At the top of the chart for dating older partners, we find men in Wyoming, North Dakota, and Alaska clustered at the top, with a near-11-year average gap in their relationships. Alaska is a genuine outlier with women who have the largest average age gap of 20.57 years. West Virginia trails by three years, averaging 17.83. Women in New Hampshire, Massachusetts, and Maryland are the least open to dating someone older than them.

The data shifts when we look at people who are dating or willing to date someone younger. Hawaii leads for both genders and the gap is striking. Men’s average acceptable gap is dating someone up to 18.59 years younger, nearly double that of women, who are only willing to date someone up to nine years younger. Alaska and New York are near the top in willingness to date someone older, but they sink near the bottom of the rankings when it comes to men dating someone younger.

Keep in mind that the respondents were Tawkify’s matchmaking clients, a self-selected group of people seeking relationships rather than a national sample, but the data is still valuable and gives us logical insights. Small-state results might indicate a smaller dating pool, or it could be correlational with fewer respondents. The rankings are a vivid snapshot of the preferences of a wide pool of singles and serve as an interesting conversation starter about modern dating.

The post Study Examines American Age-Gap Difference Preferences appeared first on Infographics Archive.

A lone outlier is West Virginia, the only state to favor intrapersonal solitary learning, which is the least popular style nationwide. It’s curious to see one state buck a near-universal preference for study buddies.

The team emphasizes the importance of recognizing that they measured search interest in learning styles, not evidence of how our brains work or how we retain information. So, this study is less about neuroscience and more a cultural snapshot of how Americans prefer to learn. While we might prefer certain learning styles, there is no evidence that a specific learning style that “matches” us makes us retain more information. Whatever the science says about styles, the map captures something real: studying is personal, regional, and shaped by culture as much as our cognition.

The post New Map Displays Patterns in Learning Style Preference appeared first on Infographics Archive.

Preply used five metrics to create their rankings: Flesch readability score, percentage of unique words, percentage of rare words, AI transcription accuracy via the Clipto tool, and words per minute. Artists were ranked using submission counts from a mondegreen database. The top song “Blinded by the Light” wins not on speed but on readability. It only scored 85 on Flesch, the least readable song in the study. AI managed to translate only 63% of the song “Empire State of Mind” accurately, showing confusion occurring for a different reason. The song is fast at 158 wpm and has 43% unique words. The song “Saint-Tropez” by Post Malone is highly readable, but its 131 wpm tempo even baffles AI 31% of the time.

We see two distinct rankings emerge from the team’s graphic. Among recent artists, listeners struggled the most to understand Lady Gaga, who had 306 submissions of mishearing, often due to her unusual and theatrical pronunciation style. Taylor Swift is frequently misunderstood, too, with 300 submissions and two songs in the top 20 most misunderstood song list. Kelly Clarkson ranks closely behind her. The most misunderstood artists of all time, not just recent releases, were Elton John, with “Tiny Dancer” alone receiving 214 submissions; Queen, particularly the song “Bohemian Rhapsody”; and Michael Jackson, with “Billie Jean.” This all-time leaderboard skews toward artists with big catalogs, but the per-song counts of mondegreens are striking.

The data doesn’t capture the cultural memory of these mondegreens, like the “Starbucks lovers” memes about Taylor Swift. These mondegreens might outlive the song itself. While data can explain the mechanics of mishearing, the Internet might just be the determiner of which mondegreens become canon.

The post Study Reveals the Most Misheard Song Lyrics appeared first on Infographics Archive.

The team at Ooma helped us understand why this finding matters by highlighting facts and figures about the senior loneliness epidemic and the effects of a simple phone call. The truth is, loneliness goes beyond unpleasantness and becomes a physiological stressor. The graphic highlights figures that illustrate the reality of senior loneliness as a public health crisis. Lonely seniors are at a 50% higher risk of dementia, 32% increased risk of stroke, 28% higher risk of hearing loss, and heart failure patients have a 4x mortality increase if they’re lonely. Isolation is a clinical condition with serious consequences that affects all aspects of health.

A map shows us which seniors are the most at risk based on geographic patterns. It highlights West Virginia seniors as the loneliest, a symptom of their rural lives with limited transportation options, weaker Internet access, and a cultural stigma around admitting loneliness in a tough, self-reliant community.

