论文标题
谁赢得了权力游戏？情感如何改善候选人选择的预测
Who Wins the Game of Thrones? How Sentiments Improve the Prediction of Candidate Choice
论文作者
论文摘要
本文分析了候选人选择预测如何通过不同的心理预测因素改善。为了调查这个问题，它收集了一个原始的调查数据集，其中包含流行的电视连续剧“权力的游戏”。受访者回答了他们期望在该系列的最后一集中赢得哪个角色，并解释了他们在自由文字中选择最终候选人的选择，从中提取了情感。将这些情感与候选人的喜好和候选人个性评分得出的特征集进行了比较。在我们在100次重复中对10倍跨验证的基准测试中，除了可爱的评级外，所有功能集都在基本模型上的持续集合中的准确性提高了10-11％。通过合成少数族裔过度采样（SMOTE）治疗班级失衡（SMOTE）增加了持有的绩效20-34％，但令人惊讶的是不测试设定的性能。综上所述，我们的研究提供了对心理预测因素的其他预测价值的量化估计。基于个性，情感价和基本情绪的功能集明显优于可爱性评分。
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.
