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Are chatbots reliable text annotators? Sometimes
4 references·3 citing·27 second hop
Are chatbots reliable text annotators? Sometimes (2025)Are chatbots reliable text annotators? So…Large language models as a substitute for human experts in annotating political text (2024)Large language models as a su…Unveiling security, privacy, and ethical concerns of ChatGPT (2023)Unveiling security, privacy, …ChatGPT outperforms crowd workers for text-annotation tasks (2023)ChatGPT outperforms crowd wor…ChatGPT for Text Annotation? Mind the Hype! (2023)ChatGPT for Text Annotation? …New opportunities and challenges for conservation evidence synthesis from advances in natural language processing (2025)New opportunities and challen…Let’s talk about language—and its role for replicability (2025)Let’s talk about language—and…A systematic evaluation of text mining methods for short texts: Mapping individuals’ internal states from online posts (2024)A systematic evaluation of te…Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts (2013)Can Large Language Models Transform Computational Social Science? (2023)The dangers of using proprietary LLMs for research (2024)ChatGPT’s Potential for Quantitative Content Analysis: Categorizing Actors in German News Articles (2025)“What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter (2023)Aion Framework: Dimensional Emergence of AI Consciousness, Observer-Induced Collapse, and Cosmological Portal Dynamics (2023)Integrating the adapted UTAUT model with moral obligation, trust and perceived risk to predict ChatGPT adoption for assessment support: A survey with students (2024)Factors influencing academic staff satisfaction and continuous usage of generative artificial intelligence (GenAI) in higher education (2025)Generative artificial intelligence as an enabler of student feedback engagement: a framework (2025)ChatGPT-4 Outperforms Experts and Crowd Workers in Annotating Political Twitter Messages with Zero-Shot Learning (2023)Synthetic Replacements for Human Survey Data? The Perils of Large Language Models (2024)Codebook LLMs: Evaluating LLMs as Measurement Tools for Political Science Concepts (2025)The impact of advanced AI systems on democracy (2025)Content Analysis: An Introduction to its Methodology. (1984)An argument for basic emotions (1992)RoBERTa: A Robustly Optimized BERT Pretraining Approach (2019)Using large language models for preprocessing and information extraction from unstructured text: A proof-of-concept application in the social sciences (2025)Computational Text Analysis for Building and Testing Social Theory (2026)Semantic stability protocol: intercoder reliability for zero-shot classification via AI coders (2026)Why Most Published Research Findings Are False (2005)The weirdest people in the world? (2010)Estimating the reproducibility of psychological science (2015)A typology of reviews: an analysis of 14 review types and associated methodologies (2009)Practical Bayesian Optimization of Machine Learning Algorithms (2012)The PRISMA 2020 statement: an updated guideline for reporting systematic reviews (2021)Can Generative AI improve social science? (2024)Durably reducing conspiracy beliefs through dialogues with AI (2024)
this work references cited by second hop

References

  • 2023ChatGPT outperforms crowd workers for text-annotation tasks1,193 cited
  • 2023Unveiling security, privacy, and ethical concerns of ChatGPT319 cited
  • 2024Large language models as a substitute for human experts in annotating political text103 cited
  • 2023ChatGPT for Text Annotation? Mind the Hype!29 cited

Cited by

  • 2024A systematic evaluation of text mining methods for short texts: Mapping individuals’ internal states from online posts15 cited
  • 2025New opportunities and challenges for conservation evidence synthesis from advances in natural language processing7 cited
  • 2025Let’s talk about language—and its role for replicability6 cited

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