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The purpose of this study is to explore teen-adult dialogic interactions during the co-design of data literacy activities in order to determine the nature of teen thinking, their emotions, level of engagement, and the power of relationships between teens and adults in the context of data literacy. This study conceives of co-design as a learning space for data literacy. It investigates the teen–adult dialogic interactions and what these interactions say about the nature of teen thinking, their emotions, level of engagement and the power relationships between teens and adults.

The study conceives of co-design as a learning space for teens. Linguistic Inquiry and Word Count (LIWC-22), a natural language processing (NLP) software tool, was used to examine the linguistic measures of Analytic Thinking, Clout, Authenticity, and Emotional Tone using transcriptions of recorded Data Labs with teens and adults. Linguistic Inquiry and Word Count (LIWC-22), a natural language processing (NLP) software tool, was used to examine the linguistic measures of Analytic Thinking, Clout, Authenticity and Emotional Tone using transcriptions of recorded Data Labs with teens and adults.

LIWC-22 scores on the linguistic measures Analytic Thinking, Clout, Authenticity and Emotional Tone indicate that teens had a high level of friendly engagement, a relatively low sense of power compared with the adult co-designers, medium levels of spontaneity and honesty and the prevalence of positive emotions during the co-design sessions.

This study provides a concrete example of how to apply NLP in the context of data literacy in the public library, mapping the LIWC-22 findings to STEM-focused informal learning. It adds to the understanding of assessment/measurement tools and methods for designing data literacy education, stimulating further research and discussion on the ways to empower youth to engage more actively in informal learning about data.

This study applies a novel approach for exploring teen engagement within a co-design project tasked with the creation of youth-oriented data literacy activities.

This study aims to investigate the global issues of youth unemployment using bibliometric analysis covering the period from 1983 to 2022. There is a dearth of a bibliometric study analysis on unemployment, particularly youth unemployment even at the global level. The present study seeks to fill this gap by exploring the prominent studies related to youth unemployment at the global level.

Using VOSviewer software bibliometric results and the Scopus database, the study uncovered the most frequently cited, prominent and influential authors, as well as the institutions that have worked on youth unemployment and the most prominent keywords published on youth unemployment.

Nearly 80% of the research articles on youth unemployment were published from 2005 to 2022, and a significant increase in publication after 2012 is observed. Based on the published papers, the most studied determinants of youth unemployment are increased levels of regional economic advances, state demographics, relocation, household conditions, regional openness and export/import. Economic freedom, labour market reforms, economic growth, high proportion of part-time employment, active labour market policies, minimum wage norms, extent of bargaining scope and alignment are prominent determinants that reduce unemployment at large and improve labour market performance of youth in particular.

Bibliometric analysis, like the present study, can narrow down the most prominent sources of information on youth unemployment for beginners in this field of research.

This bibliometric study on youth employment assists researchers and policymakers in understanding and summarizing the necessary determinants of youth employment that are already being identified and studied based on practical evidence from the authors’ case study-based research work. The present study raises the issue of youth unemployment at large. It helps in identifying factors in one place and thus new researchers can use it as a starting point for their research on youth unemployment. It helps in providing clustering of factors. It highlighted the significant studies, authors and institutions working in this field.

On social implication, it can be argued that studies on topics related to human resources have a direct impact on society standards. By producing scientific knowledge that aids in the recognition of the complexities of human processes and behaviours, social science research significantly contributes to the enrichment of the community as a whole. When young people are unemployed, it causes social unrest and may increase crime and terrorism, all of which contribute to political instability. Youth unemployment causes psychological illness because of anxiety, alienation and depression. As a result, it causes social instability and necessitates immediate attention in all societies. The present study highlights that although the unemployment rate of youth is significantly higher in underdeveloped countries than the developed countries, their representation in the publication is significantly low. This under-representation of countries shows their lack of commitment to society in working on the issue of youth unemployment.

It is assumed that there are plenty of research studies on unemployment, particularly at the global level. However, various domains of researchers may require a bibliometric kind of analysis wherein they may get an idea about the prominent number of literatures arguing concerning issues at large, in the sense of “focused studies” covering the comprehensive viewpoint on youth unemployment. The paper aimed to emphasize the topic of youth unemployment, its development in the research field and the usefulness of bibliometric analysis in social sciences in general, and youth unemployment in particular.

This study aims to follow a rigorous approach to identify, critically analyze and synthesize 75 papers published from 2000 to 2022.

The study presents a systematic literature review on identity expressiveness (IE), clarifying and expanding what is currently known about the concept.

To synthesize current knowledge on IE, the study uses the overarching framework of antecedents-phenomenon-consequences, using this same framework to identify gaps and future research directions. The findings show individual and brand-related factors such as the need for uniqueness and anthropomorphism as antecedents of IE, and eWOM/WOM, impulse purchases and upgrading to more exclusive lines as consequences of IE.

The study contributes to theory by synthesizing and mapping current understanding of the state of knowledge on the concept of IE while highlighting gaps in the extant literature and paving future research directions for scholars in the field.

The study offers useful insights for practitioners, broadening marketers’ actionable options in identity-based marketing. Marketers can use insights from this study to inform marketing strategy and communication campaigns for different types of brands.

To the best of the authors’ knowledge, this study is the first of its kind and offers an integrative review of the current literature on IE, thus enhancing understanding of the concept, its antecedents and consequences. The study also contributes to knowledge by highlighting future research priorities for researchers in this field of enquiry.

This work aims to establish the relationship between painting art and sustainability, which allows for highlighting implications likely to improve sustainability for humanity's welfare.

To achieve this objective, painting art is measured by a composite index aggregating the quantity and quality represented by the market value. As for sustainable development, it is represented by a composite index comprising three variables: the climate change performance index (ecological dimension), the wage index reflecting distributive justice (social dimension) and the gross domestic product (economic dimension). The composite indices were determined through adjusted data envelopment analysis. In addition, two other methods are used in this work: correlation analysis and a neural network method. These methods are applied to data from 2007 to 2021 across the world.

The correlation method highlighted a perfect positive correlation between painting art and sustainability. As for the neural network method, it revealed that the quality of painting has the greatest impact on sustainability. The neural network method also showed that the most positively impacted variable of sustainability by painting art is the social variable, with a pseudo-probability of 0.90.

The relationship between painting art and sustainability is underexplored, in particular in terms of statistical analysis. Therefore, this research intends to fill this gap. Moreover, analysis of the relationship between both using composite indices computed via an original method (adjusted data envelopment analysis) and a neural network method is nonexistent, which constitutes the novelty of this work.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-01-2023-0006