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Emotions play a fundamental role in language learning, use, and processing. Words denoting positivity account for a larger part of the lexicon than words denoting negativity, and they also tend to be used more frequently, a phenomenon known as positivity bias. However, language experience changes over an individual’s lifetime, making the examination of the emotion-laden lexicon an important topic not only across the life span but also across languages. Furthermore, existing theories predict a range of different age-related trajectories in processing valenced words. The present study pits all of these predictions against written productions (Facebook status updates from over 20,000 users) and behavioral data from three publicly available megastudies on different languages, namely English, Dutch, and Spanish, across adulthood. The production data demonstrated an increase in positive word types and tokens with advancing age. In terms of comprehension, the results showed a uniform and consistent effect of valence across languages and cohorts based on data from a visual word recognition task. The difference in reaction times to very positive and very negative words declined with age, with responses to positive words slowing down more strongly with age than responses to negative words. We argue that the results stem from lifelong learning and emotion regulation: Advancing age is accompanied by an increased type frequency of positive words in language production, which is mirrored as a discrimination penalty in comprehension. To our knowledge, this is the first study to simultaneously target both language production and comprehension across adulthood and in a cross-linguistic perspective. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

The major aim of the present megastudy of picture-naming norms was to address the shortcomings of the available picture data sets used in psychological and linguistic research by creating a new database of normed colour images that researchers from around the world can rely upon in their investigations. In order to do this, we employed a new form of normative study, namely a megastudy, whereby 1620 colour photographs of items spanning across 42 semantic categories were named and rated by a group of German speakers. This was done to establish the following linguistic norms: speech onset times (SOT), name agreement, accuracy, familiarity, visual complexity, valence, and arousal. The data, including over 64,000 audio files, were used to create the LinguaPix database of pictures, audio recordings, and linguistic norms, which to our knowledge, is the largest available research tool of its kind (http://linguapix.uni-mannheim.de). In this paper, we present the tool and the analysis of the major variables.

We present a new dataset of English word recognition times for a total of 62 thousand words, called the English Crowdsourcing Project. The data were collected via an internet vocabulary test in which more than one million people participated. The present dataset is limited to native English speakers. Participants were asked to indicate which words they knew. Their response times were registered, although at no point were the participants asked to respond as quickly as possible. Still, the response times correlate around .75 with the response times of the English Lexicon Project for the shared words. Also, the results of virtual experiments indicate that the new response times are a valid addition to the English Lexicon Project. This not only means that we have useful response times for some 35 thousand extra words, but we now also have data on differences in response latencies as a function of education and age.

We monitored the progress of 40 children when they first started to acquire a second language (L2) implicitly through immersion. Employing a longitudinal design, we tested them before they had any notions of an L2 (Time 0) and after 1 school year of L2 exposure (Time 1) to determine whether cognitive abilities can predict the success of L2 learning. Task administration included measures of intelligence, cognitive control, and language skills. Initial scores on measures of inhibitory control seemed predictive of L2 Dutch vocabulary acquisition. At the same time, progress on IQ, inhibitory control, attentional shifting, and working memory were also identified as contributing factors, suggesting a more intricate relationship between cognitive abilities and L2 learning than previously assumed. Furthermore, L1 development was mainly predicted by performance on inhibitory control and working memory. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Subjective ratings for age of acquisition, concreteness, affective valence, and many other variables are an important element of psycholinguistic research. However, even for well-studied languages, ratings usually cover just a small part of the vocabulary. A possible solution involves using corpora to build a semantic similarity space and to apply machine learning techniques to extrapolate existing ratings to previously unrated words. We conduct a systematic comparison of two extrapolation techniques: k-nearest neighbours, and random forest, in combination with semantic spaces built using latent semantic analysis, topic model, a hyperspace analogue to language (HAL)-like model, and a skip-gram model. A variant of the k-nearest neighbours method used with skip-gram word vectors gives the most accurate predictions but the random forest method has an advantage of being able to easily incorporate additional predictors. We evaluate the usefulness of the methods by exploring how much of the human performance in a lexical decision task can be explained by extrapolated ratings for age of acquisition and how precisely we can assign words to discrete categories based on extrapolated ratings. We find that at least some of the extrapolation methods may introduce artefacts to the data and produce results that could lead to different conclusions that would be reached based on the human ratings. From a practical point of view, the usefulness of ratings extrapolated with the described methods may be limited.

