The DOI matches its Crossref record; 113 of the 113 references it cites were found in a registry or an index.
Science of science
Open accessAbstract
The whys and wherefores of SciSci: The science of science (SciSci) is based on a transdisciplinary approach that uses large data sets to study the mechanisms underlying the doing of science—from the choice of a research problem to career trajectories and progress within a field. In a Review, Fortunato et al. explain that the underlying rationale is that with a deeper understanding of the precursors of impactful science, it will be possible to develop systems and policies that improve each scientist's ability to succeed and enhance the prospects of science as a whole. Science , this issue p. eaao0185
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“the cumulative nature of scientific research [12] makes the knowledge ecosystem vulnerable to perpetuating errors [13], [14]”
From LLM hallucinations in the wild: Large-scale evidence from non-existent citations (2026) · cites this paper as [12]
In the citing paper
“Specifically, we believe that practices fundamental to the business models of paper mills leave a collaboration fingerprint that can be identified using techniques familiar to the ‘Science of Science’12.”
From Identifying fabricated networks within authorship-for-sale enterprises (2024) · cites this paper as [12]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · cited 1×
“Power-law tails can be generated through a cumulative advantage process (74), known as preferential attachment in network science (75), suggesting that the probability of citing a paper grows with the number of citations that it has already collected.”
An index to quantify an individual’s scientific research output
Hirsch, J. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0507655102 · Cited by 11,669
The file drawer problem and tolerance for null results.
Rosenthal, R. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.3.638 · Cited by 9,068
The Matthew Effect in Science: The reward and communication systems of science are considered.
Merton, R. K. (1968) · Science · doi:10.1126/science.159.3810.56 · Cited by 6,720 · cited 2×
“Together, these datadriven efforts complement contributions from related research domains such as the economics (30) and sociology of science (60, 86).”
(1968) · PubMed · Cited by 4,803
The structure of scientific collaboration networks
Newman, M. E. J. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.2.404 · Cited by 4,550 · cited 1×
“A life-cycle analysis of eight fields (10) shows that successful fields undergo a process of knowledge and social unification that leads to a giant connected component in the collaboration network (104), corresponding to a sizeable group of regular coauthors.”
Price, D. J. D. S. (1963) · Columbia University Press eBooks · doi:10.7312/pric91844 · Cited by 4,400
The Essential Tension: Selected Studies in Scientific Tradition and Change
Kuhn, T. S. (1977) · doi:10.7208/chicago/9780226217239.001.0001 · Cited by 3,861
The Increasing Dominance of Teams in Production of Knowledge
Wuchty, S., Jones, B. F., & Uzzi, B. (2007) · Science · doi:10.1126/science.1136099 · Cited by 3,615 · cited 3×
“1 million patents reveals a nearly universal shift toward teams in all branches of science (50) (Fig.”
Self-citationPrice, D. J. D. S. (1965) · Science · doi:10.1126/science.149.3683.510 · Cited by 3,205
Science faculty’s subtle gender biases favor male students
Moss-Racusin, C. A., Dovidio, J. F., Brescoll, V. L., Graham, M. J., & Handelsman, J. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211286109 · Cited by 3,150
Garfield, E. (1972) · Science · doi:10.1126/science.178.4060.471 · Cited by 2,788
Citation Indexes for Science: A New Dimension in Documentation through Association of Ideas
Garfield, E. (1955) · Science · doi:10.1126/science.122.3159.108 · Cited by 2,334
A general theory of bibliometric and other cumulative advantage processes
Price, D. J. D. S. (1976) · Journal of the American Society for Information Science · doi:10.1002/asi.4630270505 · Cited by 2,013
Quantifying social group evolution
Palla, G., Barabási, A.-Ĺ., & Vicsek, T. (2007) · Nature · doi:10.1038/nature05670 · Cited by 1,681 · cited 1×
“Size is a crucial determinant of team survival strategies: Small teams survive longer if they maintain a stable core, but larger teams persist longer if they manifest a mechanism for membership turnover (56).”
Self-citationAtypical Combinations and Scientific Impact
Uzzi, B., Mukherjee, S., Stringer, M. J., & Jones, B. F. (2013) · Science · doi:10.1126/science.1240474 · Cited by 1,579 · cited 3×
“the context of established knowledge (26).”
