CoChat
Sign Up
Cited by 2,624Mental Health via WritingAuthorship Attribution and ProfilingComputational and Text Analysis Methods

Psychological Aspects of Natural Language Use: Our Words, Our Selves

Pennebaker, James W., Mehl, Matthias R., Niederhoffer, Kate G.·2003·Annual Review of Psychology
DOI 10.1146/annurev.psych.54.101601.145041
Open this paper in CoChat — free account

Abstract

The words people use in their daily lives can reveal important aspects of their social and psychological worlds. With advances in computer technology, text analysis allows researchers to reliably and quickly assess features of what people say as well as subtleties in their linguistic styles. Following a brief review of several text analysis programs, we summarize some of the evidence that links natural word use to personality, social and situational fluctuations, and psychological interventions. Of particular interest are findings that point to the psychological value of studying particles—parts of speech that include pronouns, articles, prepositions, conjunctives, and auxiliary verbs. Particles, which serve as the glue that holds nouns and regular verbs together, can serve as markers of emotional state, social identity, and cognitive styles.

Integrity signals

Registry

Crossref · 10.1146/annurev.psych.54.101601.145041

Cites

137 of 137 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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?

  • From a psycholinguistic perspective, there is a relationship between word usage and personality, social conditions, and consequently emotional states.

    “From a psycholinguistic perspective, there is a relationship between word usage and personality, social conditions, and consequently emotional states [120].”

    From Online grooming detection: A comprehensive survey of child exploitation in chat logs (2023) · cites this paper as [120]

  • Removal of functional words and stopwords may embed useful signals about authorship and/or emotional states, threatening research validity.

    “Even if such words might not be useful for certain analyses, for other applications they may embed useful signals about e.g., authorship and/or emotional states (Pennebaker et al., 2003; Saif et al., 2014), threatening as a result the research validity (Denny and Spirling, 2016).”

    From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Pennebaker et al., 2003

  • Language can reflect affective, cognitive, perceptual, and other psychological processes of individuals, including changes over time around specific events.

    “Language can re fl ect these affective, cognitive, perceptual, and other psychological processes of individuals, including changes over time around speci fi c events (school shooter drills in our case) (Pennebaker et al., 2003).”

    From Impacts of school shooter drills on the psychological well-being of American K-12 school communities: a social media study (2021) · cites this paper as Pennebaker et al., 2003

  • The increase in 'we' is a proxy for social integration, suggesting the increasing importance of friendships and relationships as people age.

    “We take this as a proxy for social integration [19], suggesting the increasing importance of friendships and relationships as people age.”

    From Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013) · cites this paper as [19]

  • It remains unclear to what extent the results of constrained studies generalize to less constrained real-world situations.

    “It remains unclear to what extent the results of such studies generalize to less constrained real-world situations where people's personalities can influence not only how they write or talk about specific topics, but also what topics they choose to write or talk about (cf. Pennebaker, Mehl, & Niederhoffer, 2003).”

    From Personality in 100,000 Words: A large-scale analysis of personality and word use among bloggers (2010) · cites this paper as Pennebaker, Mehl, & Niederhoffer, 2003

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G.
Affiliations
The University of Texas at Austin (US)
ORCID
Venue
Annual Review of Psychology
Publisher
Annual Reviews
Published
2003-02
Volume
54
Issue
1
Pages
547-577
ISSN
  • 0066-4308 (ISSN-L)
  • 1545-2085
DOI
10.1146/annurev.psych.54.101601.145041
OpenAlex
W2100772444
Cited by
2,624
References
137
Citations by year
2026: 158 · 2025: 149 · 2024: 167 · 2023: 174 · 2022: 166 · 2021: 159 · 2020: 165 · 2019: 163 · 2018: 157 · 2017: 139 · 2016: 151 · 2015: 129 · 2014: 136 · 2013: 97 · 2012: 116
FWCI
3.94
Type
journal article
Language
en
Open access
closed
Locations
  • Annual Review of Psychology (publishedVersion)
  • PubMed (publishedVersion)
  • CLOK (University of Central Lancashire) (submittedVersion)
Funders
National Institute of Mental Health (R01MH052391, MH52391)
Topics
  • Social Sciences › Psychology › Social Psychology › Mental Health via Writing
  • Physical Sciences › Computer Science › Artificial Intelligence › Authorship Attribution and Profiling
  • Social Sciences › General Social Sciences › Computational and Text Analysis Methods
Keywords
natural language use, text analysis, personality, language style, particles, parts of speech, pronouns, prepositions, auxiliary verbs, emotional state, social identity, cognitive style, psychological intervention, self-representation
MeSH terms
Artificial Intelligence, Emotions, Health Status, Humans, Individuality, Interpersonal Relations, Mental Health, Natural Language Processing, Personality, Psycholinguistics, Semantics, Social Environment, Verbal Behavior

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