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Predicting gender from electronic discourse.

R Thomson1, T Murachver

  • 1University of Otago, New Zealand.

The British Journal of Social Psychology
|July 12, 2001
PubMed
Summary
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Gendered language is evident in electronic communication, with distinct styles allowing for accurate author identification. This study confirms gender-preferential language use in digital interactions.

Area of Science:

  • Psycholinguistics
  • Sociolinguistics
  • Computer-mediated communication

Background:

  • Established gender differences in face-to-face communication.
  • Hypothesized similar differences in electronic communication (e-discourse).

Purpose of the Study:

  • To investigate gender-preferential language styles in electronic discourse.
  • To determine if readers can accurately identify author gender from e-messages.
  • To analyze linguistic markers associated with gender in digital communication.

Main Methods:

  • Three experiments involving participants sending and receiving electronic messages.
  • Discriminant analysis to classify author gender based on message content (91.4% accuracy).
  • Reader prediction tasks and analysis of gender-neutral messages with male/female versions.

Related Experiment Videos

Main Results:

  • High accuracy (91.4%) in classifying author gender from electronic messages.
  • Readers could correctly predict author gender from e-mails for 14 out of 16 messages.
  • Distinct language variations were identified between male and female authored messages, even on neutral topics.

Conclusions:

  • People utilize gender-preferential language in informal electronic discourse.
  • Gender-linked linguistic differences in e-messages are discernible by readers.
  • Electronic communication reflects and reinforces gendered communication patterns.