Hedgehogs, Foxes, and Global Science Ecosystems: Decoding Universities’ Research Profiles across Fields with Nested Ecological Networks.

Gomez, Charles J., Dahlia Lieberman, and Elina Mäkinen. 2024. Hedgehogs, Foxes, and Global Science Ecosystems: Decoding Universities Research Profiles across Fields with Nested Ecological Networks. Research Policy. [Impact Factor 2022: 7.2]

Modern scientific research evokes ecological imagery and metaphors, given that it is global, interdependent, and diverse. Ecological network structures—like matrices of species inhabiting islands across an archipelago—can be reordered to form nested patterns. These patterns describe the overall health of ecosystems, place species on a spectrum between being described as generalists (foxes) or specialists (hedgehogs), and which of these interactions might appear or disappear. Using the number of citations universities receive for work published in a particular subfield taken from over 66 million scientific publications in OpenAlex, we construct and analyze yearly nested ecological networks of a dozen academic fields between 1990 and 2017. We find increasingly nested structures across fields infer future acknowledgment in different subfields. We argue that this framework can inform policy on scientific research and university funding and evaluation.

Leading Countries in Global Science Increasingly Receive More Citations than Other Countries Despite Doing Similar Research.

Gomez, Charles J., Andrew C. Herman, and Paolo Parigi. 2022. Leading Countries in Global Science Increasingly Receive More Citations than Other Countries Despite Doing Similar Research. Nature Human Behaviour. [Impact Factor 2021: 13.66]

Citations and text analysis are both used to study the distribution and flow of ideas between researchers, fields, and countries, but the resulting flows are rarely equal. We argue that the differences in these two flows capture a growing global inequality in the production of scientific knowledge. We offer a framework called ‘citational lensing’ to identify where citations should appear between countries but are absent given that what is embedded in their published abstract texts is highly similar.

This framework also identifies where citations are overabundant given lower similarity. Our data come from nearly 20 million papers across nearly 35 years and 150 fields from the Microsoft Academic Graph. We find that scientific communities increasingly centre research from highly active countries while overlooking work from peripheral countries. This inequality is likely to pose substantial challenges to the growth of novel ideas.

Moving More, but Closer: Mapping the Growing Regionalization of Global Scientific Mobility Using ORCID.

Gomez, Charles J., Andrew C. Herman, and Paolo Parigi. 2020. Moving More, but Closer: Mapping the Growing Regionalization of Global Scientific Mobility Using ORCID. Journal of Informetrics. [Impact Factor 2018: 3.879]

This article investigates the taken-for-granted notion of scientific mobility as fundamentally “global.” We use self- reported biographical profile data of over a hundred thousand scientists from ORCID (Open Researcher and Contributor ID) who received a Ph.D. between the 1980s and 2010s. These data are advantageous over data commonly used to trace scientific mobility like surveys and disambiguated bibliometric data, as ORCID data offer both publication histories and a curriculum vitae itemization of scientists’ education and employment. We find that scientists who do move internationally in their careers increasingly move within the same transnational region. Furthermore, while we find that mobility between countries has remained stagnant since the 1980s as compared to mobility within countries, scientists who move internationally do so more frequently but for shorter distances. European and Asian Ph.D. holders comprise the majority of scientists who are driving these trends.

Clustering Knowledge and Dispersing Abilities Enhance Collective Problem Solving in a Network.

Gomez, Charles J. and David Lazer. 2019. Clustering Knowledge and Dispersing Abilities Enhance Collective Problem Solving in a Network. Nature Communications. [Impact Factor 2018: 12.03]

Diversity tends to generate more and better ideas in social settings, ranging in scale from small-deliberative groups to tech-clusters and cities. Implicit in this research is that there are knowledge-generating benefits from diversity that comes from mixing different individuals, ideas, and perspectives. Here, we utilize agent-based modeling to examine the emergent outcomes resulting from the manipulation of how diversity is distributed and how knowledge is generated within communicative social structures. In the context of problem solving, we focus on cognitive diversity and its two forms: ability and knowledge. For diversity of ability, we find that local diversity (intermixing of different agents) performs best at all time scales. However, for diversity of knowledge, we find that local homogeneity performs best in the long-run, because it maintains global diversity, and thus the knowledge-generating ability of the group, for a longer period.

Identity Override: How Sexual Orientation Reduces the Rigidity of Racial Boundaries.

Horowitz, Adam and Charles J. Gomez. 2018. Identity Override: How Sexual Orientation Reduces the Rigidity of Racial Boundaries. Sociological Science. [Impact Factor 2018: 2.18]

Although most Americans have limited interpersonal relations with different-race others, interracial ties are notably more common among gay, lesbian, and bisexual (GLB) individuals. Departing from the modal explanation of intergroup relations theories, which suggests that individual propensities for between-group interactions are driven by demographic groups’ physical location relative to one another, we show that, beyond propinquity, GLB interraciality is spiked through active identification as GLB. We evaluate full romantic/sexual partnership histories along with friendship network racial compositions for respondents in a large, nationally representative sample. We show that GLBs have a greater likelihood and frequency than heterosexuals of forming multiple types of interracial ties and also that this effect applies only to those who actively identify as GLB and not to those who engage in same-sex relations but do not identify as GLB. This discovery refines theories of intergroup relations, isolating how identification serves as a mediating mechanism that can heighten the propensity for intergroup interaction. We argue that active identification with a group that crosses racial boundaries spurs overriding the rigidity of intergroup borders that otherwise dissuade interpersonal diversity.

Identifying Diffusion Patterns of Research on Social Media.

