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.

中文翻译：

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谁赢得了权力的游戏？情绪如何提高对候选人选择的预测

本文分析了不同的心理预测因素如何改善候选人选择预测。为了调查这个问题，它收集了一个以流行电视剧“权力的游戏”为特色的原始调查数据集。受访者回答了他们预计在该系列的最后一集中赢得哪个角色，并在从中提取情感的自由文本中解释他们对最终候选人的选择。将这些情绪与从候选人喜爱程度和候选人个性评级得出的特征集进行比较。在我们对 100 次重复中的 10 倍交叉验证进行的基准测试中，除了喜欢度评级之外的所有特征集都使保留集的准确度比基本模型提高了 10-11%。使用合成少数过采样 (SMOTE) 处理类不平衡将保持集性能提高了 20-34%，但令人惊讶的是没有测试集性能。综上所述，我们的研究提供了对心理预测因子额外预测价值的量化估计。基于个性、情绪效价和基本情绪的特征集明显优于可爱度评级。