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.

In this paper, we present a novel approach for automatic summarization. Our system, called CBSEAS, integrates a new method to detect redundancy at its very core, and produce more expressive summaries than previous approaches. Moreover, we show that our system is versatile enough to integrate opinion mining techniques, so that it is capable of producing opinion oriented summaries. The very competitive results obtained during the last Text Evaluation Conference (TAC 2008) show that our approach is efficient.

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