Young people’s critical capacity regarding digital advertising reproduces social inequalities

According to a pioneering study by UPF, young people from the lower classes have less critical capacity regarding digital advertising personalization strategies than those from the upper classes.

Universitat Pompeu Fabra - Barcelona

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A recent study by Pompeu Fabra University (UPF) reveals that socioeconomic conditions are a determining factor in young people’s ability to identify digital advertising personalization strategies. The lower young people’s socioeconomic status is, the more their ability to detect algorithmically personalized advertising also declines. Therefore, the study concludes that digital advertising is exacerbating structural inequalities and warns that algorithmic awareness cannot be understood as an individual cognitive ability but should be linked to people’s social environment.

To date, several studies had found that youth itself is already a factor of algorithmic vulnerability, due to the younger age and lower maturity of people in this demographic group. But this UPF study pioneers the examination of the relationship between young people’s abilities in this field (their level of digital advertising literacy) and their socioeconomic status and gender. 

The study, recently published by the journal Technology in Society, was led by Mònika Jiménez, director of the Communication, Advertising and Society (CAS) research group of the UPF Department of Communication. The main author of the article is Carolina Sáez, a researcher from the same research group, with Isabel Rodríguez-de-Dios (University of Salamanca) as a co-author.

1,200 young Catalans from different socio-economic backgrounds surveyed

The researchers conducted an online survey of 1,200 young people in Catalonia aged between 14 and 30 who had different profiles in terms of sociodemographic status and gender. To determine their socioeconomic status, each subject’s place of residence -one of the data collected by the survey- was cross referenced with the Government of Catalonia’s Territorial Socioeconomic Index (IST). 

In the survey, the young people had to rate eight statements related to various aspects of algorithmic advertising as being true or false. Among other issues, they were asked about companies’ ability to cross-reference data between different devices used by the same person; to segment people into different groups according to their habits and behaviours to send them different types of advertisements, and the role of cookies to enable this; or the possibility of displaying different adverts on the same web page according to each user’s profile or personalizing them based on what is entered in a search engine, the contents of an email or what is said out loud. 

Socioeconomic status marks critical capacity regarding advertising algorithms

The results of the study show that overall young people have a good level of digital advertising literacy. On average, they correctly answered 6 of the 8 statements for classifying as true or false. However, the success rate of young people with a more privileged economic background is higher than that of those in the lowest socioeconomic stratum. Although the gender factor carries less weight than social class, it should be noted that girls always score better than boys in the same socioeconomic group. Girls' scores range from 6.2 (lower class) to 6.8 (upper class), while boys' range from 5.8 (lower class) to 6.4 (upper class).

Four out of 10 respondents do not notice that the ads on a website change according to the user’s profile

The study also reveals that young people understand the most explicit strategies of persuasion, but less so the implicit mechanisms that enable this (related to data collection and processing). “They are also better at detecting algorithmic advertising strategies that they learn from their own experience than those that are transmitted to them in an abstract way”, Carolina Sáez (UPF) explains. As they tend to consult social networks on their mobile phones, they are not so skilled at detecting advertising personalization through websites. In fact, the statement with the highest percentage of wrong answers is the one that refers to the possibility of seeing different ads when browsing the same website (4 out of 10 considered that this is not possible). 

Confidence in one’s own knowledge does not always match the reality

In addition, on a scale of 1 to 5 the young people had to rate their level of self-confidence in the answers provided in the previous statements, since another of the objectives of the study was to compare their objective and subjective knowledge. The average score for this self-confidence scale was 3.94. “This shows that young people generally feel confident in their own abilities, although their subjective perception of what they know does not always coincide with their real level of knowledge”, Carolina Sáez (UPF) warns.

However, this score varies greatly according to the young people’s profile and, in this case, the gender factor is far more relevant than in the case of objective knowledge. While in the case of boys self-confidence increases as socioeconomic status rises (from 3.8 to 4.2), in the case of girls it is the opposite (it falls from 4.15 to 3.7).

Lack of critical vision regarding gender and social class stereotypes of algorithmic advertising

In another part of the study, the youths had to identify the target audience of four Instagram ads about cryptocurrencies and gambling (in these two cases, with regard to gender); and about financial education programmes and stock market investments (in these two cases, with regard to social class). The results reveal that, with little critical distance, young people reproduce the same gender and class stereotypes as perpetuated by the algorithms themselves.

Most of the youths responded that the first two ads were targeting men, based on the stereotype that links financial risk-taking and the male gender. This bias manifested itself more clearly among upper-class respondents. In other words, gender bias is lower among young people from lower socioeconomic backgrounds. 

Concerning financial education adverts, the youths mostly responded that they were targeting lower-class young people, based on the cliché that this group requires more training to learn how to manage its money. In contrast, they mostly associated advertising on stock investments with upper-class people.