UT Austin’s call study, along with a trial from BASIL, and a HELPeN nursing student program, provided us with a powerful weapon against the epidemic. It’s a simple phone call. Research points to voice-based interactions as vastly more powerful than text-based interactions, though it’s worth noting a BYU study that found face-to-face contact to be the most common type of interaction. But when in-person visits aren’t possible, as they weren’t during the pandemic, we can’t underestimate the power of a phone call. For many seniors, this call is the reminder they need that someone cares and that they have a connection to the world outside their four walls.

The post Study Proves a Phone Call is Our Best Tool in Fighting the Senior Loneliness Epidemic appeared first on Infographics Archive.

The top three villains on the list are all operatic, larger-than-life figures from the darker corners of the Disney movie catalog. We see Frollo from The Hunchback of Notre Dame at #1, Jadis, the White Witch from Narnia, at #2, and the Horned King from The Black Cauldron at #3. Many of these films aren’t the first titles that come to mind when people think of Disney movies, but that may be part of what allowed these villains to rank so highly. Darker movies allow for darker deeds.

We can also see that villains have evolved over time. Snow White’s Evil Queen and Chernabog from Fantasia are villain archetypes of pure evil with no backstory. The early Disney Renaissance featured villains like Jafar and Ursula, who are theatrical schemers with clear goals. Modern-era villains like Mother Gothel from Tangled, Prince Hans from Frozen, and King Magnifico from Wish are given greater depth to their villainy. We can see how they ended up on the villainous path, and how they use subtler, more manipulative tactics to enact villainy.

To further complicate how we see villainy, Disney has released a lot of material that explores the origins of villains like Maleficent and Cruella. They show us that these villains might be more sympathetic than we first imagined and rewrite them as the wrong protagonists.

The team’s ranking shows us that Disney’s ideas of evil have changed over time and with different genres, storylines, and morally complicated heroes and villains alike. This is ultimately what keeps us coming back to Disney films!

The post Graphic Ranks Disney Villains by Villainousness Level appeared first on Infographics Archive.

New York City is the most difficult metro area to move in or out of, with a score of 77.16 on the Rove lab index. The data points stack up with the Big Apple’s reputation: 3,247.7 people per square mile, the lowest rent turnover in the country at 19.7%, a median rental building age of 65 years, and 212 vehicles per square mile during rush hours. New York is hard to move house in because it’s a hard city to navigate, period. Congestion and stiff competition for space and resources will always present a challenge.

A hard move means different things in different places. In Los Angeles, your biggest struggle is with the traffic. There are 7 hours and 49 minutes of weekday traffic congestion that can seriously slow down your moving truck. D.C. is home to the oldest buildings in the country, which means your rental might be on the sixth floor of a narrow, twisting staircase that repels furniture. Seattle can turn your cardboard boxes to mush with 156 rainy days a year, and Boston will send you stomping through snow drifts with its 23 snow days a year. Every city on the top of the list will extract its own unique toll on moving day.

Looking at the easier cities on the list, we see both advantages and setbacks. Austin has the best renter turnover rate at 49.1%, which means there are plenty of new construction rentals available. The team lists Fresno, Riverside-San Bernardino, and Birmingham as lower-density metro areas with plenty of new housing stock.

The hardest cities to move in and out of are, unfortunately, also the ones that feel the most alive. They’re old, dense, and layered, and the friction of the place is part of the price of moving there.

The post Study Examines Different Moving Experiences in 55 Cities appeared first on Infographics Archive.

Qualtrics surveyed 32 countries and color-coded them by the percentage of people who think AI will improve their work experience. Over 50% of workers in China, Indonesia, Peru, South Africa, and Thailand are optimistic about the effects AI will have on their jobs. In the Anglosphere and Western Europe, workers are much more skeptical, with 35% or fewer feeling that AI is a threat to their work lives. Japan is the most skeptical, with only 17% feeling positively about AI. The team also examined optimism about AI’s effects on the job market. Mexico leads that optimism, and Belgium and Poland tie for the most skeptical.

There are many explanations for why these differences are so stark. China leads the optimistic end of the spectrum, possibly because of the government’s heavy investment and positive messages about AI. People in developing economies are more likely to see AI as a way to bridge gaps and help them reach prosperity through new opportunities and narrower skill gaps. In wealthier nations, AI is framed more as a disruptor of an already stable economy, where satisfied workers feel it will disturb the good.

