Prior research has examined how distributional properties of contexts (number of unique contexts or their informativeness) influence the effort of word recognition. These properties do not directly interrogate the semantic properties of contexts. We evaluated the influence of average concreteness, valence (positivity) and arousal of the contexts in which a word occurs on response times in the lexical decision task, age of acquisition of the word, and word recognition memory performance. Using large corpora and norming mega-studies we quantified semantics of contexts for thousands of words and demonstrated that contextual factors were predictive of lexical representation and processing above and beyond the influence shown by concreteness, valence and arousal of the word itself. Our findings indicate that lexical representations are influenced not only by how diverse the word's contexts are, but also by the embodied experiences they elicit.

This paper investigates the historical (1850s-2000s) evolution of semantics in the English language using contemporaneous, decade-specific computational estimates of word concreteness. Study 1 describes the computational method of generating time-locked estimates of concreteness based on the Corpus of Historic American English, and makes available the computed scores for 25,000 English words over 15 decades. We also report several tests of reliability and validity, demonstrating that our historical concreteness scores have high levels of both. Study 2 uses concreteness scores to revisit findings of studies that use a static set of contemporary human concreteness norms to examine historical trends of semantic change. Specifically, we observed (contra Hills & Adelman, (Cognition, 143, 87-92 2015)) that distinct word types of the English language become increasingly more concrete over time and (in line with Hills & Adelman, (Cognition, 143, 87-92 2015) & Hills, Adelman & Noguchi, (The Quarterly Journal of Experimental Psychology, 70(8), 1603-1619 2016)) that relatively concrete words tend to be used more often than abstract ones. We discuss both contrastive and corroborative claims in light of recent work on semantic evolution and argue for the use of time-locked computed estimates over static human norms when examining diachronic linguistic phenomena.

Existing evidence shows that more abstract mental representations are formed, and more abstract language is used, to characterize phenomena which are more distant from self. Yet the precise form of the functional relationship between distance and linguistic abstractness has been unknown. In four studies, we test whether more abstract language is used in textual references to more geographically distant cities (Study 1), times further into the past or future (Study 2), references to more socially distant people (Study 3), and references to a specific topic (Study 4). Using millions of linguistic productions from thousands of social media users, we determine that linguistic concreteness is a curvilinear function of the logarithm of distance and discuss psychological underpinnings of the mathematical properties of the relationship. We also demonstrate that gradient curvilinear effects of geographic and temporal distance on concreteness are near-identical, suggesting uniformity in representation of abstractness along multiple dimensions.

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National character stereotypes, or beliefs about the personality characteristics of the members of a nation, present a paradox. Such stereotypes have been argued to not be grounded in the actual personality traits of members of nations, yet they are also prolific and reliable. Stereotypes of Canadians and Americans exemplify the paradox; people in both nations strongly believe that the personality profiles of typical Canadians and Americans diverge, yet aggregated self-reports of personality profiles of Canadians and Americans show no reliable differences. We present evidence that the linguistic behavior of nations mirrors national character stereotypes. Utilizing 40 million tweets from the microblogging platform Twitter, in Study 1A we quantify the words and emojis diagnostic of Canadians and Americans. In Study 1B we explore the positivity of national language use. In Studies 2A and 2B, we present the 120 most nationally diagnostic words and emojis of each nation to naive participants, and ask them to assess personality of a hypothetical person who uses either diagnostically Canadian or American words and emojis. Personality profiles derived from the diagnostic words of each nation bear close resemblance to national character stereotypes. We therefore propose that national character stereotypes may be partially grounded in the collective linguistic behaviour of nations.