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Now you see me, now you don’t: How subtle ‘sponsored content’ on social media tricks us into viewing ads

People are not as good at spotting them as they think. If people recognized ads, they usually ignored them – but some, designed to blend in with your friends’ posts, flew under the radar.

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How many ads do you see on social media? It might be more than you realize. Scientists studying how ads work on Instagram-style social media have found that people are not as good at spotting them as they think. If people recognized ads, they usually ignored them – but some, designed to blend in with your friends’ posts, flew under the radar.

“We wanted to understand how ads are really experienced in daily scrolling — beyond what people say they notice, to what they actually process,” said Maike Hübner, PhD candidate at the University of Twente, corresponding author of the article in Frontiers in Psychology. “It’s not that people are worse at spotting ads. It’s that platforms have made ads better at blending in. We scroll on autopilot, and that’s when ads slip through. We may even engage with ads on purpose, because they’re designed to reflect the trends or products our friends are talking about and of course we want to keep up. That’s what makes them especially hard to resist.”

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The scientists wanted to test how much time people spent looking at sponsored versus organic posts, how they looked at different areas of these different posts, and how they behaved after realizing they were looking at sponsored content. They randomly assigned 152 participants, all of whom were regular Instagram users, to one of three mocked-up social media feeds, each of which was made up of 29 posts — eight ads and 21 organic posts. 

They were asked to imagine that the feed was their own and to scroll through it as they would normally. Using eye-tracking software, the scientists measured fixations — the number of times a participant’s gaze stopped on different features of a post — and dwell time, how long the fixations last. A low dwell time suggests that someone just noticed the feature, while a high dwell time might indicate they were paying attention. After each session, the scientists interviewed the participants about their experience.

Although people did notice disclosures when they were visible, the eye-tracking data suggested that participants paid more attention to calls to action — like a link to sign up for something — which could indicate that this is how they recognize ads. Participants were also quick to recognize an ad by the profile name or verification badge of a brand’s official account, or glossy visuals, which caused participants to express distrust. 

“People picked up on design details like logos, polished images, or ‘shop now’ buttons before they noticed an actual disclosure,” said Hübner. “On brand posts, that label is right under the username at the top, while on influencer content or reels, it might be hidden in a hashtag or buried in the ‘read more’ section.”

Although the scientists found that the ads often went unnoticed, if people realized that the content wasn’t organic, many of them stopped engaging with the post. Dwell time dropped immediately.

#ad

This was less likely to happen to ads that blended in better, with less polished visuals and a tone and format more typical of organic content. If ad cues like disclosures or call-to-action buttons weren’t noticed right away, they got similar levels of engagement to organic posts. 

“Many participants were shocked to learn how many ads they had missed. Some felt tricked, others didn’t mind — and that last group might be the most worrying,” said Hübner. “When we stop noticing or caring that something is an ad, the boundary between persuasion and information becomes very thin.”

The scientists say these findings show that transparency goes well beyond just labelling ads. Understanding how people really process ads should lead to a rethink of platform design and regulation to make sure that people know when they’re looking at advertising. 

However, this was a lab-based study with simulated feeds, and it’s possible that studies on different cultures, age groups, or types of social media might get different results. It’s also possible that ads are even harder to recognize under real-life conditions.

“Even in a neutral, non-personalized feed, participants struggled to tell ads apart from regular content,” Hübner pointed out. “In their own feeds which are shaped around their interests, habits, and social circles it might be even harder to spot ads, because they feel more familiar and trustworthy.”

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Profit alone is a poor measure of success, study shows companies can look efficient while harming the planet

Firms that appear highly efficient at generating revenue can perform far worse when their environmental footprint are included in the calculation.  

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Companies celebrated for strong financial performance may actually be inefficient once their environmental impact is taken into account, according to new research from the University of Surrey. 

The study, published in the European Journal of Operational Research, shows that firms that appear highly efficient at generating revenue can perform far worse when their environmental footprint are included in the calculation.  

