Computational humor detection systems rarely model the subjectivity of humor responses, or consider alternative reactions to humor - namely offense. We analyzed a large dataset of humor and offense ratings by male and female annotators of different age groups. We find that women link these two concepts more strongly than men, and they tend to give lower humor ratings and higher offense scores. We also find that the correlation between humor and offense increases with age. Although there were no gender or age differences in humor detection, women and older annotators signalled that they did not understand joke texts more often than men. We discuss implications for computational humor detection and downstream tasks.
翻译:计算幽默检测系统很少以幽默反应的主观性为模型,或考虑对幽默的替代反应----即犯罪。我们分析了不同年龄组男女评分员的幽默和犯罪评级的庞大数据集。我们发现,妇女比男性更紧密地将这两个概念联系起来,她们往往给予较低的幽默评级和更高的犯罪分数。我们也发现,幽默和犯罪与年龄的关系增加。虽然在幽默检测方面不存在性别或年龄差异,但女性和年长的告别员表示,他们不理解笑话文本的频率高于男性。我们讨论了对计算幽默检测和下游任务的影响。