InfluentialSelf-citationBibliometrics: Global gender disparities in science
Larivière, V., Ni, C., Gingras, Y., Cronin, B., & Sugimoto, C. R. (2013) · Nature · doi:10.1038/504211a · Cited by 1,499 · cited 1×
“Gender inequality in science remains prevalent and problematic (34).”
The specificity of the scientific field and the social conditions of the progress of reason
Bourdieu, P. (1975) · Social Science Information · doi:10.1177/053901847501400602 · Cited by 1,483
A review of the literature on citation impact indicators
Waltman, L. (2016) · Journal of Informetrics · doi:10.1016/j.joi.2016.02.007 · Cited by 1,356
Self-citationThe essential tension : selected studies in scientific tradition and change
Kühn, T. (1977) · Philosophy of Science · doi:10.7208/9780226217239 · Cited by 1,204
Team Assembly Mechanisms Determine Collaboration Network Structure and Team Performance
Guimerà, R., Uzzi, B., Spiro, J., & Amaral, L. A. N. (2005) · Science · doi:10.1126/science.1106340 · Cited by 1,126 · cited 1×
“Teams are growing in size, increasing by an average of 17% per decade (50, 54, 105), a trend underlying a fundamental change in teamcompositions.”
Self-citationThe Burden of Knowledge and the “Death of the Renaissance Man”: Is Innovation Getting Harder?
JONES, B. F. (2009) · Review of Economic Studies · doi:10.1111/j.1467-937x.2008.00531.x · Cited by 1,058
Human Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018) · The Quarterly Journal of Economics · doi:10.1093/qje/qjx032 · Cited by 1,040
Does the h index have predictive power?
Hirsch, J. E. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0707962104 · Cited by 980 · cited 1×
“It has been suggested that the future h-index (83) of a scientist can be accurately predicted (84), although the predictive power is reduced when”
Stephan, P. E. (2012) · Harvard University Press eBooks · doi:10.4159/harvard.9780674062757 · Cited by 958
Factors Affecting Number of Citations: A Comprehensive Review of the Literature
Tahamtan, I., Safipour Afshar, A., & Ahamdzadeh, K. (2016) · Scientometrics · doi:10.1007/s11192-016-1889-2 · Cited by 912
The Role of Gender in Scholarly Authorship
West, J. D., Jacquet, J., King, M. M., Correll, S. J., & Bergstrom, C. T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066212 · Cited by 897
Self-citationUniversality of citation distributions: Toward an objective measure of scientific impact
Radicchi, F., Fortunato, S., & Castellano, C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0806977105 · Cited by 828
Self-citationWagner, C. S., Roessner, J. D., Bobb, K., Klein, J. T., Boyack, K. W., Keyton, J., Ràfols, I., & Börner, K. (2010) · Journal of Informetrics · doi:10.1016/j.joi.2010.06.004 · Cited by 777
Self-citationQuantifying Long-Term Scientific Impact
Wang, D., Song, C., & Barabási, A.-L. (2013) · Science · doi:10.1126/science.1237825 · Cited by 753
Self-citationWhat is societal impact of research and how can it be assessed? a literature survey
Bornmann, L. (2012) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.22803 · Cited by 732 · cited 1×
“The development of alternative metrics covering web (88) and social media (89) activity and societal impact (90) is critical in this regard.”
Azoulay, P., Zivin, J. S. G., & Wang, J. (2010) · Quarterly Journal of Economics · doi:10.1162/qjec.2010.125.2.549 · Cited by 720
Costas, R., Zahedi, Z., & Wouters, P. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23309 · Cited by 711
Creative productivity: A predictive and explanatory model of career trajectories and landmarks.
Simonton, D. K. (1997) · Psychological Review · doi:10.1037/0033-295x.104.1.66 · Cited by 708 · cited 1×
“Decades of research on outstanding researchers and innovators concluded that major breakthroughs take place relatively early in a career, with a median age of 35 (48).”
Incentives and creativity: evidence from the academic life sciences
Azoulay, P., Zivin, J. G., & Manso, G. (2011) · The RAND Journal of Economics · doi:10.1111/j.1756-2171.2011.00140.x · Cited by 652 · cited 3×
“For example, one study finds that funding schemes that are tolerant of early failure, which reward long-term success, are more likely to generate high-impact publications than grants subject to short review cycles (31).”
