Evidence map›Paper›PMID 39438680›Full record

ReviewNature human behaviour2024

How developments in natural language processing help us in understanding human behaviour.

Rada Mihalcea, Laura Biester, Ryan L Boyd, Zhijing Jin, Veronica Perez-Rosas, Steven Wilson, James W Pennebaker

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature human behaviour, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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.

Rada MihalceaUniversity of Michigan, Ann Arbor, MI, USA. mihalcea@umich.edu.ORCID http://orcid.org/0000-0002-0767-6703
Laura BiesterMiddlebury College, Middlebury, VT, USA.ORCID http://orcid.org/0000-0003-3901-2968
Ryan L BoydUniversity of Texas at Dallas, Richardson, TX, USA.
Zhijing JinMax Planck Institute for Intelligence Systems, Tübingen, BW, Germany.ORCID http://orcid.org/0000-0003-0238-9024
Veronica Perez-RosasUniversity of Michigan, Ann Arbor, MI, USA.
Steven WilsonOakland University, Rochester, MI, USA.ORCID http://orcid.org/0000-0002-2458-0439
James W PennebakerUniversity of Texas at Austin, Austin, TX, USA.ORCID http://orcid.org/0000-0001-9091-214X

Funding

National Science Foundation (NSF) 2306372Robert Wood Johnson Foundation (RWJF) 80345
6 · The paper itself

Abstract

The ways people use language can reveal clues to their emotions, social behaviours, thinking styles, cultures and the worlds around them. In the past two decades, research at the intersection of social psychology and computer science has been developing tools to analyse natural language from written or spoken text to better understand social processes and behaviour. The goal of this Review is to provide a brief overview of the methods and data currently being used and to discuss the underlying meaning of what language analyses can reveal in comparison with more traditional methodologies such as surveys or hand-scored language samples.

Indexed as

Natural Language ProcessingHumansLanguageSocial Behavior

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.