Starting with the idea that sentiment analysis models should be able to
predict not only positive or negative but also other psychological states of a
person, we implement a sentiment analysis model to investigate the relationship
between the model and emotional state. We first examine psychological
measurements of 64 participants and ask them to write a book report about a
story. After that, we train our sentiment analysis model using crawled movie
review data. We finally evaluate participants' writings, using the pretrained
model as a concept of transfer learning. The result shows that sentiment
analysis model performs good at predicting a score, but the score does not have
any correlation with human's self-checked sentiment.

本文提出情感分析模型应该能预测人的其他心理状态，通过研究情感分析模型与情绪状态之间的关系并最终使用预训练模型来评估参与者的作品，得出情感分析模型能在预测分数方面表现良好，但是分数与人的自我检查情绪没有相关性。

文本中的心理状态：情感分析的限制

Psychological State in Text: A Limitation of Sentiment Analysis

For more than 30 years, it has been claimed that a way to improve software
developers' productivity and software quality is to focus on people and to
provide incentives to make developers satisfied and happy. This claim has
rarely been verified in software engineering research, which faces an
additional challenge in comparison to more traditional engineering fields:
software development is an intellectual activity and is dominated by
often-neglected human aspects. Among the skills required for software
development, developers must possess high analytical problem-solving skills and
creativity for the software construction process. According to psychology
research, affects-emotions and moods-deeply influence the cognitive processing
abilities and performance of workers, including creativity and analytical
problem solving. Nonetheless, little research has investigated the correlation
between the affective states, creativity, and analytical problem-solving
performance of programmers. This article echoes the call to employ
psychological measurements in software engineering research. We report a study
with 42 participants to investigate the relationship between the affective
states, creativity, and analytical problem-solving skills of software
developers. The results offer support for the claim that happy developers are
indeed better problem solvers in terms of their analytical abilities. The
following contributions are made by this study: (1) providing a better
understanding of the impact of affective states on the creativity and
analytical problem-solving capacities of developers, (2) introducing and
validating psychological measurements, theories, and concepts of affective
states, creativity, and analytical-problem-solving skills in empirical software
engineering, and (3) raising the need for studying the human factors of
software engineering by employing a multidisciplinary viewpoint.

该研究报告调查了 42 名软件开发人员的情绪、创造力和分析问题解决能力之间的关系，并支持了 “快乐开发者更擅长分析问题解决” 的说法。该研究提供了更好地理解情绪状态对软件开发人员创造力和分析问题解决能力的影响，并引入和验证了关于情感状态、创造力和分析问题解决能力的心理测量、理论和概念，从而提出了利用多学科视角研究软件工程的人因素的需要。