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Labels are everything: New study reveals role of popularity in news articles

The way that news organizations label articles could directly influence how much attention they receive and ultimately impact their revenue.

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News readers often click on articles not based on topic but rather the behavior of their fellow audience members, according to new research from the University of Georgia.

And the way that news organizations label those articles could directly influence how much attention they receive and ultimately impact their revenue.

When you go to a news organization’s homepage, they typically label articles that readers are engaging with the most. The researchers focused on two common labels: “most shared” and “most read.”

“These types of labels are not going anywhere. Popularity even in news labels is a psychological phenomenon,” said Tari Dagago-Jack, lead author of the study and an assistant professor of marketing in the UGA Terry College of Business. “Popularity labels on news outlets are taking advantage of the idea that we follow the lead of others and that our decision-making is influenced by what other people are doing.”

Article section labels influence click rate

At first glance, you may assume that these labels, “most shared” and “most read,” mean the same thing: A lot of people checked out the article. But there’s a clear difference that consumers pick up on.

“If something is most shared, we might assume that means many people had to read it and then deem it interesting enough or important enough to pass it on,” Dagogo-Jack said. “But then there’s this other reality where we know a lot of things that are widely shared are often extremely frivolous like cat videos or funny memes.”

In nine surveys and experiments involving hundreds of people, the study found respondents interpreted “most read” stories as being more informative. “Most shared” articles were viewed as less serious and more entertainment based.

“The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.” —Tari Dagago-Jack, Terry College

“We as readers have two primary motives: to be informed or to be entertained — that is, for a welcome diversion,” said Dagogo-Jack. “At a baseline level, we were finding that people were choosing ‘most read’ at a way higher rate than ‘most shared.’ The primary goal for reading news is to gain information, and the label ‘most read’ is a stronger signal of an article’s information value.”

That means if editors want certain articles to get more attention, they should tailor the label to the readers’ goals.

Knowing your audience, content is key for engagement

The same went for articles advertised on social media. Posts from faux news organizations that had captions describing a more educational article as “most shared” received fewer clicks.

This wasn’t the case, however, for news stories that were less serious and newsworthy. In that case, the “most shared” label worked as well as the “most read” label.

It’s a key message for reporters, editors and web developers: Know your audience and your content.

“People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?” —Tari Dagago-Jack

“For pop culture, sports or music — more entertainment — in those sections you should highlight what is ‘most shared,’” Dagogo-Jack said. “But for world news, politics and science sections, you should be using things like ‘most read’ or ‘most viewed.’”

Dagogo-Jack also recommends putting thought into labels. Ambiguous choices like “trending” or “most popular” may stump readers altogether, as there are so many things this could mean.

“Providing these lists helps us get over information overload or choice paralysis,” he said. “It’s a crutch and makes the decision process easier, but I often wonder: At what cost?

“You’re clicking on something that a lot of people like and social proof is valuable, but it may not necessarily provide what you are looking for, and you just gave up on the search. People should ask themselves: Why am I even clicking on this thing? Is it just because everyone else read it?”

This study was published in the Journal of Consumer Research and was co-authored by New York University assistant professor Jared Watson.

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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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