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Related Experiment Video

Updated: Jul 17, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Large-Scale Social Feedback and Language Usage: a Distributional Analysis.

Brendan T Johns¹

¹Department of Psychology, McGill University, 2001 McGill College Avenue, Montreal, QC H3 A 1G1 Canada.

Computational Brain & Behavior

|July 16, 2026

Summary

Social feedback on Reddit comments influences language use. Normative language, or typical word patterns, correlates with positive social approval, suggesting form matters as much as content for message acceptance.

Keywords:

Big data Cognitive modeling Corpus studies Distributional semantics Lexical organization Lexical semantics

Related Experiment Videos

Last Updated: Jul 17, 2026

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

Published on: June 25, 2019

Area of Science:

Computational cognitive science
Social media analysis
Linguistic studies

Background:

Computational cognitive science increasingly uses large-scale naturalistic data to test theories.
Social feedback, defined by upvotes and downvotes on Reddit, offers a novel way to study social approval's impact on language.
Previous research has explored individualized language models for analyzing user behavior.

Purpose of the Study:

To investigate the relationship between social feedback and language usage on the Reddit platform.
To determine if linguistic norms influence the social reception of online comments.
To examine this connection at both aggregate and individual commenter levels.

Main Methods:

Analysis of over 400 billion words from Reddit comments, including social feedback data (upvotes minus downvotes).
Creation of large corpora (approx. 1.7 billion words) categorized by comment sentiment (positive, negative, neutral).
Development of individual corpora for over 1,500 high-level commenters using distributional modeling techniques on lexical and semantic data.

Main Results:

Comments with positive social feedback exhibited greater alignment with normative language usage.
This trend indicates that the structural form of an utterance, not just its content, may influence its acceptability.
Individual commenters with more typical language patterns generally received higher social ratings.

Conclusions:

Social approval on online platforms is linked to adherence to linguistic norms.
The findings suggest that the way something is communicated (distributional form) is crucial for social acceptance.
Normative language usage appears to be a significant factor in receiving positive social feedback in online discussions.