Quantifying the evolution of individual scientific impact
Sinatra, R., Wang, D., Deville, P., Song, C., & Barabási, A.-Ĺ. (2016) · Science · doi:10.1126/science.aaf5239 · Cited by 639
Self-citationSystematic inequality and hierarchy in faculty hiring networks
Clauset, A., Arbesman, S., & Larremore, D. B. (2015) · Science Advances · doi:10.1126/sciadv.1400005 · Cited by 624
Interdisciplinary research has consistently lower funding success
Bromham, L. D., Dinnage, R., & Hua, X. (2016) · Nature · doi:10.1038/nature18315 · Cited by 602
van Raan, A. F. J. (2004) · Scientometrics · doi:10.1023/b:scie.0000018543.82441.f1 · Cited by 579 · cited 1×
“Only a tiny fraction of papers deviate from the pattern described by such a model—some of which are called “sleeping beauties,” because they receive very little notice for decades after publication and then suddenly receive a burst of attention and citations (80, 81).”
Tradition and Innovation in Scientists’ Research Strategies
Foster, J., Rzhetsky, A., & Evans, J. A. (2013) · arXiv.org · doi:10.1177/0003122415601618 · Cited by 578
Self-citationHuman Decisions and Machine Predictions
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2017) · doi:10.3386/w23180 · Cited by 545
Boudreau, K. J., Guinan, E. C., Lakhani, K. R., & Riedl, C. (2014) · Management Science · doi:10.1287/mnsc.2015.2285 · Cited by 518
New developments in the use of citation analysis in research evaluation
Moed, H. F. (2009) · Archivum Immunologiae et Therapiae Experimentalis · doi:10.1007/s00005-009-0001-5 · Cited by 507
Team size matters: Collaboration and scientific impact since 1900
Larivière, V., Gingras, Y., Sugimoto, C. R., & Tsou, A. (2015) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23266 · Cited by 484 · cited 1×
“3 times more likely to receive 1000 citations or more than a solo-authored paper, a difference that cannot be explained by self-citations (50, 52).”
Rodenticidal Effect on Pine Mice of Endrin Used as a Ground Spray
Horsfall, F. (1956) · Science · doi:10.1126/science.123.3185.61-a · Cited by 437
Defining and identifying Sleeping Beauties in science
Ke, Q., Ferrara, E., Radicchi, F., & Flammini, A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1424329112 · Cited by 430 · cited 1×
“Only a tiny fraction of papers deviate from the pattern described by such a model—some of which are called “sleeping beauties,” because they receive very little notice for decades after publication and then suddenly receive a burst of attention and citations (80, 81).”
Self-citationKlavans, R., & Boyack, K. W. (2016) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.23734 · Cited by 360 · cited 1×
“By applying network science methods to citation networks, researchers are able to identify communities as defined by subsets of publications that frequently cite one another (6).”
Publishing: Credit where credit is due
Allen, L., Scott, J., Brand, A., Hlava, M. M. K., & Altman, M. (2014) · Nature · doi:10.1038/508312a · Cited by 352 · cited 1×
“Properly allocating individual credit for a collaborative work is difficult because we cannot easily distinguish individual contributions (61).”
Yegros, A., Ràfols, I., & D’Este, P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0135095 · Cited by 345
The Temporal Structure of Scientific Consensus Formation
Shwed, U., & Bearman, P. (2010) · American Sociological Review · doi:10.1177/0003122410388488 · Cited by 339
Reputation and impact in academic careers
Petersen, A. M., Fortunato, S., Pan, R. K., Kaski, K. K., Penner, O., Rungi, A., Riccaboni, M., Stanley, E., & Fabio Pammolli, A. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1323111111 · Cited by 318 · cited 1×
“The reputation of paper authors, measured by the total citations of their previous output, markedly boosts the number of citations collected by that paper in the first years after publication (47).”