Greater control is needed over advertising algorithms that accentuate structural inequalities

In view of these results, the study deems that there is a need to critically monitor algorithmically personalized advertising systems that can reproduce structural social and gender inequalities and calls for greater transparency on this issue from the companies responsible for them. It also insists on strengthening young people’s digital literacy to address not only knowledge gaps, but also overconfidence.

Reference article:

Carolina Sáez-Linero, Isabel Rodríguez-de-Dios, Mònika Jiménez-Morales, Algorithmic personalization and social inequality: young people’s knowledge and perceptions of bias in digital advertising, Technology in Society, Volume 86, 2026, 103287, ISSN 0160-791X, https://doi.org/10.1016/j.techsoc.2026.103287.

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Journal

Technology in Society

DOI

10.1016/j.techsoc.2026.103287 

Method of Research

Survey

Subject of Research

People

Article Title

Algorithmic personalization and social inequality: young people's knowledge and perceptions of bias in digital advertising

Article Publication Date

2-Mar-2026

 

Struggling to identify emotions may increase vulnerability to TikTok addiction

Research shows that problems with focus and identifying emotions may make young people more vulnerable to short video addiction, but mental training can help

Frontiers

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No matter where we turn on social media, short videos are everywhere. Repeated exposure to this brief, information-dense, and rewarding content stimulates the brain in a way that tells us the experience is pleasurable or satisfying. If indulged in too much, people may develop short video addiction (SVA), a maladaptive pattern where viewers are more prone to having difficulties regulating their short video consumption. With the proliferation of short videos online, SVA is a growing concern as it impacts efficiency in daily life and negatively affects psychological and physical health. This makes understanding this relatively new type of addiction vital: not much is known about the psychological mechanisms that increase vulnerability.

Now, new research done in China has examined how attachment anxiety – a relationship pattern characterized by fear of abandonment which is often shaped in early childhood – contributes to SVA. The results were published in Frontiers in Psychology.

“We show that higher levels of attachment anxiety are associated with a greater risk of SVA,” said first author Haodong Su, a lecturer at the College of Humanities at Anhui Science and Technology University. “Poorer attentional control, or control over what we choose to ignore or focus on, as well as difficulties with processing one’s own or others’ emotions can explain this relationship in part.”

Pathways to addiction

For their study, the researchers recruited 342 students aged 18 to 22 and used different scales to measure their levels of SVA, attachment anxiety, attentional control – commonly referred to as concentration – and alexithymia, a character trait characterized by difficulty identifying and describing emotions. Previous research suggests that alexithymia is relatively common among young people, especially during key developmental stages or when confronted with stress.

The results showed that higher levels of attachment anxiety increased the likelihood of developing SVA. This susceptibility may be shaped by both attentional control and alexithymia, both mechanisms that shape emotional processing. Previous research has shown that higher levels of attachment anxiety lead to decreased attentional control and that people with higher levels of attachment anxiety tend to exhibit more severe alexithymic traits. When these mechanisms fail to fully regulate emotions, people may start to rely on external regulators, such as short videos, to cope with the negative effects.

“Individuals with more severe alexithymia symptoms showed significantly higher levels of SVA, indicating that having difficulties with identifying and expressing emotions may increase reliance on short videos as a form of emotional escape,” explained Su.

Poorer attentional control, which in turn often intensifies and heightens alexithymia levels, also mediated the relationship between attachment anxiety and SVA.

Protected by attention

While poor attentional control can make teens more susceptible to becoming addicted to short videos, training one’s concentration may also achieve the opposite effect and play a protective role in the development of SVA.

“Young people who are better able to regulate and sustain their attention are less likely to develop addictive patterns of short video use, even when they experience emotional difficulties such as attachment anxiety,” Su pointed out.

Small measures, like setting time limits on video consumption, scheduling designated phone-free periods, or establishing routines that encourage reflection on emotions, can be useful starting points for young adults struggling with focus or alexithymia.

“Attentional control is not a fixed ability and can be improved with practice,” said Su. “Strategies such as mindfulness training, reducing multitasking, and deliberately scheduling periods of focused activity may help strengthen attention regulation and reduce the risk of SVA.”

The researchers note that the data used in the study was self-reported by students and may be biased. The study’s cross-sectional design provides a snapshot, and the findings show associations rather than direct cause-and-effect relationships. The sample also was gender-imbalanced, with around 72% of the participants being male. As attachment anxiety and attentional control differ by gender, future research with more balanced samples will be important to determine whether these patterns hold across genders. Studies spanning longer periods of time are also necessary to confirm the relationships identified here.

“Our findings show that strengthening attentional control and emotional awareness, rather than relying solely on restricting technology use can be effective to prevent SVA,” concluded Su. “Short video addiction is not only about screen time, but also about emotional and cognitive regulation.”

