使用社交媒体和人格特征来评估软件开发人员的情感极性
Leo Silva1, Marília Gurgel de Castro2, Miriam Bernardino Silva2
1Centre of Informatics and Systems, University of Coimbra, Coimbra, Portugal.
PeerJ. Computer science
|October 9, 2023
概括
这项研究表明,分析软件开发人员的社交媒体帖子可以准确地衡量他们的情绪. 这种非侵入性的方法有助于识别可能影响软件开发生产率和质量的情绪转变.
科学领域:
- 软件工程 软件工程 软件工程
- 人与计算机的交互
- 情绪分析 情绪分析
背景情况:
- 人类因素对于软件开发的生产力和质量至关重要.
- 评估软件开发人员的情绪和个性特征是具有挑战性的,因为测量难度和现有方法的侵入性.
- 目前的情绪检测方法 (面部表情,调查,生物识别) 是侵入性的,仅限于正常工作时间.
研究的目的:
- 评估使用社交媒体帖子 (例如,Twitter) 进行软件开发人员非侵入性,长期情绪极性评估的可行性.
- 识别可能影响软件开发结果的情感情绪转变.
- 探索软件开发人员的个性特征和情绪表达之间的关系.
主要方法:
- 在来自16个软件开发人员的79,029条公开推特帖子数据集上评估了31种无监督的基于词典的技术.
- 使用了一组SentiStrength,Sentilex-PT和LIWC2015_PT词典.
- 评估了开发人员的五大性格特征,并将它们与情绪极性相关联.
主要成果:
- 推特数据是准确推断情绪极性的一个有效来源,达到0.745的宏F1-Score和76.8%的准确性.
- 在31.25%的参与者中,在工作期间与非工作期间的推特极性之间存在统计学上显著的差异.
- 人格特征显示了相关性:开放,良心和外向与中立/积极帖子相关;神经主义与负面帖子相关.
结论:
- 社交媒体分析为软件开发中的情绪评估提供了一个准确,简单和非侵入性的替代方案.
- 监测情绪极性,即使在工作时间之外,也可能与理解开发人员情绪有关.
- 这种方法可以支持决策,以提高软件开发流程和团队福祉.
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