Evidence map›Paper›PMID 34194043›Full record

ArticleNature2021

Meaningful measures of human society in the twenty-first century.

David Lazer, Eszter Hargittai, Deen Freelon, Sandra Gonzalez-Bailon, Kevin Munger, Katherine Ognyanova, Jason Radford

Abstract readHistorical Article
PubMed Publisher
In one paragraph

Article in Nature, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
  2. Article
  3. Scientific standards suffer from misrepresenting past work.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  4. Review
  5. Article
  6. New strategies for the cognitive science of dreaming.Trends in cognitive sciences · 2024
    Review
  7. Article
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Mental health culturomics.PLOS mental health · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Urban resilience to socioeconomic disruptions during the COVID-19 pandemic: Evidence from China.International journal of disaster risk reduction : IJDRR · 2023
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

David LazerNetwork Science Institute, Northeastern University, Boston, MA, USA. d.lazer@northeastern.edu.
Eszter HargittaiDepartment of Communication and Media Research, University of Zurich, Zurich, Switzerland.ORCID http://orcid.org/0000-0003-4199-4868
Deen FreelonHussman School of Journalism and Media, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.ORCID http://orcid.org/0000-0001-5055-0316
Sandra Gonzalez-BailonAnnenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA.ORCID http://orcid.org/0000-0002-8372-798X
Kevin MungerDepartment of Political Science, Pennsylvania State University, State College, PA, USA.
Katherine OgnyanovaSchool of Communication and Information, Rutgers University, New Brunswick, NJ, USA.ORCID http://orcid.org/0000-0003-3038-7077
Jason RadfordNetwork Science Institute, Northeastern University, Boston, MA, USA.ORCID http://orcid.org/0000-0003-3045-5527

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Science rarely proceeds beyond what scientists can observe and measure, and sometimes what can be observed proceeds far ahead of scientific understanding. The twenty-first century offers such a moment in the study of human societies. A vastly larger share of behaviours is observed today than would have been imaginable at the close of the twentieth century. Our interpersonal communication, our movements and many of our everyday actions, are all potentially accessible for scientific research; sometimes through purposive instrumentation for scientific objectives (for example, satellite imagery), but far more often these objectives are, literally, an afterthought (for example, Twitter data streams). Here we evaluate the potential of this massive instrumentation-the creation of techniques for the structured representation and quantification-of human behaviour through the lens of scientific measurement and its principles. In particular, we focus on the question of how we extract scientific meaning from data that often were not created for such purposes. These data present conceptual, computational and ethical challenges that require a rejuvenation of our scientific theories to keep up with the rapidly changing social realities and our capacities to capture them. We require, in other words, new approaches to manage, use and analyse data.

Indexed as

Social ChangeDatasets as TopicHistory, 21st CenturyHumansSocial ConditionsSocial Sciences

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.