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Journal

Frontiers in Psychology

DOI

10.3389/fpsyg.2026.1764536 

Method of Research

Experimental study

Article Title

From Attachment Anxiety to Short Video Addiction: The Roles of Attentional Control and Alexithymia

Article Publication Date

26-Mar-2026

Powering the future: swarm intelligence unlocks optimal integration of distributed generation and fast EV charging in smart cities

Beijing Institute of Technology Press Co., Ltd

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Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities

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Credit: GREEN ENERGY AND INTELLIGENT TRANSPORTATION

As cities worldwide accelerate toward electrification and decarbonization, the convergence of distributed energy resources and electric mobility is reshaping the architecture of modern power systems. Distributed Generation (DG), encompassing technologies such as solar photovoltaics, wind turbines, and fuel cells, has emerged as a critical enabler for reducing transmission losses and enhancing energy resilience. At the same time, the rapid adoption of electric vehicles (EVs) is introducing unprecedented demand patterns, placing new stress on existing distribution networks. The challenge lies not merely in deploying these technologies, but in orchestrating their integration in a way that ensures grid stability, efficiency, and sustainability.

 

This study addresses a pivotal question at the heart of smart city development: how can DG units and fast Electric Vehicle Charging Stations (EVCS) be optimally allocated within a power distribution network to maximize performance while minimizing adverse impacts? Rather than treating these components independently, the research advances a unified optimization framework that simultaneously determines the placement and sizing of both DG units and fast EVCS. By doing so, it directly tackles the complex interplay between generation and load introduced by high EV penetration, which is often associated with increased power losses, voltage instability, and infrastructure strain.

 

The proposed approach leverages two bio-inspired swarm intelligence algorithms—Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC)—to solve this high-dimensional, nonlinear optimization problem. These algorithms emulate collective behaviors observed in nature, enabling efficient exploration of large solution spaces. Their performance is rigorously evaluated on both the IEEE 69-bus test system and a real-world 33 kV distribution network in Ghana’s Ashanti region, offering both theoretical validation and practical relevance.

 

The results demonstrate a compelling enhancement in network performance when DG units and fast EVCS are optimally co-located. Under high penetration scenarios—up to 40% integration—the system achieves a remarkable reduction in active power losses of up to 68%. This improvement significantly surpasses many conventional planning approaches, highlighting the value of coordinated allocation strategies. Moreover, voltage profiles across the network are substantially stabilized, with deviations maintained within the stringent ±5% limits defined by international standards. Notably, PSO consistently outperforms ABC in minimizing voltage deviation indices, indicating superior convergence behavior and solution quality in this application context.

 

Beyond numerical gains, the implications of these findings extend to broader societal benefits. Reduced power losses translate directly into improved energy efficiency and lower operational costs, while enhanced voltage stability contributes to more reliable electricity delivery. In the context of rapidly urbanizing regions—particularly in emerging economies—such improvements are essential for supporting both residential and commercial electrification. Furthermore, by facilitating higher penetration of renewable DG sources alongside EV infrastructure, the proposed framework contributes to significant reductions in greenhouse gas emissions, aligning with global climate targets.

 

Looking ahead, the integration strategy outlined in this study opens new pathways for intelligent energy planning in future smart cities. The simultaneous optimization of DG and EVCS can be further extended to incorporate dynamic factors such as real-time load variability, renewable generation intermittency, and vehicle-to-grid (V2G) interactions. Incorporating advanced forecasting techniques and adaptive control mechanisms could further enhance system responsiveness and resilience. Additionally, the application of hybrid or next-generation metaheuristic algorithms may yield even greater optimization performance, particularly in large-scale, heterogeneous networks.

 

In practical terms, this research provides a scalable and adaptable framework for utilities, policymakers, and urban planners seeking to design energy systems that are both efficient and future-ready. By demonstrating that coordinated deployment strategies can unlock substantial technical and economic benefits, it challenges conventional siloed approaches to infrastructure planning.

 

Ultimately, this work underscores a fundamental shift in how energy systems are conceived: not as static networks, but as dynamic ecosystems where generation, consumption, and mobility are deeply interconnected. Through the intelligent application of swarm-based optimization, it offers a forward-looking solution to one of the most pressing challenges in sustainable urban development, paving the way for cleaner, smarter, and more resilient cities.

 

 

Reference

 

Author: Isaac Prempeh a,  Albert K. Awopone a, Patrick N. Ayambire a, Ragab A. El-Sehiemy b

 

Title of original paper: Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities

 

Article link: https://www.sciencedirect.com/science/article/pii/S2773153725000313

Journal: Green Energy and Intelligent Transportation

 

DOI: 10.1016/j.geits.2025.100281

 

Affiliations:

a Department of Electrical and Electronics Engineering, Akenten Appiah-Menka University of Skills Training and Entrepreneurial Development, Kumasi, Ghana

b Electrical Engineering Department, Kafrelsheikh University 33516, Kafrelsheikh, Egypt

 

 

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Journal

Green Energy and Intelligent Transportation

DOI

10.1016/j.geits.2025.100281 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

Optimal allocation of distributed generation units and fast electric vehicle charging stations for sustainable cities

Article Publication Date

1-Sep-2026