Self-citationThe Gender Gap in NIH Grant Applications
Ley, T. J., & Hamilton, B. H. (2008) · Science · doi:10.1126/science.1165878 · Cited by 275
Evans, J. A., & Foster, J. G. (2011) · Science · doi:10.1126/science.1201765 · Cited by 271
Self-citationData-driven predictions in the science of science
Clauset, A. J., Larremore, D. B., & Sinatra, R. (2017) · Science · doi:10.1126/science.aal4217 · Cited by 267
Self-citationPublication bias and the canonization of false facts
Nissen, S. B., Magidson, T., Gross, K., & Bergstrom, C. T. (2016) · eLife · doi:10.7554/elife.21451 · Cited by 266
Self-citationPrinciples of scientific research team formation and evolution
Milojević, S. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1309723111 · Cited by 262
Self-citationChoosing experiments to accelerate collective discovery
Rzhetsky, A., Foster, J. G., Foster, I. T., & Evans, J. A. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1509757112 · Cited by 259
Self-citationDuch, J., Zeng, X. H. T., Sales‐Pardo, M., Radicchi, F., Otis, S., Woodruff, T. K., & Amaral, L. A. N. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051332 · Cited by 254
Self-citationAcuna, D. E., Allesina, S., & Kording, K. P. (2012) · Nature · doi:10.1038/489201a · Cited by 249
Scientists have most impact when they're free to move
Sugimoto, C. R., Robinson‐García, N., Murray, D., Yegros, A., Costas, R., & Larivière, V. (2017) · Nature · doi:10.1038/550029a · Cited by 222 · cited 1×
“Scientists who left their country of origin outperformed scientists who did not relocate, according to their citation scores, which may be rooted in a selection bias that offers better career opportunities to better scientists (43, 44).”
The mover’s advantage: The superior performance of migrant scientists
Franzoni, C., Scellato, G., & Stephan, P. E. (2013) · Economics Letters · doi:10.1016/j.econlet.2013.10.040 · Cited by 222 · cited 1×
“Scientists who left their country of origin outperformed scientists who did not relocate, according to their citation scores, which may be rooted in a selection bias that offers better career opportunities to better scientists (43, 44).”
Long-Distance Interdisciplinarity Leads to Higher Scientific Impact
Larivière, V., Haustein, S., & Börner, K. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122565 · Cited by 210
Self-citationCollective credit allocation in science
Shen, H., & Barabási, A.-Ĺ. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1401992111 · Cited by 193
Self-citationCharacterizing and Modeling Citation Dynamics
Eom, Y.-H., & Fortunato, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024926 · Cited by 192 · cited 1×
“Such a model can be augmented with other characteristic features of citation dynamics, such as the obsolescence of knowledge, decreasing the citation probability with the age of the paper (76–79, 106), and a fitness parameter, unique to each paper, capturing the appeal of the work to the scientific community (77, 78).”
Self-citationPersistence and uncertainty in the academic career
Petersen, A. M., Riccaboni, M., Stanley, H. E., & Pammolli, F. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121429109 · Cited by 188 · cited 3×
“Having more collaborations means greater visibility through a larger number of coauthors, who will likely introduce the work to their networks, an enhanced impact thatmay partially compensate for the fact that credit within a team must be shared with many colleagues (29).”
Self-citationCareer on the Move: Geography, Stratification and Scientific Impact
Deville, P., Wang, D., Sinatra, R., Song, C., Blondel, V. D., & Barabási, A.-Ĺ. (2014) · Scientific Reports · doi:10.1038/srep04770 · Cited by 182 · cited 2×
“This finding, along with the work reported in (46), suggests that, for productive scientific careers, reputation is less of a critical driver for success than talent, hard work, and relevance.”
Self-citationParolo, P. D. B., Pan, R. K., Ghosh, R., Huberman, B. A., Kaski, K. K., & Fortunato, S. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2015.07.006 · Cited by 180
Self-citationEffectiveness of Journal Ranking Schemes as a Tool for Locating Information
Stringer, M. J., Sales‐Pardo, M., & Amaral, L. A. N. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001683 · Cited by 179
Quantifying patterns of research-interest evolution
Jia, T., Wang, D., & Szymanski, B. K. (2017) · Nature Human Behaviour · doi:10.1038/s41562-017-0078 · Cited by 172
Self-citationScientific discovery and topological transitions in collaboration networks
Bettencourt, L. M. A., Kaiser, D. I., & Kaur, J. (2009) · Journal of Informetrics · doi:10.1016/j.joi.2009.03.001 · Cited by 164 · cited 1×
“A life-cycle analysis of eight fields (10) shows that successful fields undergo a process of knowledge and social unification that leads to a giant connected component in the collaboration network (104), corresponding to a sizeable group of regular coauthors.”
