Department of Psychology, McGill University, 2001 McGill College Avenue, Montreal, Quebec, H3A 1G1, Canada.
Mem Cognit. 2022 Jul;50(5):1013-1032. doi: 10.3758/s13421-021-01249-z. Epub 2021 Nov 22.
Contextual diversity modifies word frequency by ignoring the repetition of words in context (Adelman, Brown, & Quesada, 2006, Psychological Science, 17(9), 814-823). Semantic diversity modifies contextual diversity by taking into account the uniqueness of the contexts that a word occurs in when calculating lexical strength (Jones, Johns, & Recchia, 2012, Canadian Journal of Experimental Psychology, 66, 115-124). Recent research has demonstrated that measures based on contextual and semantic diversity provide a considerable improvement over word frequency when accounting for lexical organization data (Johns, 2021, Psychological Review, 128, 525-557; Johns, Dye, & Jones, 2020a, Quarterly Journal of Experimental Psychology, 73, 841-855). The article demonstrates that these same findings generalize to word-level episodic recognition rates, using the previously released data of Cortese, Khanna, and Hacker (Cortese et al., 2010, Memory, 18, 595-609) and Cortese, McCarty, and Schock (Cortese et al., 2015, Quarterly Journal of Experimental Psychology, 68, 1489-1501). It was found that including the best fitting contextual diversity model allowed for a very large increase in variance accounted for over previously used variables, such as word frequency, signalling commonality with results from the lexical organization literature. The findings of this article suggest that current trends in the collection of megadata sets of human behavior (e.g., Balota et al., 2007, Behavior Research Methods, 39(3), 445-459) provide a promising avenue to develop new theoretically oriented models of word-level episodic recognition data.
语境多样性通过忽略语境中单词的重复来修改单词频率（Adelman、Brown 和 Quesada，2006，《心理科学》，17（9），814-823）。语义多样性通过考虑单词出现的上下文的独特性来修改语境多样性，从而计算词汇强度（Jones、Johns 和 Recchia，2012，《加拿大实验心理学杂志》，66，115-124）。最近的研究表明，基于语境和语义多样性的测量方法在解释词汇组织数据时，比单词频率提供了相当大的改进（Johns，2021，《心理评论》，128，525-557；Johns、Dye 和 Jones，2020a，《实验心理学季刊》，73，841-855）。本文证明，这些相同的发现可以推广到单词级别的情节识别率，使用 Cortese、Khanna 和 Hacker（Cortese 等人，2010，《记忆》，18，595-609）和 Cortese、McCarty 和 Schock（Cortese 等人，2015，《实验心理学季刊》，68，1489-1501）先前发布的数据。研究发现，包括最佳拟合的语境多样性模型可以大大增加方差解释，超过了以前使用的变量，如单词频率，与词汇组织文献的结果具有共同性。本文的研究结果表明，当前收集人类行为大数据集的趋势（例如，Balota 等人，2007，《行为研究方法》，39（3），445-459）为开发新的理论导向的单词级情节识别数据模型提供了一个很有前途的途径。