Alperin, Juan, Charles J. Gomez, and Stephanie Haustein. 2018. Identifying Diffusion Patterns of Research on Social Media. Public Understanding of Science. [Impact Factor 2018: 2.754]

The growing presence of research shared on social media, coupled with the increase in freely available research, invites us to ask whether scientific articles shared on platforms like Twitter diffuse beyond the academic community. We explore a new method for answering this question by identifying 11 articles from two open access biology journals that were shared on Twitter at least 50 times and by analyzing the follower network of users who tweeted each article. We find that diffusion patterns of scientific articles can take very different forms, even when the number of times they are tweeted is similar. Our small case study suggests that most articles are shared within single-connected communities with limited diffusion to the public. The proposed approach and indicators can serve those interested in the public understanding of science, science communication, or research evaluation to identify when research diffuses beyond insular communities.

Using Text to Measure Paradigmaticness.

Evans, Eliza, Charles J. Gomez, and Dan McFarland. 2016. Using Text to Measure Paradigmaticness. Sociological Science. [Impact Factor 2018: 2.18]

In this paper, we describe new methods that use the text of publications to measure the paradigmaticness of disciplines. Drawing on the text of published articles in the Web of Science, we build samples of disciplinary discourse. Using these language samples, we measure the two core concepts of paradigmaticness—consensus and rapid discovery (Collins 1994)—and show the relative positioning of eight example disciplines on each of these measures. Our measures show consistent differences between the “hard” sciences and “soft” social sciences. Deviations in the expected ranking of disciplines within the sciences and social sciences suggest new interpretations of the hierarchy of disciplines, directions for future research, and further insight into the developments in disciplinary structure and discourse that shape paradigmaticness.

Regionalization of Intergovernmental Organization Networks: A Non-Linear Process.

Gomez, Charles J. and Paolo Parigi. 2015. Regionalization of Intergovernmental Organization Networks: A Non-Linear Process. Social Networks. [Impact Factor 2018: 2.949]

We use a computationally intensive approach to explore how the world polity is becoming more fractured along regional lines. We discover that regionalization is a non-linear process and show that the world polity oscillates between fracturing and re-contracting. We do so by applying the technique of Hierarchical Link Clustering (HLC) to yearly intergovernmental organization (IGO) networks from 1971 to 2005. The mechanism for explaining this seemingly contradictory result lies in the behavior of IGOs, which depends largely on the organizations’ geographic focus: regionally focused IGOs create more communities, thereby fracturing the world polity, while globally focused IGOs create relationships across communities, thereby bringing communities together. Every year, different percentages of global and regional IGOs enter the network, thereby producing oscillations in the overall structure.

The Instructor’s Face in Video Instruction: Evidence from Two Large-Scale Field Studies.

Kizilcec, Rene F., Jeremy Bailenson, and Charles J. Gomez. 2015. The Instructor’s Face in Video Instruction: Evidence from Two Large-Scale Field Studies. Journal of Educational Psychology. [Impact Factor 2018: 4.433]

Multimedia learning research has established several principles for the effective design of audiovisual instruction. The image principle suggests that showing the instructor’s face in multimedia instruction does not promote learning, because the potential benefits from inducing social responses are outweighed by the cost of additional cognitive processing. In an 8-week observational field study (N = 2,951), online learners chose to watch video lectures either with or without the instructor’s face. Although learners who saw the face reported having a better lecture experience than those who chose not to see the face, 35% watched videos without the face for self-reported reasons including avoiding distraction. Building on these insights, the authors developed a video presentation style that strategically shows the face to reduce distraction while preserving occasional social cues. A 10-week field experiment (N = 12,468) compared the constant with the strategic presentation of the face and provided evidence consistent with the image principle. Cognitive load and perceived social presence were higher in the strategic than in the constant condition, but learning outcomes and attrition did not differ. Learners who expressed a verbal learning preference experienced substantially lower attrition and cognitive load with the constant than the strategic presentation. The findings highlight the value of social cues for motivation and caution against onesize- fits-all approaches to instructional design that fail to account for individual differences in multimedia instruction.

The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems.

Bustos, Sebastian, Charles J. Gomez, Ricardo Hausmann, and Cesar Hidalgo. 2011. The Dynamics of Nestedness Predicts the Evolution of Industrial Ecosystems. PLoS ONE. [Impact Factor 2018: 2.777]

In economic systems, the mix of products that countries make or export has been shown to be a strong leading indicator of economic growth. Hence, methods to characterize and predict the structure of the network connecting countries to the products that they export are relevant for understanding the dynamics of economic development. Here we study the presence and absence of industries in international and domestic economies and show that these networks are significantly nested. This means that the less filled rows and columns of these networks’ adjacency matrices tend to be subsets of the fuller rows and columns. Moreover, we show that their nestedness remains constant over time and that it is sustained by both, a bias for industries that deviate from the networks’ nestedness to disappear, and a bias for the industries that are missing according to nestedness to appear. This makes the appearance and disappearance of individual industries in each location predictable. We interpret the high level of nestedness observed in these networks in the context of the neutral model of development introduced by Hidalgo and Hausmann (2009). We show that the model can reproduce the high level of nestedness observed in these networks only when we assume a high level of heterogeneity in the distribution of capabilities available in countries and required by products. In the context of the neutral model, this implies that the high level of nestedness observed in these economic networks emerges as a combination of both, the complementarity of inputs and heterogeneity in the number of capabilities available in countries and required by products. The stability of nestedness in industrial ecosystems, and the predictability implied by it, demonstrates the importance of the study of network properties in the evolution of economic networks.