mlsanityData to 14 Oct 2026

Contrasting Linguistic Patterns in Human and LLM-Generated News Text

arXiv 2308.09067 ↗First posted 17 Aug 2023cs.CLcited by 62

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Abstract (arXiv)

We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from six different LLMs that cover three different families and four sizes in total. Our analysis spans several measurable linguistic dimensions, including morphological, syntactic, psychometric, and sociolinguistic aspects. The results reveal various measurable differences between human and AI-generated texts. Human texts exhibit more scattered sentence length distributions, more variety of vocabulary, a distinct use of dependency and constituent types, shorter constituents, and more optimized dependency distances. Humans tend to exhibit stronger negative emotions (such as fear and disgust) and less joy compared to text generated by LLMs, with the toxicity of these models increasing as their size grows. LLM outputs use more numbers, symbols and auxiliaries (suggesting objective language) than human texts, as well as more pronouns. The sexist bias prevalent in human text is also expressed by LLMs, and even magnified in all of them but one. Differences between LLMs and humans are larger than between LLMs.

Key facts. Cited by 62 papers in the map (data through 14 Oct 2026). Builds on 39 of its 81 references that are in the map. First posted on arXiv 17 Aug 2023.

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39 of 81 references.

References · 39

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 3; 2024: 9; 2025: 28; 2026: 22.

62 papers.

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  1. 2023A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directionscited by 105
  2. 2024Do LLMs write like humans? Variation in grammatical and rhetorical stylescited by 62
  3. 2023Bias of AI-Generated Content: An Examination of News Produced by Large Language Modelscited by 38
  4. 2024Exploring the Deceptive Power of LLM-Generated Fake News: A Study of Real-World Detection Challengescited by 30
  5. 2025The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Modelscited by 29
  6. 2026Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunitiescited by 20
  7. 2025Comparing LLM-generated and human-authored news text using formal syntactic theorycited by 11
  8. 2025Catch Me If You Can? Not Yet: LLMs Still Struggle to Imitate the Implicit Writing Styles of Everyday Authorscited by 10
  9. 2025BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Datacited by 10
  10. 2024A Linguistic Comparison between Human and ChatGPT-Generated Conversationscited by 9
  11. 2025Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Taskscited by 9
  12. 2025Consistency of Responses and Continuations Generated by Large Language Models on Social Mediacited by 7
38 more
  1. 2025Linguistic Characteristics of AI-Generated Text: A Surveycited by 7
  2. 2023How many words does ChatGPT know? The answer is ChatWordscited by 6
  3. 2024ESPERANTO: Evaluating Synthesized Phrases to Enhance Robustness in AI Detection for Text Originationcited by 6
  4. 2025Linguistic and Embedding-Based Profiling of Texts generated by Humans and Large Language Modelscited by 6
  5. 2024Investigating Wit, Creativity, and Detectability of Large Language Models in Domain-Specific Writing Style Adaptation of Reddit's Showerthoughtscited by 5
  6. 2024Differentiating Between Human-Written and AI-Generated Texts Using Automatically Extracted Linguistic Featurescited by 5
  7. 2025Users Favor LLM-Generated Content -- Until They Know It's AIcited by 4
  8. 2025Beyond One-Size-Fits-All: Inversion Learning for Highly Effective NLG Evaluation Promptscited by 4
  9. 2025IRLBench: A Multi-modal, Culturally Grounded, Parallel Irish-English Benchmark for Open-Ended LLM Reasoning Evaluationcited by 4
  10. 2024Towards Reliable Detection of LLM-Generated Texts: A Comprehensive Evaluation Framework with CUDRTcited by 3
  11. 2025The Arabic AI Fingerprint: Stylometric Analysis and Detection of Large Language Models Textcited by 3
  12. 2025On the Detectability of LLM-Generated Text: What Exactly Is LLM-Generated Text?cited by 3
  13. 2026Markovian Generation Chains in Large Language Modelscited by 3
  14. 2026More Aligned, Less Diverse? Analyzing the Grammar and Lexicon of Two Generations of LLMscited by 3
  15. 2025Beyond checkmate: exploring the creative chokepoints in AI textcited by 2
  16. 2025Did ChatGPT or Copilot use alter the style of internet news headlines? A time series regression analysiscited by 2
  17. 2025EMMM, Explain Me My Model! Explainable Machine Generated Text Detection in Dialoguescited by 2
  18. 2026Spotlights and Blindspots: Evaluating Machine-Generated Text Detectioncited by 2
  19. 2024MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detectioncited by 1
  20. 2024Is the Digital Forensics and Incident Response Pipeline Ready for Text-Based Threats in LLM Era?cited by 1
  21. 2025Feature Extraction and Analysis for GPT-Generated Textcited by 1
  22. 2025How Persuasive Could LLMs Be? A First Study Combining Linguistic-Rhetorical Analysis and User Experimentscited by 1
  23. 2025AI Brown and AI Koditex: LLM-Generated Corpora Comparable to Traditional Corpora of English and Czech Textscited by 1
  24. 2025A Generalizable Rhetorical Strategy Annotation Model Using LLM-based Debate Simulation and Labellingcited by 1
  25. 2025AI Text Detectors and the Misclassification of Slightly Polished Arabic Textcited by 1
  26. 2026How to measure the optimality of word or gesture order with respect to the principle of swap distance minimizationcited by 1
  27. 2026Interpretable Stylistic Variation in Human and LLM Writing Across Genres, Models, and Decoding Strategiescited by 1
  28. 2026Paraphrasing Attack Resilience of Various AI-Generated Text Detection Methodscited by 1
  29. 2026Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimizationcited by 1
  30. 2025ChatGPT for President! Presupposed content in politicians versus GPT-generated textscited by 0
  31. 2025From Thinking to Output: Chain-of-Thought and Text Generation Characteristics in Reasoning Language Modelscited by 0
  32. 2025EduCoder: An Open-Source Annotation System for Education Transcript Datacited by 0
  33. 2025How Do LLM-Generated Texts Impact Term-Based Retrieval Models?cited by 0
  34. 2025IDEAlign: Comparing Ideas of Large Language Models to Domain Expertcited by 0
  35. 2025Surprisal reveals diversity gaps in image captioning and different scorers change the storycited by 0
  36. 2025LLM-Generated Negative News Headlines Dataset: Creation and Benchmarking Against Real Journalismcited by 0
  37. 2026Explaining Generalization of AI-Generated Text Detectors Through Linguistic Analysiscited by 0
  38. 2026Do Large Language Models Adapt to Language Variation across Socioeconomic Status?cited by 0

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