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Experience is all you need: A large language model application of fine-tuned GPT-3.5 and RoBERTa for aspect-based sentiment analysis of college football stadium reviews

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Dataset and Code Descriptions

  • Training_AE – Fine-tuning dataset for GPT-3.5 to extract aspects (AE).
  • Training_CC – Fine-tuning dataset for GPT-3.5 to classify aspects (CC).
  • Testing_all_variables – Comprehensive testing dataset containing review texts, metadata, and all statistical analysis variables.
  • Testing_analysis – Testing dataset for statistical analysis.
  • RoBERTa_eval_data – Evaluation dataset extracted from the training data for model assessment.
  • Code_SMR – Python code executed on Google Colab for performing all study analyses.

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Experience is all you need: A large language model application of fine-tuned GPT-3.5 and RoBERTa for aspect-based sentiment analysis of college football stadium reviews

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