This paper analyzes how candidate choice prediction improves by different
psychological predictors. To investigate this question, it collected an
original survey dataset featuring the popular TV series "Game of Thrones". The
respondents answered which character they anticipated to win in the final
episode of the series, and explained their choice of the final candidate in
free text from which sentiments were extracted. These sentiments were compared
to feature sets derived from candidate likeability and candidate personality
ratings. In our benchmarking of 10-fold cross-validation in 100 repetitions,
all feature sets except the likeability ratings yielded a 10-11% improvement in
accuracy on the holdout set over the base model. Treating the class imbalance
with synthetic minority oversampling (SMOTE) increased holdout set performance
by 20-34% but surprisingly not testing set performance. Taken together, our
study provides a quantified estimation of the additional predictive value of
psychological predictors. Likeability ratings were clearly outperformed by the
feature sets based on personality, emotional valence, and basic emotions.

本研究使用《权力的游戏》作为研究对象，通过调查收集数据，分别从候选人好感度和候选人人格评分两个角度，比较了不同心理预测因素的效果，结果表明，情感价值和基本情感特征比候选人好感度更能准确预测获胜者。