Emails by LLMs: A Comparison of Language in AI-Generated and Human-Written Emails

The growing excitement around generative AI (and LLMs) is fueling a heightened interest in the development of AI-assisted writing tools.One popular context is AI-assisted email writing, and this paper explores how AI-generated emails compare to human-written emails.We obtained human-written emails from the W3C corpus and generated analogous AI-generated emails using GPT-3.5,GPT-4, Llama-2, and Mistral-7B, and compared AI-generated and humanwritten emails using a suite of natural language analyses across syntactic, semantic, and psycholinguistic dimensions.AI-generated emails are generally consistent across different LLMs but differ significantly from human-written emails.Specifically, AI-generated emails tend to be more formal, verbose, and complex, whereas human-written emails are often more concise and personalized.While AI-generated emails are slightly more polite, both types exhibit a similar level of empathetic tone in language.Further, we qualitatively examined user perceptions of AI and human-written emails by conducting a small survey of 41 participants and interviewing a subset of them.This study highlights preliminary insights into generative AI's distinct strengths and weaknesses in assisting email communication, and we discuss the theoretical and practical implications of the evolving landscape of AI-generated content.

Authors

Institutions

Publication Details

Published
2025-05-19
DOI
https://doi.org/10.1145/3717867.3717872
Citations
2
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
4.96
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Emails by LLMs: A Comparison of Language in AI-Generated and Human-Written Emails

Koustuv Saha, Weijiang Li, S. D. Soni, Y.-T. Lai
2 citations
Topic Modeling
4.96
article

Emails by LLMs: A Comparison of Language in AI-Generated and Human-Written Emails

Koustuv Saha, Weijiang Li, S. D. Soni, Y.-T. Lai
article en
2 citations

Abstract

The growing excitement around generative AI (and LLMs) is fueling a heightened interest in the development of AI-assisted writing tools.One popular context is AI-assisted email writing, and this paper explores how AI-generated emails compare to human-written emails.We obtained human-written emails from the W3C corpus and generated analogous AI-generated emails using GPT-3.5,GPT-4, Llama-2, and Mistral-7B, and compared AI-generated and humanwritten emails using a suite of natural language analyses across syntactic, semantic, and psycholinguistic dimensions.AI-generated emails are generally consistent across different LLMs but differ significantly from human-written emails.Specifically, AI-generated emails tend to be more formal, verbose, and complex, whereas human-written emails are often more concise and personalized.While AI-generated emails are slightly more polite, both types exhibit a similar level of empathetic tone in language.Further, we qualitatively examined user perceptions of AI and human-written emails by conducting a small survey of 41 participants and interviewing a subset of them.This study highlights preliminary insights into generative AI's distinct strengths and weaknesses in assisting email communication, and we discuss the theoretical and practical implications of the evolving landscape of AI-generated content.

Emory University (US), University of Illinois Urbana-Champaign (US)
Quality Education
Openalex Percentile: Top 5%
Topic Modeling
4.96
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.