Science

What your Wikipedia browsing style says about you

What your Wikipedia browsing style says about you
Hyperlink network from English Wikipedia, with only 0.1% of articles (nodes) and their connections (edges) visualized. Seven different reader journeys are highlighted in various colors. The network is organized by topic and displayed using a layout that groups related articles together
Hyperlink network from English Wikipedia, with only 0.1% of articles (nodes) and their connections (edges) visualized. Seven different reader journeys are highlighted in various colors. The network is organized by topic and displayed using a layout that groups related articles together
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Hyperlink network from English Wikipedia, with only 0.1% of articles (nodes) and their connections (edges) visualized. Seven different reader journeys are highlighted in various colors. The network is organized by topic and displayed using a layout that groups related articles together
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Hyperlink network from English Wikipedia, with only 0.1% of articles (nodes) and their connections (edges) visualized. Seven different reader journeys are highlighted in various colors. The network is organized by topic and displayed using a layout that groups related articles together
In the 2020 study, the hunter was characterized by high clustering (related topics) and low overall path length, while the busybody showed a tendency for low clustering and high overall path length
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In the 2020 study, the hunter was characterized by high clustering (related topics) and low overall path length, while the busybody showed a tendency for low clustering and high overall path length

The 'down the rabbit hole' online-search behaviors of nearly 500,000 people from 50 countries has shed new light on how mood, education level, gender, background and culture influence how we sate our curiosity and seek out new knowledge. So we ask: Are you a hunter, busybody or a newly identified 'dancer'?

While many of us have lost hours chasing links on Wikipedia – some following a more or less linear line of questioning, others jumping wildly from topic to topic, others having a mix of both – a collaborative team of scientists has found that patterns in our browsing have a personal fingerprint.

A formative 2020 study, in which University of Pennsylvania (Penn) researchers assessed 15-minute Wikipedia browsing habits of 149 participants over three weeks, revealed there were two types of information-seekers, the busybody and the hunter.

In the 2020 study, the hunter was characterized by high clustering (related topics) and low overall path length, while the busybody showed a tendency for low clustering and high overall path length
In the 2020 study, the hunter was characterized by high clustering (related topics) and low overall path length, while the busybody showed a tendency for low clustering and high overall path length

In this new study, which massively expands on that earlier work and analyzes 482,760 people from 50 countries using Wikipedia on their smartphone, scientists have confirmed that across the globe these two types dominate, as well as a new category – the 'dancer'.

“The busybody loves any and all kinds of newness, they’re happy to jump from here to there, with seemingly no rhyme or reason, and this is contrasted by the ‘hunter,’ which is a more goal-oriented, focused person who seeks to solve a problem, find a missing factor, or fill out a model of the world,” said Dani Bassett from Penn.

As Bassett and colleagues note in the research: "The busybody scouts for loose threads of novelty, the hunter pursues specific answers in a projectile path, and the dancer leaps in creative breaks with tradition across typically siloed areas of knowledge. These three architectural styles underscore a dimensional approach to the study of curiosity, foregrounding the practice of curiosity as an individual difference."

So what does this tell us besides the fact that some of our rabbit holes resemble complex expansive 'tunnels' of inquiry that have more side quests than an open-world video game? Through systematic analysis, researchers found massive contrasts in browsing patterns between countries with higher overall education and gender equality, compared to regions with more society inequity. And this may help better design tools for learning in different parts of the world that are best suited to how varying populations engage in knowledge gathering.

“We observed that in countries with greater inequality, particularly around gender and access to education, people tended to browse with more focused intent," said first author Dale Zhou. "In contrast, in countries with more equality browsing was more expansive and covered a wider diversity or topics.

“While the exact reasons for why this is occurring are not fully clear, we have some strong hunches, and we believe these findings will prove useful in helping scientists in our field better understand the nature of curiosity across different cultures and locations globally.”

The countries or territories assessed were Algeria, Argentina, Australia, Austria, Bangladesh, Belgium, Brazil, Canada, Chile, Colombia, Czechia, Denmark, Finland, France, Germany, Ghana, Greece, Hong Kong, Hungary, India, Indonesia, Ireland, Israel, Italy, Japan, Kenya, Korea, Malaysia, Mexico, Morocco, Nepal, the Netherlands, New Zealand, Nigeria, Norway, Peru, the Philippines, Poland, Portugal, Romania, Serbia, South Africa, Spain, Sri Lanka, Sweden, Switzerland, Taiwan, Ukraine, the UK and the US.

