论文标题
匹配的理论和数据与个人性：意大利YouTube的评论揭示了有关个性的评论
Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality
论文作者
论文摘要
作为对英语以外的其他语言检测的贡献，我们依靠遥远的监督来创建个人性，这是意大利语中的YouTube评论的新颖语料库，在其中作者标有个性特征。这些特征源自心理学研究中主流性格理论之一，名为MBTI。使用人格预测实验，我们（i）研究人格预测的任务本身以及在曲折上，也用MBTI标签注释的Twitter数据集； （ii）对分类器使用的特征进行了广泛的深入分析，并特别是根据我们首先用来创建语料库的原始理论的特殊观察。我们观察到，没有单一模型最适合人格检测，尽管某些特征比其他特征更容易检测，并且可以与理论相匹配，但对于其他较不频繁的特征，图片比较模糊。
As a contribution to personality detection in languages other than English, we rely on distant supervision to create Personal-ITY, a novel corpus of YouTube comments in Italian, where authors are labelled with personality traits. The traits are derived from one of the mainstream personality theories in psychology research, named MBTI. Using personality prediction experiments, we (i) study the task of personality prediction in itself on our corpus as well as on TwiSty, a Twitter dataset also annotated with MBTI labels; (ii) carry out an extensive, in-depth analysis of the features used by the classifier, and view them specifically under the light of the original theory that we used to create the corpus in the first place. We observe that no single model is best at personality detection, and that while some traits are easier than others to detect, and also to match back to theory, for other, less frequent traits the picture is much more blurred.