To tackle this problem, researchers developed a new way to measure “sustainable corporate efficiency”, combining traditional financial metrics with environmental data such as energy consumption, carbon emissions and revenues generated from environmentally friendly products and services.  

Dr Menelaos Tasiou, co-author of the study and Senior Lecturer in Finance at the University of Surrey, said: “Businesses have long been judged on how efficiently they turn resources into profit. But if those profits come with large environmental costs, the picture changes completely. What we show is that true efficiency means generating revenue while also reducing the environmental damage caused by production. In other words, profitability alone can mask how wasteful a business really is when environmental costs are considered.  

The research analysed more than 2,800 publicly listed companies across 61 countries between 2010 and 2022, creating one of the largest global datasets measuring how sustainable companies are, when both financial performance and environmental impact are assessed together.  

The team combined company financial records, in alignment with the green economy (defined as a low carbon, resource efficient and socially inclusive economy), with environmental disclosures such as energy use and greenhouse gas emissions. They then applied a machine learning technique known as Convexified Efficiency Analysis Trees (CEAT) to estimate how efficiently companies convert resources into revenue while minimising pollution.  

Unlike older approaches, the method models the reality that production creates both desirable outputs, such as revenue, and undesirable ones, such as emissions. This allows companies to be compared on how well they balance profit with environmental performance.  

The results found a moderate link between financial efficiency and environmental efficiency, meaning many firms that are strong financially are not necessarily good at managing their environmental impact.  

The study also found large differences across industries and countries. Firms operating in sectors with high emissions, such as manufacturing and energy, often lagged behind leaders that were better at reducing carbon intensity while maintaining revenue.  

Dr Tasiou continued: “Measuring efficiency in this broader way can help investors, regulators and policymakers identify companies that are genuinely prepared for a low carbon economy. Stronger management capability plays a key role. Firms with more capable management teams were more likely to balance profitability with environmental responsibility, suggesting that leadership decisions can strongly influence sustainable performance.  

“As governments push towards net zero and investors scrutinise environmental performance more closely, companies that fail to integrate sustainability into their operations risk falling behind.” 

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Reminder to marketing people: Missing information can misinform

You don’t need bad actors for people to get the wrong idea. Incomplete information can be enough.

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To get people to pay attention, you have to make it engaging. But what makes content engaging often comes at the cost of detail – shaping what people learn and what they think they’ve learned. The result: People can come away with the wrong idea, even when what they read isn’t factually wrong.

That tension sits at the core of research from Marta Serra-Garcia, a behavioral economist at the University of California San Diego’s Rady School of Management. The study, published in the American Economic Review, examines how incentives in the online attention economy shape the way scientific information is communicated – and what readers ultimately take away from it.

A trade-off in the attention economy

You don’t need bad actors for people to get the wrong idea. Incomplete information can be enough.

Crucially, the research finds that attention-grabbing summaries are not more likely to be factually inaccurate. Instead, they tend to include less information – especially key details about how studies were conducted.

“This is not a simple story that clickbait is bad,” said Serra-Garcia, associate professor of economics and strategy and Phyllis and Daniel Epstein Chancellor’s Endowed Faculty Fellow at UC San Diego’s Rady School. “You need to get people’s attention in order for them to learn something, and it’s good to encourage curiosity. Yet there’s a trade-off: Material designed to engage can also unintentionally contribute to the kinds of misunderstandings that can fuel misinformation.”

The finding comes from a large, multi-stage experimental study in which freelance writers produced nearly 600 summaries of actual scientific research, and more than 3,700 participants were then tested on what they learned from them.

Why “in mice” matters

In one study used in the experiment, a compound in broccoli reduced cancer cell growth – in mice. Leave out those last two words, and the finding can sound far more directly relevant to human health than it actually is.

“Why can’t we say ‘in mice’?” Serra-Garcia said. “It’s not very hard to add. It’s two words. But once you say ‘in mice,’ maybe fewer people will click.”

Study results were consistent. Summaries written to attract attention were shorter, easier to read and more engaging – but included less detailed information, especially about sample sizes and methods.

