Using social media and personality traits to assess software developers' emotions

Companion DATA of the paper "Using social media and personality traits to assess software developers’ emotions" submitted to the IEEE Access journal, 2022. The folders contain: /analysis analyzed_tweets_by_psychologists.csv: file containing the manual analysis done by psychologists analyzed_tweets_by_participants.csv: file containing the manual analysis done by participants analyzed_tweets_by_psychologists_solved_divergencies.csv: file containing the manual analysis done by psychologists over 51 divergent tweets' classifications /dataset alldata.json: contains the dataset used in the paper /notebooks General - Charts.ipynb: notebook file containing all charts produced in the study, including those in the paper Statistics - Lexicons and Ensembles.ipynb: notebook file with the statistics for the five lexicons and ensembles used in the study Statistics - Linear Regression.ipynb: notebook file with the multiple linear regression results Statistics - Polynomial Regression: notebook file with the polynomial regression results Statistics - Psychologists versus Participants.ipynb: notebook file with the statistics between the psychologists and participants manual analysis Statistics - Working x Non-working.ipynb: notebook file containing the statistical analysis for the tweets posted during work period and those posted outside of working period /surveys Demographic_Survey.pdf: survey inviting participants to enroll in the study. We collect demographic data and participants' authorization to access their public Tweet posts Demographic_Survey_answers.xlsx: participants' demographic survey answers ibf_pt_br.doc: the Portuguese version of the Big Five Inventory (BFI) instrument to infer participants' Big Five polarity traits ibf_answers.xlsx: participantes' and psychologists' answers for BFI ------------------------------------------------------------ We have removed from dataset any sensible data to protect participants' privacy and anonymity. We have removed from demographic survey answers any sensible data to protect participants' privacy and anonymity.

本数据集为2022年提交至IEEE Access期刊的论文《利用社交媒体与人格特质评估软件开发人员情绪》的配套数据。

各文件夹包含内容如下：

/analysis 文件夹：
- analyzed_tweets_by_psychologists.csv：由心理学家完成的人工标注分析结果文件
- analyzed_tweets_by_participants.csv：由参与者完成的人工标注分析结果文件
- analyzed_tweets_by_psychologists_solved_divergencies.csv：针对51条存在分类分歧的推文，由心理学家完成人工标注并解决分歧后的结果文件

/dataset 文件夹：
- alldata.json：论文研究中使用的数据集文件

/notebooks 文件夹：
- General - Charts.ipynb：包含本研究所有图表（含论文刊载图表）的Jupyter Notebook文件
- Statistics - Lexicons and Ensembles.ipynb：包含本研究所用5种词典与集成模型的统计分析结果的Jupyter Notebook文件
- Statistics - Linear Regression.ipynb：包含多元线性回归分析结果的Jupyter Notebook文件
- Statistics - Polynomial Regression.ipynb：包含多项式回归分析结果的Jupyter Notebook文件
- Statistics - Psychologists versus Participants.ipynb：包含心理学家与参与者人工标注结果对比统计分析的Jupyter Notebook文件
- Statistics - Working x Non-working.ipynb：包含针对工作时段与非工作时段发布推文的统计分析结果的Jupyter Notebook文件

/surveys 文件夹：
- Demographic_Survey.pdf：本研究的参与者招募调查问卷，用于收集参与者人口统计学数据，并获取其公开推文的访问授权
- Demographic_Survey_answers.xlsx：参与者人口统计学调查问卷的作答结果文件
- ibf_pt_br.doc：用于推断参与者大五人格（Big Five Inventory, BFI）极性特质的葡萄牙语版大五人格量表文件
- ibf_answers.xlsx：参与者与心理学家的大五人格量表作答结果文件

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本数据集已移除所有敏感数据，以保护参与者的隐私与匿名性。人口统计学调查问卷作答数据亦已移除所有敏感数据，以保障参与者的隐私与匿名性。