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Gender Differences in Language Use: An Analysis of 14,000 Text Samples
Abstract
Differences in the ways that men and women use language have long been of interest in the study of discourse. Despite extensive theorizing, actual empirical investigations have yet to converge on a coherent picture of gender differences in language. A significant reason is the lack of agreement over the best way to analyze language. In this research, gender differences in language use were examined using standardized categories to analyze a database of over 14,000 text files from 70 separate studies. Women used more words related to psychological and social processes. Men referred more to object properties and impersonal topics. Although these effects were largely consistent across different contexts, the pattern of variation suggests that gender differences are larger on tasks that place fewer constraints on language use.
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“For example, multiple studies report that emoticons (i.e. ‘:)’ ‘:-(‘) are used more often by females [34], [36], [38], but Huffaker & Calvert found males use them more in a sample of 100 teenage bloggers [39].”
From Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013) · cites this paper as [34]
In the citing paper
“Males used more swear words, object references (e.g., ‘xbox’ and swear words) [34], [89].”
From Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013) · cites this paper as [34]
In the citing paper
“they mention more psychological and social processes [34] (e.g., ‘love you’ and ‘3’ –a heart)”
From Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013) · cites this paper as [34]
In the citing paper
“Males used more swear words, object references (e.g., ‘xbox’ and swear words) [34], [89].”
From Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach (2013) · cites this paper as [34]
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“…1 = present, α = .76, Piersoul & Van de Velde, 2023), references to psychological processes (e.g., “I adore…”; 0 = absent, 1 = present, α = .66, Newman et al., 2008), use of overly polite forms (e.g., “please”; count variable, α = 1.00), apologies (e.g., “I’m sorry”; count variable, α = 1.00,…”
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“One challenge that researchers face is to develop methods for extracting psychologically relevant information from text (Argamon et al. 2003; Riedel et al. 2006; Newman et al. 2008; Dam and Kaufmann 2008; Chung and Pennebaker 2008; Back et al. 2010; Tausczik and Pennebaker 2010; Herdagdelen and Baroni 2011; Diermeier…”
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“In particular, research has shown that people perceive gender even in the absence of explicit cues, for instance, from the writing style (Newman et al., 2008).”
BackgroundDoes Language Type Affect Perceptions of Disability Images? An Experimental Study
Kamenetsky, S. B., & Sadowski, A. S. (2020) · Journal of Education Teaching and Social Studies · doi:10.22158/jetss.v2n4p75 · Cited by 8
“Newman et al. (2008), however, argue that at least some scholars contend that there are no meaningful gender differences in language.”
BackgroundPredicting author profiles from online abuse directed at public figures.
van der Vegt, I., Kleinberg, B., & Gill, P. (2022) · Journal of Threat Assessment and Management · doi:10.1037/tam0000172 · Cited by 8
Crane, P. R., & Ireland, M. E. (2022) · The Journal of Sex Research · doi:10.1080/00224499.2022.2111400 · Cited by 6
“It is also worth noting that men typically use more secondperson pronouns than women (Newman et al., 2008), which may partly explain this result, given that participants who identified as Dominant were predominantly men.”
ResultUnpacking Gender Stereotypes in Film Dialogue
Yu, Y., Hao, Y., & Dhillon, P. S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-19097-1_26 · Cited by 5
A Word Embeddings based Approach for Author Profiling: Gender and Age Prediction
Kavuri, K., & Kavitha, M. (2023) · International Journal on Recent and Innovation Trends in Computing and Communication · doi:10.17762/ijritcc.v11i7s.6996 · Cited by 7
Why cartoons make (some of) us smile
Dunbar, R., & Stirling-Middleton, E. (2024) · Humor - International Journal of Humor Research · doi:10.1515/humor-2023-0111 · Cited by 5
“These di ff erences may re fl ect women ’ s greater facility with language (Coates 2015; Newman et al. 2008), itself re fl ected in their more intense reading habits (Chiu and McBride-Chang 2006; Logan and Johnston 2010; Summers 2013; Uusen and Müürsepp 2012).”