Quantifying the impact of weak, strong, and super ties in scientific careers
Petersen, A. M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1501444112 · Cited by 162 · cited 1×
“Publications involving extremely strong collaborators gain 17% more citations on average, pointing to the value of career partnership (59).”
Self-citationWeaving the fabric of science: Dynamic network models of science's unfolding structure
Shi, F., Foster, J. G., & Evans, J. A. (2015) · Social Networks · doi:10.1016/j.socnet.2015.02.006 · Cited by 159 · cited 1×
“Recentwork focusing onbiomedical science has illustrated how the growth of the literature reinforces these communities (9).”
Self-citationDifferences in Collaboration Patterns across Discipline, Career Stage, and Gender
Zeng, X. H. T., Duch, J., Sales‐Pardo, M., Moreira, J. A. G., Radicchi, F., Ribeiro, H. V., Woodruff, T. K., & Amaral, L. A. N. (2016) · PLoS Biology · doi:10.1371/journal.pbio.1002573 · Cited by 157 · cited 2×
“Women have fewer publications (35–37) and collaborators (38) and less funding (39), and they are penalized in hiring decisions when compared with equally qualified men (40).”
Self-citationPeer review of grant applications: what do we know?
Wessely, S. C. (1998) · The Lancet · doi:10.1016/s0140-6736(97)11129-1 · Cited by 146
On the Predictability of Future Impact in Science
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K., & Fortunato, S. (2013) · Scientific Reports · doi:10.1038/srep03052 · Cited by 140
Self-citationFunding Science: The Real Defects of Peer Review and An Alternative To It
Roy, R. (1985) · Science Technology & Human Values · doi:10.1177/016224398501000309 · Cited by 140
The Burden of Knowledge and the 'Death of the Renaissance Man': Is Innovation Getting Harder?Preprint
Jones, B. F. (2004) · SSRN Electronic Journal · doi:10.2139/ssrn.608702 · Cited by 139
Sun, X., Kaur, J., Milojević, S., Flammini, A., & Menczer, F. (2013) · Scientific Reports · doi:10.1038/srep01069 · Cited by 132
Self-citationThe bureaucratization of science
Walsh, J. P., & Lee, Y.-N. (2015) · Research Policy · doi:10.1016/j.respol.2015.04.010 · Cited by 119
Inheritance Patterns in Citation Networks Reveal Scientific Memes
Kuhn, T., Perc, M., & Helbing, D. (2014) · Physical Review X · doi:10.1103/physrevx.4.041036 · Cited by 117
Self-citationGlobal mobility: Science on the move
Noorden, R. V. (2012) · Nature · doi:10.1038/490326a · Cited by 115
Quantifying the cognitive extent of science
Milojević, S. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2015.10.005 · Cited by 111
Self-citationPredicting the long-term citation impact of recent publications
Stegehuis, C., Litvak, N., & Waltman, L. (2015) · Journal of Informetrics · doi:10.1016/j.joi.2015.06.005 · Cited by 109
Self-citationCompetition and Careers in Biosciences
Freeman, R., Weinstein, E., Marincola, E., Rosenbaum, J., & Solomon, F. (2001) · Science · doi:10.1126/science.1067477 · Cited by 105
On the Predictability of Future Impact in Science
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K. K., & Fortunato, S. (2013) · IMT Institutional Repository (IMT School for Advanced Studies Lucca) · Cited by 102
Self-citationGender, Productivity, and Prestige in Computer Science Faculty Hiring Networks
Way, S. F., Larremore, D. B., & Clauset, A. J. (2016) · International World Wide Web Conference (WWW) · doi:10.1145/2872427.2883073 · Cited by 95
Sociological Innovation through Subfield Integration
Leahey, E., & Moody, J. W. (2014) · Social Currents · doi:10.1177/2329496514540131 · Cited by 93
Specific and general information sharing among competing academic researchers
Haeussler, C., Jiang, L., Thursby, J. G., & Thursby, M. (2013) · Research Policy · doi:10.1016/j.respol.2013.08.017 · Cited by 92 · cited 1×
“, data) that scientists share with competitors (91), the help that they offer to their peers (92), and their reliability as reviewers of their peers’ works (93).”
