Suppose there are two papers of the same quality, one written by a Nobel laureate and the other by an unknown graduate student. Which one would be read and cited more? Most people would open the first paper first. This phenomenon, in which attention and recognition flock to people who are already famous and that attention returns as even greater fame, is the ‘Matthew Effect.’
Put simply, the Matthew effect means ‘the phenomenon in which a person or work that starts slightly ahead gains more opportunities and recognition thanks to that lead, so the gap widens as time goes on.’ In library and information science, it is treated as an important concept for explaining why paper citations, academic evaluation and the use of materials become skewed to one side.
In this piece, we will look in turn at where the name Matthew effect comes from, the principle by which citations attract more citations, cases from the world of scholarly information, and ways to reduce the imbalance.
The World of Scholarly Information Through the Lens of ‘the Rich Get Richer’
What Is the Matthew Effect?
The name comes from Matthew 25:29 in the New Testament: “For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken away even that which he hath.” In 1968, the American sociologist Robert K. Merton borrowed this verse in his paper “The Matthew Effect in Science,” published in the journal Science, to explain inequality in the community of scientists. Merton built on the research of Harriet Zuckerman, who had interviewed Nobel laureates, and he later stated himself that Zuckerman deserved much of the credit for the concept.
(1) Recognition That Depends on Fame
What Merton noticed was that even for similar achievements, scientists who were already famous received more credit. Even in research done by several people together, prizes and praise tend to go to the best-known senior researcher.
(2) An Imbalance That Even Reshapes the Communication System
The Matthew effect does not stop at individual reputation. Papers by famous scholars are read more and spread faster, while papers of the same quality written by unknown scholars draw less notice. As a result, research funding, talent and research facilities also gather in places that are already ahead. In 1986, the psychologist Keith Stanovich also applied this name to the phenomenon in which children who learn to read early read more and widen the gap with their peers.
Cumulative Advantage: Citations Attract More Citations
The place where the Matthew effect shows up most clearly in numbers is paper citations. In 1976, the historian of science Derek J. de Solla Price explained with a mathematical model the process by which papers that have already been cited many times become more likely to gain new citations.
- Cumulative advantage (Cumulative Advantage): A feedback structure in which a small early success leads to resources such as research funding, excellent graduate students and good equipment, and those resources in turn produce greater success.
- Preferential attachment (Preferential Attachment): In 1999, the physicists Albert-László Barabási and Réka Albert used this name for the phenomenon in which web pages that have already received many links also receive more new links. It applies the same principle as Price’s cumulative advantage to networks.
- Power-law distribution (Power Law Distribution): As this process builds up, a long-tailed distribution appears in which a small number of papers and scholars take up most of the citations. Price believed that Lotka’s law and Bradford’s law could also be explained by this principle.
Search tools can also amplify the imbalance. On scholarly search screens that factor citation counts into rankings or sorting, papers that appear near the top are read and cited more often, which in turn locks in their ranking.
The Matthew Effect in the World of Scholarly Information
The Matthew effect is actually observed in many corners of the research world.
[Case 1] Research Funding Decided by a Hair’s Breadth
A study published in 2018 in the Proceedings of the National Academy of Sciences (PNAS) analyzed data from a Dutch grant program for young researchers. Even though their review scores were almost the same, researchers who barely cleared the selection threshold collected more than twice as much research funding over the next eight years as those who narrowly missed it. In other words, a single early selection created the gap more than any difference in ability.
[Case 2] Discoveries That Change Names and Hidden Contributions
In 1980, the statistician Stephen Stigler put forward Stigler’s law of eponymy, which states that ‘no scientific discovery is named after its original discoverer,’ and noted that the person who first voiced this idea was Merton, making the law an example of itself. In 1993, the historian of science Margaret W. Rossiter named the phenomenon in which women scientists’ contributions are credited to their male colleagues the ‘Matilda Effect,’ after the 19th-century women’s rights activist Matilda Joslyn Gage.
Information Services’ Efforts to Reduce the Imbalance
The Matthew effect cannot be eliminated completely, but the people and institutions that handle information can weaken its pull.
(1) Mechanisms That Look at Content Before Names
Many journals use double-blind peer review (Double-Blind Peer Review), in which reviewers and authors do not know each other’s identities, to reduce the room for fame to influence evaluation.
(2) Curation That Shines a Light on Hidden Materials
If a library puts only its most-borrowed rankings front and center, a cycle forms in which books that are borrowed a lot get borrowed even more. Librarians introducing good but lesser-known materials through subject-based recommendation lists and featured displays is a good way to loosen this loop.
(3) Open Access and Careful Citation
Open access (Open Access) widens the opportunity to share research broadly even for researchers who do not belong to well-known institutions. However, some point out that open science practices can work more in favor of those who already have plenty of resources, so careful design is needed. Researchers themselves also need to build the habit of finding and citing the original paper that first proposed an idea rather than a well-known commentary.
The Matthew effect shows how, even when abilities are similar, a small difference at the starting point grows into a large gap over time. Citation counts, borrowing rankings and search rankings are convenient guides, but those numbers carry not only ability but also the weight of attention that piled up first.
Taking a second look at the materials and people hidden behind the numbers: that is the first step toward a fair knowledge ecosystem.