Across this vast field, the Wikipedia phone app was read in 14 different languages.

To reduce bias, the 482,760 participants – the "naturalistic dataset" – were selected from a larger pool of more than two million Wikipedia users, as their browsing could be best related to the 2020 study's observational findings. The researchers identified the naturalistic dataset by considering: "The number of articles visited, the number of unique articles visited, the number of days of usage in one month, and the fraction of articles reached via Wikipedia hyperlinks (versus from an external website)."

Unlike the controlled study conducted at Penn, the naturalistic dataset participants had no prior knowledge of assessment, so habits differed – generally, the 482,760 people read fewer articles, clicked on fewer unique pages and went to fewer Wikipedia internal links on fewer days. Through a statistical method known as propensity score matching, the researchers were able to align the participants of the 2020 study ('treated' subjects) with the observational data ('untreated' subjects).

What they were able to form was a knowledge network that has been illustrated like a neural network, showing the difference in narrow and loose subject linkages that represent the hunter and the busybody. As well as country-wide browsing falling into these hunter and busybody categories, the investigation also confirmed the existence of the 'dancer' type – something that was thought to exist but not extrapolated on in the earlier work.

“The dancer is someone who moves along a track of information but, unlike the busybody, they make leaps between ideas in a creative, choreographed way,” said study co-author Perry Zurn, a professor of philosophy at American University. “They don’t jump randomly; they connect different domains to create something new.”

This style of browsing is distinct from the hunter and the busybody, as the dancer weaves a path through new information across broad subjects that have some tangible link.

“It’s less about randomness and more about seeing connections where others might not,” Bassett said.

The study identified specific areas of interests across languages and countries. Busybodies tended to read more articles about culture topics including the media, food, art, philosophy and religion. Hunters were more inclined to read pages that covered science, technology, engineering and mathematics (STEM).

"Hunters tended to read articles about history and society in some languages (German and English), whereas busybodies tended to do so in other languages (Arabic, Bengali, Hindi, Dutch, and Chinese)," the researchers noted. "These tendencies are consistent with the hypothesis that busybodies gravitate more toward social topics than do hunters."

Looking at browsing habits, in the context of population-wide indicators of education, mood, well-being and gender equality, the researchers emerged with three hypotheses for why busybodies and hunters dominated in different regions.

“One is that it’s possible that countries that have more inequality also have more patriarchal structures of oppression that are constraining the knowledge production approaches to be more hunter-like,” says Bassett. “Countries that have greater equality, in contrast, are open to a diversity of ideas, and therefore a diversity of ways that we’re engaging in the world. This is more like the busybody – the one that’s moving between ideas in a very open-minded way.”

A second reason, they suggest, is that knowledge-seekers use Wikipedia for different purposes in different countries. For instance, users in wealthy nations may be accessing the site for entertainment or leisure rather than for work. And finally, the distinct differences might be due to disparities in national age, gender, socioeconomic status and education.

Overall, the team highlighted how an individual's curiosity and knowledge seeking is dependent on many broader factors, and shows how little we know about what influences browsing habits.

“What this tells us is that people – and likely children – have different curiosity styles, and that might affect how they approach learning,” Bassett said. “A child with a hunter-like curiosity may struggle if assessed using methods that favor the busybody style, or vice versa. Understanding these styles could help us tailor educational experiences to better support individual learning paths.

“One question I’m particularly interested in is whether people browse differently at different times of day – perhaps they’re more hunter-like in the morning and more like busybodies in the evening,” says Bassett.

Not surprisingly, this comprehensive study now opens the door to a host of specific population studies – and, of course, how artificial intelligence systems learn.

“This opens up new research avenues, including the role of biological processes in shaping how we seek information,” said Shubhankar Patankar, a doctoral student in Penn Engineering. “Imparting notions of curiosity to AI systems learning from interactions is an increasingly important area of research,” Patankar says.

Incidentally, the ad-free Wikipedia is at the center of both studies as it's considered a reliable model to investigate how we satisfy our curiosity online.

“Wikipedia is a very special place on the internet,” said Annenberg School for Communication assistant professor David Lydon-Staley, an author of this study and who also led the 2020 foundational research. “The site features exclusively free content and no commercial advertisements. Much of the rest of the contemporary digital landscape is designed to activate individuals’ buying impulses and customizes our media content. This raises the question of how much we are in charge of where our curiosity takes us in online contexts beyond Wikipedia.”

The the research was published in the journal Science Advances.

Source: University of Pennsylvania

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