by so-called ‘dark participation’ the spreading of lies and incivility. Using ‘problematic behaviour theory’ as framework and focusing on incivility as a specific form of dark participation, this article investigates the role of users’ personal characteristics, media use, and online experiences in relation to offensive and hateful online behaviour. Using a random-quota survey of the German population, we explored how dark personality traits, political attitudes and emotions, the frequency and spaces of online-media use, and users’ experiences with both civil and uncivil online discourses predicted participants own uncivil behaviour, such as posting, sharing, or liking uncivil content. We found that 46% of the participants who had witnessed incivility in the last three months also engaged in uncivil participation. A hierarchical logistic regression analysis showed that incivility was associated with manipulative personality traits as measured by the dark triad, right-wing populist voting intentions, and frequent social-media use. Experiences with both civil comments and hate speech predicted higher levels of uncivil participation. The strongest predictor was participants’ personal experiences with online victimisation. Overall, the results confirmed that dark participation in the sense of uncivil engagement results from the interplay of personality traits, an online environment that allows for deviant engagement, and, most importantly, participants’ experiences in said environment.

Youth with disabilities often encounter many challenges in securing employment. Although the common barriers that youth face are well documented, little is known about the experiences of youth who have multiple minoritized identities in finding and maintaining employment. Youth with disabilities who belong to racial minoritized groups may encounter ableism and racism and other forms of discrimination at work. Exploring the experiences of racial minoritized youth with non-apparent disabilities is important given the growing concern about social inequities that are linked to disadvantage and differential access to resources such as employment. We used a qualitative design involving semi-structured interviews with 19 youth (13 women, 3 non-binary, 3 men), aged 17–30 (mean 23.5 years). An inductive thematic analysis was applied to analyze the data. We identified the following themes: (1) challenges finding and maintaining employment; (2) the extent of safety and comfort with disclosing minoritized identities in the workplace (i.e., comfortable disclosing; uncomfortable disclosing; did not need to disclose and/or hiding identities); (3) workplace discrimination based on minoritized identities (i.e., ableism, racism, ableist racism, gendered ableism, racist and gendered ableism); (4) impact of discrimination (i.e., negative affective outcomes, social and work adjustment, impact on professional development) and coping strategies (i.e., advocacy, networking, peer support); and (5) advice for youth and employers. Our study highlights the extent of racism and ableism that racial minoritized youth with non-apparent disabilities experience in the workplace and the importance of rehabilitation clinicians supporting their inclusion.

Gull chicks beg for food from their parents. Peacocks spread their tails to attract potential mates. Meerkats alert family members of the approach of predators. But are these--and other animals--sometimes dishonest? That's what William Searcy and Stephen Nowicki ask in The Evolution of Animal Communication. They take on the fascinating yet perplexing question of the dependability of animal signaling systems. The book probes such phenomena as the begging of nesting birds, alarm calls in squirrels and primates, carotenoid coloration in fish and birds, the calls of frogs and toads, and weapon displays in crustaceans. Do these signals convey accurate information about the signaler, its future behavior, or its environment? Or do they mislead receivers in a way that benefits the signaler? For example, is the begging chick really hungry as its cries indicate or is it lobbying to get more food than its brothers and sisters? Searcy and Nowicki take on these and other questions by developing clear definitions of key issues, by reviewing the most relevant empirical data and game theory models available, and by asking how well theory matches data. They find that animal communication is largely reliable--but that this basic reliability also allows the clever deceiver to flourish. Well researched and clearly written, their book provides new insight into animal communication, behavior, and evolution.

Across two studies, the current work sought to understand the impact of elaboration questions in political discussion on perceptions of feeling heard and future discussion intentions. Participants were presented with a recorded video of a political conversation where we manipulated the presence and absence of elaboration questions in political conversations surrounding homelessness (Study 1) and abortion (Study 2). Results indicate the presence of elaboration questions increased perceptions of being heard and intentions to engage in discussion in the future. We also found significant indirect results where the relationship between elaboration questions and intentions to engage in future discussions was mediated by feeling heard. These findings were never moderated by whether participants agreed with the political stance taken in the conversation.

Digitization has profoundly changed how government interacts with its publics. The expanding use of AI promises even more advancement. However, the rollout of AI is not without risk. This work explores the use of AI in federal rulemaking, the process by which regulations are introduced and revised. The US federal government has created digital platforms that dramatically expand access for the public commenting on pending regulations. However, these platforms also attract volumes of opinion spam that attempt to influence regulatory decision-making. Using AI to identify opinion spam may offer a potential remedy, but removing or limiting comments with the help of AI may threaten rulemaking legitimacy. This research uses the situational theory of problem-solving as a framework, segmenting publics based on their problem recognition, constraints, and involvement with a specific issue, then predicting how each public behaves. We examined how employing AI in the processing of rulemaking comments affects public segments’ intention to comment, their perceptions of legitimacy of the resulting rules, trust in agencies, and control mutuality between the public and the agency. This work describes two controlled, randomized experiments (N = 149; N = 250) that capture public segments’ reactions to AI use in analyzing comments in the presence or absence of opinion spam. We show that public segmentation is a key aspect in shaping attitudes and behaviors regarding the use of AI for e-rulemaking purposes. These findings suggest that communicating effectively with publics is essential for agencies, and that the use of AI does not make the publics’ attitudes differ.

This study examined the communicative action in problem solving model through data science-driven approaches to enhance the understanding of online publics’ communication behaviors. Using ChatGPT, the study analyzed YouTube comments from news channels that covered a contentious entertainment issue with multiple related events. The findings indicated that communication behaviors changed over time and manifested in diverse combinations. In addition, the study demonstrated that aware publics in the digital era were not merely passive; rather, they engaged in communication activities similar to active publics. Furthermore, it identified distinct communication behaviors associated with certain types of publics, indicating that public types also evolve dynamically across events. The results suggested that the communicative action in problem solving model served as a valuable framework for examining online communication behaviors in the digital era. Based on these insights, this study offered both academic and practical contributions to the field.