Research shows that workers can be cautiously optimistic because AI tends to reshape jobs rather than eliminate them wholesale. The global story of AI is still unfolding, and workers’ feelings and attitudes will certainly shape how it unfolds.

The post Map Presents a Vivid View of Emotions Toward AI in the Workplace appeared first on Infographics Archive.

The team’s study included plenty of specific examples. They discussed Welsh as a policy-driven success in language revival. Only 20% of Wales spoke Welsh for 50 years, but thanks to government investment and efforts, 30% of Welsh children now speak the language fluently. Welsh fluency is now viewed as an employment asset, not a stigma like it once was.

French may be a widely spoken language, but Cajuns in Louisiana speak their own endangered dialect. There were millions of Louisiana French speakers in the 1960s, but the language had collapsed by 2011, with only 130,000 speakers. This is a legacy of the language being banned in schools and social stigma. An organized effort called CODOFIL helped slow the decline of Louisiana French, but threats remain.

Cornish is a fascinating example of an “awakened” language. This refers to a once-extinct language being revitalized. A standardized written form of Cornish was developed in 2008, making the language accessible again, and it now has a handful of speakers, with hopes of spreading.

Kaurna is another example of an awakened language, now with 50 speakers, thanks to dictionaries, songs, and formal programs to teach it. It shows that revitalization is slow, meticulous, and multi-generational.

The post Study Examines Endangered Languages and Revival Attempts appeared first on Infographics Archive.

•  Alaska: 23.81%
•  Idaho: 17.24%
•  California: 13.33%
•  Nevada: 12.50%
•  New Hampshire: 11.90%
•  Iowa: 11.90%
•  Washington: 11.28%
•  Oregon: 9.04%
•  Virginia: 8.84%

Frontier states with a growing economy top the list here. We see Alaska, Idaho, Nevada, and Washington rank among the top ten for active labor reallocations in states experiencing population booms and infrastructure development. California, in the third spot, ranks for a different reason. This large, prosperous state has many thriving industries, like tech and entertainment, that will always create job openings and attract hungry talent. Moving to the bottom of the rankings, we find Kentucky, Missouri, and Arkansas, which have lower workforce churn and/or tight labor markets.

Sometimes job-seeking activity is a marker of job satisfaction. According to the team’s data, 42% of employees feel engaged at work, a shockingly low number. 62% feel leaders at work don’t listen to their employees’ feedback. These feelings can lead workers to switch jobs multiple times. In high-activity states, managers should examine their employee retention rates. This data can help HR managers assess their strategies. An active job-seeking region can be an opportunity for businesses and potential employees alike.

States with expanding economies and robust industries experience higher workforce churn, reflecting dynamic labor markets and growth opportunities. Meanwhile, regions with less turnover often maintain tighter labor markets, signaling stability. Overall, these patterns highlight the significance of economic development and industry diversification in shaping labor mobility across the nation.

The post Map Illustrates Variations in Job-Seeking Rates Throughout the U.S. appeared first on Infographics Archive.

Between 2015 and 2019, imports of dumb phones began to rise again. They reached a peak of 18.9 million units (about $3.5 billion in value) imported in 2022. Post-pandemic supply chain corrections might have inflated these numbers, but it’s also clear that demand for dumb phones shifted. Even after 2022’s market spike, dumb phone imports remained above mid-2010s levels. That means a small but persistent segment of the cell phone market is deliberately downgrading to simpler options.

The reasons for this shift are clear. Screen time has been linked to many negative health outcomes: poor sleep, poor eyesight and posture, headaches, eye strain, depression, anxiety, and a host of other problems. Add to this the data security concerns around smartphones, and it’s less surprising that people would prefer a simpler phone option. The average smartphone can track your location, log your biometric data, and sell your information to advertisers and other entities. Not so for the dumb phone, which is stripped down and focused solely on calling and texting. No more late-night doom scrolling. No captures of your face and voice.

The interest in dumb phones seems to be more than a niche revolt. There’s sustained evidence that we can’t assume the smartphone is the only option for connectivity and that more is always more. A dedicated base of consumers wants something simpler, and their numbers just might grow.

The post 17 Years of Import Data Reveals a Tech Reversal in the World of Phones appeared first on Infographics Archive.