Which Peers Matter? The Relative Impacts of Collaborators, Colleagues, and Competitors
Borjas, G. J., & Doran, K. B. (2014) · The Review of Economics and Statistics · doi:10.1162/rest_a_00472 · Cited by 85
IBM’s Health Analytics and Clinical Decision Support
Sun, J., Knoop, S., Shabo, A., Carmeli, B., Sow, D., Syeda-Mahmood, T. F., Rapp, W., & Kohn, M. S. (2014) · Yearbook of Medical Informatics · doi:10.15265/iy-2014-0002 · Cited by 82
Web indicators for research evaluation. Part 2: Social media metrics
Thelwall, M. A., & Kousha, K. (2015) · El Profesional de la Informacion · doi:10.3145/epi.2015.sep.09 · Cited by 78
Thelwall, M. A., & Kousha, K. (2015) · El Profesional de la Informacion · doi:10.3145/epi.2015.sep.08 · Cited by 78 · cited 1×
“The development of alternative metrics covering web (88) and social media (89) activity and societal impact (90) is critical in this regard.”
Universality of citation distributions revisited
Waltman, L., van Eck, N. J., & van Raan, A. F. J. (2011) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.21671 · Cited by 76
Self-citationThelwall, M. (2016) · Journal of Informetrics · doi:10.1016/j.joi.2015.12.007 · Cited by 74
Thelwall, M. A. (2016) · RePEc: Research Papers in Economics · Cited by 71
Health ROI as a measure of misalignment of biomedical needs and resources
Yao, L., Li, Y., Ghosh, S., Evans, J. A., & Rzhetsky, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3276 · Cited by 59 · cited 1×
“Measurements show that the allocation of biomedical resources in the United States is more strongly correlated to previous allocations and research than to the actual burden of diseases (18), highlighting a systemic misalignment between biomedical needs and resources.”
Self-citationTechnological novelty profile and invention’s future impact
Kim, D., Cerigo, D. B., Jeong, H., & Youn, H. (2016) · EPJ Data Science · doi:10.1140/epjds/s13688-016-0069-1 · Cited by 57
Quantifying the negative impact of brain drain on the integration of European science
Arrieta, O. A. D., Fabio Pammolli, A., & Petersen, A. M. (2017) · Science Advances · doi:10.1126/sciadv.1602232 · Cited by 55
Self-citationStochastic Dynamical Model of a Growing Citation Network Based on a Self-Exciting Point Process
Golosovsky, M., & Solomon, S. (2012) · Physical Review Letters · doi:10.1103/physrevlett.109.098701 · Cited by 54
An efficient system to fund science: from proposal review to peer-to-peer distributions
Bollen, J., Crandall, D., Junk, D., Ding, Y., & Börner, K. (2016) · Scientometrics · doi:10.1007/s11192-016-2110-3 · Cited by 47
Self-citationDetecting Communities through Network Data
Bruggeman, J., Traag, V., & Uitermark, J. (2012) · American Sociological Review · doi:10.1177/0003122412463574 · Cited by 44
Inheritance Patterns in Citation Networks Reveal Scientific MemesPreprint
Kuhn, T., Perc, M., & Helbing, D. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2426903 · Cited by 42
Self-citationBias against Novelty in Science: A Cautionary Tale for Users of Bibliometric Indicators
Wang, J., Veugelers, R., & Stephan, P. E. (2016) · National Bureau of Economic Research · doi:10.3386/w22180 · Cited by 42
Runaway events dominate the heavy tail of citation distributions
Golosovsky, M., & Solomon, S. (2012) · The European Physical Journal Special Topics · doi:10.1140/epjst/e2012-01576-4 · Cited by 38
Characterizing scientific production and consumption in Physics
Zhang, Q., Perra, N., Gonçalves, B., Ciulla, F., & Vespignani, A. (2013) · Scientific Reports · doi:10.1038/srep01640 · Cited by 36
Self-citationTurn the scientific method on ourselves
Azoulay, P. (2012) · Nature · doi:10.1038/484031a · Cited by 34
Characterizing scientific production and consumption in PhysicsPreprint
Zhang, Q., Perra, N., Gonçalves, B., Ciulla, F., & Vespignani, A. (2016) · Cited by 29
Self-citationGetting credit for peer review
(2016) · AAAS Articles DO Group · doi:10.1126/science.caredit.a1600022 · Cited by 24
刘, 斌., Govindan, R., & Uzzi, B. (2016) · PLoS ONE · doi:10.1371/journal.pone.0144945 · Cited by 23
Self-citationOettl, A. (2012) · Nature · doi:10.1038/489496a · Cited by 17
Large Teams Have Developed Science and Technology; Small Teams Have Disrupted ItPreprint
Wu, L., Wang, D., & Evans, J. A. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.3034125 · Cited by 11
Self-citation(2010) · Nature · doi:10.1038/4681002a · Cited by 6
Large Teams Have Developed Science and Technology; Small Teams Have Disrupted ItPreprint
Wu, L., Wang, D., & Evans, J. A. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1709.02445
Self-citation
Flagged first, then by citations
Research works printed but not linked: 3
- N. J. Cooke M. L. Hilton Eds. Enhancing the Effectiveness of Team Science (National Academies Press 2015).
