Evidence map›Paper›PMID 38715729›Full record

ArticlePNAS nexus2024

The topography of thought.

Jonah Berger, Olivier Toubia

Abstract read
In one paragraph

Article in PNAS nexus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Jonah BergerWharton School, University of Pennsylvania, Philadelphia, PA 19104, USA.ORCID https://orcid.org/0000-0002-2669-8211
Olivier ToubiaColumbia Business School, Columbia University, New York, NY 10027, USA.ORCID https://orcid.org/0000-0001-7493-9641

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Whether speaking, writing, or thinking, almost everything humans do involves language. But can the semantic structure behind how people express their ideas shed light on their future success? Natural language processing of over 40,000 college application essays finds that students whose writing covers more semantic ground, while moving more slowly (i.e. moving between more semantically similar ideas), end up doing better academically (i.e. have a higher college grade point average). These relationships hold controlling for dozens of other factors (e.g. SAT score, parents' education, and essay content), suggesting that essay topography encodes information that goes beyond family background. Overall, this work sheds light on how language reflects thought, demonstrates that how people express themselves can provide insight into their future success, and provides a systematic, scalable, and objective method for quantifying the topography of thought.

Indexed as

academic successautomated textual analysislanguagenatural language processingthought

Identifiers

PMID38715729
PMCPMC11075530

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.