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Age of acquisition and imageability ratings for a large set of words, including verbs and function words.

TLDR
Regression analyses showed that although word length, familiarity, and concreteness make independent contributions to the age of acquisition measure, frequency and imageability are the most important predictors of rated age of Acquisition.
Abstract
Age of acquisition and imageability ratings were collected for 2,645 words, including 892 verbs and 213 function words. Words that were ambiguous as to grammatical category were disambiguated: Verbs were shown in their infinitival form, and nouns (where appropriate) were preceded by the indefinite article (such asto crack anda crack). Subjects were speakers of British English selected from a wide age range, so that differences in the responses across age groups could be compared. Within the subset of early acquired noun/verb homonyms, the verb forms were rated as later acquired than the nouns, and the verb homonyms of high-image ability nouns were rated as significantly less imageable than their noun counterparts. A small number of words received significantly earlier or later age of acquisition ratings when the 20–40 years and 50–80 years age groups were compared. These tend to comprise words that have come to be used more frequently in recent years (either through technological advances or social change), or those that have fallen out of common usage. Regression analyses showed that although word length, familiarity, and concreteness make independent contributions to the age of acquisition measure, frequency and imageability are the most important predictors of rated age of acquisition.

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Age-of-acquisition ratings for 30,000 English words

TL;DR: This megastudy presents age-of-acquisition ratings for 30,121 English content words (nouns, verbs, and adjectives) using the Web-based crowdsourcing technology offered by the Amazon Mechanical Turk to indicate that the ratings collected are as valid and reliable as those collected in laboratory conditions.
Journal ArticleDOI

N-Watch: A program for deriving neighborhood size and other psycholinguistic statistics

TL;DR: A Windows program that enables users to obtain a broad range of statistics concerning the properties of word and nonword stimuli, including measures of word frequency, orthographic similarity, Orthographic and phonological structure, age of acquisition, and imageability, is described.
Journal ArticleDOI

The Berlin Affective Word List Reloaded (BAWL-R).

TL;DR: The BAWL-R is intended to help researchers create stimulus material for a wide range of experiments dealing with the affective processing of German verbal material, and is the first list that not only contains a large set of psycholinguistic indexes known to influence word processing, but also features ratings regarding emotional arousal.
Journal ArticleDOI

Neural correlates of written emotion word processing:a review of recent electrophysiological and hemodynamic neuroimaging studies

TL;DR: The aim of the present review is to integrate findings from electrophysiological (ERP) and hemodynamic neuroimaging (fMRI) studies in order to provide a better understanding of emotion word processing.
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Age-of-acquisition effects in word and picture identification

TL;DR: The measurement and validity of AoA ratings is discussed, along with statistical techniques used for exploring AoA's influence, and evidence for and against the various theories is presented.
References
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Book

From Neuropsychology to Mental Structure

TL;DR: Cognitive neuropsychology is a branch of psychology that investigates the role of language in the development of personality and the role that language plays in the formation of identity.
Journal ArticleDOI

The MRC Psycholinguistic Database

TL;DR: A computerised database of psycholinguistic information is described, where semantic, syntactic, phonological and orthographic information about some or all of the 98,538 words in the database is accessible, by using a specially-written and very simple programming language.
Journal ArticleDOI

Lexical Access and Naming Time.

TL;DR: The authors found a positive correlation between naming times and lexical decision times for words, but not for nonwords, indicating that word naming occurred as a result of a lexical search procedure, rather than occurring prior to lexical searching.
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