Given the option to seek out more information, most readers did not. That mirrors real-world behavior: Studies of social media use suggest most content is shared without users ever clicking through to read more.

Among those who relied on summaries alone in Serra-Garcia’s study, knowledge dropped by about 6-7 percentage points. Readers were also more likely to draw incorrect conclusions – such as assuming findings applied to humans or reflected firm medical guidance.

Inside the experiments

To isolate these effects, Serra-Garcia conducted a multi-stage experimental study. In the first stage, 149 freelance writers produced nearly 600 summaries of the same set of studies – covering topics such as cancer, sleep, vaccines and climate – under different instructions: to inform readers accurately, or to attract attention by encouraging clicks or shares. 

In the second stage, more than 3,700 participants read those summaries under different conditions, including whether they could click through for more information.

The results held across experiments: Attention-driven summaries increased engagement and prompted some readers to learn more – but left many others with less complete understanding.

AI and the attention economy

The same pattern emerged when a human wasn’t doing the writing. In additional tests, when a large language model was prompted to attract attention, it also produced less detailed summaries – suggesting the effect is driven less by who creates the content than by the objective it’s optimized for.

For Serra-Garcia, the findings point to an ongoing challenge for researchers, journalists and institutions alike.

“How do you make science engaging and important to readers,” she said, “without missing the essentials that convey the full picture?” 

The research was funded in part by National Science Foundation grant no. 2343858. 

Read the full study: “The Attention – Information Trade-off.” 

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If you’re a perfectionist at work, your boss’ expectations may matter more than your own, research finds

Help your employees by clarifying expectations through regular feedback and performance conversations to reduce role ambiguity, as doing so can provide employees with a better understanding of role expectations and enhance mutual understanding of those standards.

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If you’re among the 93% of people who struggle with perfectionism at work, new research suggests that your experience may depend less on your own high standards and more on whether those standards meet your supervisor’s expectations. 

Researchers from the University of Florida Warrington College of Business found that whether perfectionism helps or harms employees depends largely on whether employees’ personal standards align with their supervisors’ expectations. 

Specifically, they looked at the connection between employees’ self-oriented perfectionism, or the expectations of flawlessness they set for themselves, and supervisors’ other-oriented perfectionism, which reflects the extent to which they set excessively high standards for and critically evaluate their employees’ performance. 

Using data from more than 350 employees and about 100 supervisors, the researchers found that perfectionism’s impact depends on whether employees’ standards align with what their supervisors expect and how clearly those expectations are understood. 

When employees’ personal standards are aligned with their supervisors’ expectations, they tend to experience less role ambiguity, meaning they have less uncertainty about the expectations and standards for their role, why those standards matter and the consequences of not meeting them. This clarity in their work is linked to better performance, lower burnout and higher job satisfaction. 

“Problems between employees and their supervisors are more likely to arise when these expectations don’t match,” explained Brian Swider, Beth Ayers McCague Family Professor.

The most difficult situation occurs, Swider and his colleagues found, is when supervisors expect higher levels of perfectionism than employees expect from themselves. In these cases, employees reported greater uncertainty about their roles, along with worse work outcomes including higher burnout and lower job satisfaction.

“If you’re an employee who struggles with perfectionism at work, our findings suggest that understanding your supervisor’s expectations may be just as important as managing your own tendencies towards perfectionism,” Swider said. “Talking to your supervisor about priorities, standards and how your performance will be evaluated can help reduce uncertainty and ensure you both share a clear understanding of what success looks like.”

The researchers have similar recommendations for employers: help your employees by clarifying expectations through regular feedback and performance conversations to reduce role ambiguity, as doing so can provide employees with a better understanding of role expectations and enhance mutual understanding of those standards.

The researchers also recommend that organizations should consider how employees and supervisors are paired, as mismatched expectations can increase stress, reduce job satisfaction and ultimately impact performance. 

The research, “The influence of employee-supervisor perfectionism (in)congruence on employees: a configurational approach,” is published in Organizational Behavior and Human Decision Processes

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