- H. F. Moed Citation Analysis in Research Evaluation (Springer 2010).
- J. R. Cole H. Zuckerman in The Idea of Social Structure: Papers in Honor of Robert K. Merton L. A. Coser Ed. (Harcourt Brace Jovanovich 1975) pp. 139–174.
Cited by
Sorted by citations
The Diversity–Innovation Paradox in Science
Hofstra, B., Kulkarni, V., Galvez, S. M.-N., He, B. D., Jurafsky, D., & McFarland, D. A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1915378117 · Cited by 1,000
Historical comparison of gender inequality in scientific careers across countries and disciplines
Huang, J., Gates, A. J., Sinatra, R., & Barabási, A.-Ĺ. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1914221117 · Cited by 978
Self-citationEmerging Trends in the Social and Behavioral Sciences
Pecher, D., Zeelenberg, R., Scott, R., & Kosslyn, S. M. (2015) · Wiley eBooks · doi:10.1002/9781118900772 · Cited by 1,529
Unequal effects of the COVID-19 pandemic on scientists
Myers, K. R., Tham, W. Y., Yin, Y., Cohodes, N., Thursby, J. G., Thursby, M. C., Schiffer, P., Walsh, J. T., Lakhani, K. R., & Wang, D. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0921-y · Cited by 725
Self-citationBornmann, L., Haunschild, R., & Mutz, R. (2021) · Humanities and Social Sciences Communications · doi:10.1057/s41599-021-00903-w · Cited by 595
Metadata
- Authors
- Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., Vespignani, A., Waltman, L., Wang, D., & Barabási, A.-L.
- Affiliations
- Indiana University Bloomington (US)
- University of Washington (US)
- University of Chicago (US)
- ETH Zurich (CH)
- University of California, Merced (US)
- Northeastern University (US)
- Northwestern University (US)
- Leiden University (NL)
- Center for Network Science, Central European University, Budapest 1052, Hungary.
- Corresponding author
- Fortunato, Santo
- ORCID
- Venue
- Science
- Published
- 2018-03-02
- Volume
- 359
- Issue
- 6379
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC5949209
- OpenAlex
- W2793071066
- Cited by
- 1,497
- References
- 113
- Citations by year
- 2026: 222 · 2025: 223 · 2024: 223 · 2023: 197 · 2022: 164 · 2021: 180 · 2020: 126 · 2019: 113 · 2018: 43
- FWCI
- 22.72
- Type
- journal article
- Language
- en
- Open access
- Licence
- other-oa
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- IUScholarWorks Open (Indiana University) (submittedVersion)
- Funders
- NIH Office of the Director (P01 AG039347, U01CA198934, IIS-0910664)
- NSF Office of the Director (NCSE 1538763, EAGER1566393, NCN CP Supplement 1553044)
- AFOSR (FA9550-15-1-0077, FA9550-15-1-0162, FA9550-17-1-0089)
- European Commission (641191)
- Air Force Office of Scientific Research (FA9550-15-1-0364)
- Army Research Office (W911NF-15-1-0577)
- Topics
- Social Sciences › Library and Information Sciences › scientometrics and bibliometrics research
- Social Sciences › Business, Management and Accounting › Management of Technology and Innovation › Research, Science, and Academia
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychology Research and Bibliometrics
- Keywords
- science of science, research output, science policy, scientific careers, research funding, research frontiers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review