BackgroundBeiza, A. A., Maneethai, D., & Madera, J. M. (2024) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2024.103756 · Cited by 8
Downtoners and intensifiers in different registers
Hennoste, T., Prillop, K., Habicht, K., et al. (2024) · Journal of Uralic Linguistics · doi:10.1075/jul.00029.hen · Cited by 5
Author gender metadata augmentation of hathitrust digital library
Peng, Z., Chen, M., Kowalczyk, S., et al. (2014) · Proceedings of the American Society for Information Science and Technology · doi:10.1002/meet.2014.14505101098 · Cited by 5
Cariola, L. A. (2014) · Imagination Cognition and Personality · doi:10.2190/ic.34.2.d · Cited by 5
Riddle, T., Bhagavatula, S. S., Guo, W., Muresan, S., Cohen, G., Cook, J. E., & Purdie-Vaughns, V. J. (2015) · Educational Data Mining · Cited by 5
“He Said She Said” ― a Male/Female Corpus of Polish
Graliński, F., Borchmann, Ł., & Wierzchoń, P. (2016) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/2suakvj6h2jc · Cited by 5
“For example, (Newman et al., 2008) analyse 14,000 English text samples (45M words) to find gender differences in language use, whereas (Lijffijt et al.”
BackgroundAn Investigation of Different Language Choice through Personal Pronouns in the Twitter
Abdurahman, N. H. (2017) · Indonesian Journal of EFL and Linguistics · doi:10.21462/ijefll.v2i1.18 · Cited by 5
“Firstly, to find evidence whether involved features, particularly personal pronouns, are more frequent in women-authored discourses as found in many studies (Argamon et al., 2003; Argamon et al., 2007; Newman et al., 2008; Bamman et al., 2014).”
BackgroundResultInfluentialGender Differences in the Length of Words and Sentences on the Corpus of Congressional Speeches
Lenard, D. B. (2016) · Imperial journal of interdisciplinary research · Cited by 5
Polat, B. (2022) · Digital Archive @ GSU · doi:10.57709/5510657 · Cited by 5
Informational and relational functions of evidentiality in interaction
Söderqvist, E. B. (2020) · Studia Neophilologica · doi:10.1080/00393274.2020.1724823 · Cited by 5
“…female speakers (Holmes & Stubbe 1997; Merrill et al. 2015); women have also been found more likely to produce various linguistic features that might indicate greater attention to the relational aspect of communication, such as pronouns and references to thoughts and emotions (Newman et al. 2008).”
BackgroundFišer, D., & de Maiti, K. P. (2020) · Modern Languages Open · doi:10.3828/mlo.v0i0.295 · Cited by 5
How Self-Reflection Influences Use of Cognitive and Analytical Language
Brownlow, S., Fogleman, E. L., & Hirsch, S. (2020) · Psychology and Cognitive Sciences - Open Journal · doi:10.17140/pcsoj-6-154 · Cited by 5
Fernández-Cabana, M., Araújo, J. R., & Pérez, M. T. (2014) · Redalyc (Universidad Autónoma del Estado de México) · Cited by 5
Brauer, K., Sendatzki, R., & Proyer, R. T. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.935009 · Cited by 5
Ndum, E., Allen, J., Way, J. D., & Casillas, A. (2017) · Journal of Advanced Academics · doi:10.1177/1932202x17740331 · Cited by 6
Gender Classification with Data Independent Features in Multiple Languages
Isbister, T., Kaati, L., & Cohen, K. (2017) · European Intelligence and Security Informatics Conference · doi:10.1109/eisic.2017.16 · Cited by 5
Gender Differences in Being Thanked for Performing a Favor
Katz, A. N., & Woodbury, J. A. R. (2016) · Journal of Psycholinguistic Research · doi:10.1007/s10936-016-9449-8 · Cited by 5
Metadata
- Authors
- Newman, M. L., Groom, C. J., Handelman, L. D., & Pennebaker, J. W.
- Affiliations
- Arizona State University (US)
- Department for Work and Pensions (GB)
- Oxford University Press (United Kingdom) (GB)
- The University of Texas at Austin (US)
- ORCID
- Pennebaker, James W.
- Venue
- Discourse Processes
- Publisher
- Informa UK Limited
- Published
- 2008-05-15
- Volume
- 45
- Issue
- 3
- Pages
- 211-236
- ISSN
- 0163-853X (ISSN-L)
- 1532-6950
- OpenAlex
- W2139875525
- Cited by
- 788
- References
- 54
- Citations by year
- 2026: 28 · 2025: 47 · 2024: 48 · 2023: 61 · 2022: 91 · 2021: 57 · 2020: 63 · 2019: 53 · 2018: 59 · 2017: 61 · 2016: 46 · 2015: 38 · 2014: 59 · 2013: 21 · 2012: 20
- FWCI
- 27.49
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Discourse Processes (publishedVersion)
- Topics
- Social Sciences › Gender Studies › Gender Studies in Language
- Social Sciences › Linguistics and Language › Discourse Analysis in Language Studies
- Social Sciences › Linguistics and Language › Linguistic Variation and Morphology
- Keywords
- gender differences in language, language use, women's language, men's language, text analysis, topic categories, object properties, discourse analysis
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.
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