The criminalization of poverty has been widely denounced as a collective bias against the most vulnerable. NGOs and international organizations claim that the poor are blamed for their situation, are more often associated with criminal offenses than the wealthy strata of society and even incur criminal offenses simply as a result of being poor. While no evidence has been found in the literature that correlates poverty and overall criminality rates, this paper offers evidence of a collective belief that associates both concepts. This brief report measures the societal bias that correlates criminality with the poor, as compared to the rich, by using Natural Language Processing (NLP) techniques in Twitter. The paper quantifies the level of crime-poverty bias in a panel of eight different English-speaking countries. The regional differences in the association between crime and poverty cannot be justified based on different levels of inequality or unemployment, which the literature correlates to property crimes. The variation in the observed rates of crime-poverty bias for different geographic locations could be influenced by cultural factors and the tendency to overestimate the equality of opportunities and social mobility in specific countries. These results have consequences for policy-making and open a new path of research for poverty mitigation with the focus not only on the poor but on society as a whole. Acting on the collective bias against the poor would facilitate the approval of poverty reduction policies, as well as the restoration of the dignity of the persons affected.

翻译：贫困的犯罪化已被广泛谴责为针对最弱势群体的集体偏见。非政府组织和国际组织声称，穷人因自身处境而受到指责，比社会富裕阶层更常被与刑事犯罪关联，甚至仅仅因为贫困而招致刑事定罪。尽管文献中未发现贫困与整体犯罪率相关的证据，但本文提供了将这两种概念关联起来的集体信念的证据。这份简要报告通过使用Twitter上的自然语言处理技术，衡量了将犯罪与穷人（而非富人）联系起来的社会偏见程度。本文量化了八个不同英语国家的小组中犯罪-贫困偏见的水平。基于文献中与财产犯罪相关的不平等或失业率差异，无法解释犯罪与贫困之间关联的区域差异。不同地理位置观测到的犯罪-贫困偏见率变化可能受到文化因素以及特定国家高估机会平等和社会流动性倾向的影响。这些结果对政策制定具有启示意义，并为减贫开辟了一条新的研究路径，该路径不仅关注穷人，而且着眼于整个社会。对针对穷人的集体偏见采取行动，将有助于减贫政策的批准，以及恢复受影响者的尊严。