论文标题
明确的情感措施：数据科学可能有助于解释数据的复杂性和异质性
Explicit and implicit measures of emotions: Data-science might help to account for data complexity and heterogeneity
论文作者
论文摘要
衡量情绪是基本和应用研究的真正挑战，尤其是在生态环境中。 de Wijk和Noldus提出了将两种类型的措施 - 阐释结合来表征特定食物，并在现实生活中捕捉一顿饭的整体体验。这引发了一些挑战，包括开发新的和微型的传感器和设备，还开发了新的数据分析方式。我们建议对数据分析的未来研究遵循途径：在游戏中包括数据科学。这一研究领域可能会发展预测性但也可以阐明模型，这些模型将情绪的主观经验和现实生活中的生理反应联系起来。我们建议，食品科学家应与计算机科学家合作，然后接受新的数据科学工具培训，这无疑将使他们能够更好地管理复杂和异构的数据集，2/提取对这一研究领域至关重要的知识，这无疑会使他们能够更好地管理他们的舒适区。
Measuring emotions is a real challenge for fundamental and applied research, especially in ecological contexts. de Wijk and Noldus propose combining two types of measures-explicit to characterize a specific food, and implicit-physiological-to capture the whole experience of a meal in real-life situations. This raises several challenges including development of new and miniaturized sensors and devices but also developing new ways of data analysis. We suggest a path to follow for future studies regarding data analysis: to include Data Science in the game. This field of research may enable developing predictive but also explicative models that link subjective experience of emotions and physiological responses in real-life contexts. We suggest that food scientists should go out of their comfort zone by collaborating with computer scientists and then be trained with the new tools of Data Science, which will undoubtedly enable them 1/ to better manage complex and heterogeneous data sets, 2/ to extract knowledge that will be essential to this field of research.
