*.csv; *.json; *.ipynb; *.xlsx; *.pdf; *.doc; *.txt
<p>we consider GPT-4 to generate dialogues according to designed causal structures. Specifically, we, for simplicity, assumed all dialogues are composed of 4 utterances rotating from 2 speakers and designed 4 causal structures to manifest different causal relationships. Along with the designed generating rules according to 4 causal structures, we adopted gpt-4-0314 and Chat Completion api to commence dialogue generation. Below is an example dialogue of the Chain IV from our dataset:
1. Have you seen a dog around here recently?
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Driving practices while HR physiology and pre- and post-EDA were acquired. Stress levels are also rated on a 1-5 scale. The gamer's steering wheel angle, pedals, and steering wheel buttons associated with the driving activity are tracked every 10 msec. The normalized data were stored in Figure 1 in the .xlsx file. Using the Balanced Latin Square method, participants develop each level to avoid level learning when designing experiments with multiple conditions.
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Companion data of the paper "Using social media and personality traits to assess software developers’ emotions" submitted to the IEEE Access journal, 2022. This dataset contains the anonymized dataset used in the study, including the answers of demographic survey, the answers to the Big Five Inventory, the experiment protocol, the manual analysis from psychologists and participants, all generated charts and data analysis.
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