专题:Authorship Attribution and Profiling

This cluster of papers focuses on authorship attribution, stylometry, and user profiling in text, utilizing techniques such as text classification, machine learning, and forensic linguistics to analyze gender differences and language use in social media. The research aims to identify authors of anonymous texts, predict demographic attributes from online content, and study the linguistic uniqueness of individuals across different genres and languages.
最新文献
近5年高被引文献
GPT detectors are biased against non-native English writers

article Full Text OpenAlex 652 FWCI56.7968

Testing of detection tools for AI-generated text

article Full Text OpenAlex 575 FWCI138.3088

Evaluating the efficacy of AI content detection tools in differentiating between human and AI-generated text

article Full Text OpenAlex 386 FWCI93.3271

Human heuristics for AI-generated language are flawed

article Full Text OpenAlex 338 FWCI29.2845

How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection

preprint Full Text OpenAlex 312 FWCI0

Can linguists distinguish between ChatGPT/AI and human writing?: A study of research ethics and academic publishing

article Full Text OpenAlex 259 FWCI62.4453

Detection of GPT-4 Generated Text in Higher Education: Combining Academic Judgement and Software to Identify Generative AI Tool Misuse

article Full Text OpenAlex 230 FWCI55.4534

The false positives and false negatives of generative AI detection tools in education and academic research: The case of ChatGPT

article Full Text OpenAlex 218 FWCI52.5092

A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions

article Full Text OpenAlex 210 FWCI78.7062

Machine-Generated Text: A Comprehensive Survey of Threat Models and Detection Methods

article Full Text OpenAlex 195 FWCI16.9791