This paper presents the first systematic examination of the monolingual and bilingual frequency effect (FE) during natural reading. We analyzed single fixations durations on content words for participants reading an entire novel. Unbalanced bilinguals and monolinguals show a similarly sized FE in their mother tongue (L1), but for bilinguals the FE is considerably larger in their second language (L2) than in their L1. The FE in both L1 and L2 reading decreased with increasing L1 proficiency, but it was not affected by L2 proficiency. Our results are consistent with an account of bilingual language processing that assumes an integrated mental lexicon with exposure as the main determiner for lexical entrenchment (Diependaele, Lemhöfer, & Brysbaert, 2013; Gollan et al., 2008). This means that no qualitative difference in language processing between monolingual, bilingual L1 or bilingual L2 is necessary to explain reading behavior. We specify this account and argue that not all groups of bilinguals necessarily have lower L1 exposure than monolinguals do and, in line with Kuperman and Van Dyke (2013), that individual vocabulary size and language exposure change the accuracy of the relative corpus word frequencies and thereby determine the size of the FE’s in the same way for all participants.

Based on an analysis of the literature and a large scale crowdsourcing experiment, we estimate that an average 20 year old native speaker of American English knows 42,000 lemmas and 4,200 non-transparent multiword expressions, derived from 11,100 word families. The numbers range from 27,000 lemmas for the lowest 5% to 52,000 for the highest 5%. Between the ages of 20 and 60, the average person learns 6,000 extra lemmas or about one new lemma every two days. The knowledge of the words can be as shallow as knowing that the word exists. In addition, people learn tens of thousands of inflected forms and proper nouns (names), which account for the substantially high numbers of ‘words known’ mentioned in other publications.

Allomorphy is a phenomenon that occurs in many languages. Several psycholinguistic studies have shown that allomorphy, if present, co-determines cognitive processing. In the present paper we discuss allomorphic variations of Serbian instrumental singular form of pseudo-nouns as emerging from analogical learning. We compare the predictions derived from memory-based language processing models with results from a previous experimental study with adult Serbian native speakers. Results confirm that the production of suffix allomorphs in Serbian instrumental singular masculine nouns can be accounted for by memory-based learning and simple analogical inferences. The present findings are in line with a growing body of research showing that memory-based learning models make relevant predictions about the cognitive processes involved in various linguistic phenomena.

We present SUBTLEX-PL, Polish word frequencies based on movie subtitles. In two lexical decision experiments, we compare the new measures with frequency estimates derived from another Polish text corpus that includes predominantly written materials. We show that the frequencies derived from the two corpora perform best in predicting human performance in a lexical decision task if used in a complementary way. Our results suggest that the two corpora may have unequal potential for explaining human performance for words in different frequency ranges and that corpora based on written materials severely overestimate frequencies for formal words. We discuss some of the implications of these findings for future studies comparing different frequency estimates. In addition to frequencies for word forms, SUBTLEX-PL includes measures of contextual diversity, part-of-speech-specific word frequencies, frequencies of associated lemmas, and word bigrams, providing researchers with necessary tools for conducting psycholinguistic research in Polish. The database is freely available for research purposes and may be downloaded from the authors' university Web site at http://crr.ugent.be/subtlex-pl .

We present word frequencies based on subtitles of British television programmes. We show that the SUBTLEX-UK word frequencies explain more of the variance in the lexical decision times of the British Lexicon Project than the word frequencies based on the British National Corpus and the SUBTLEX-US frequencies. In addition to the word form frequencies, we also present measures of contextual diversity part-of-speech specific word frequencies, word frequencies in children programmes, and word bigram frequencies, giving researchers of British English access to the full range of norms recently made available for other languages. Finally, we introduce a new measure of word frequency, the Zipf scale, which we hope will stop the current misunderstandings of the word frequency effect.

The SUBTLEX-US corpus has been parsed with the CLAWS tagger, so that researchers have information about the possible word classes (parts‐of‐speech, or PoSs) of the entries. Five new columns have been added to the SUBTLEX-US word frequency list: the dominant (most frequent) PoS for the entry, the frequency of the dominant PoS, the frequency of the dominant PoS relative to the entry’s total frequency, all PoSs observed for the entry, and the respective frequencies of these PoSs. Because the current definition of lemma frequency does not seem to provide word recognition researchers with useful information (as illustrated by a comparison of the lemma frequencies and the word form frequencies from the Corpus of Contemporary American English), we have not provided a column with this variable. Instead, we hope that the full list of PoS frequencies will help researchers to collectively determine which combination of frequencies is the most informative.

We present a new database of lexical decision times for English words and nonwords, for which two groups of British participants each responded to 14,365 monosyllabic and disyllabic words and the same number of nonwords for a total duration of 16 h (divided over multiple sessions). This database, called the British Lexicon Project (BLP), fills an important gap between the Dutch Lexicon Project (DLP; Keuleers, Diependaele, & Brysbaert, Frontiers in Language Sciences. Psychology, 1, 174, 2010) and the English Lexicon Project (ELP; Balota et al., 2007), because it applies the repeated measures design of the DLP to the English language. The high correlation between the BLP and ELP data indicates that a high percentage of variance in lexical decision data sets is systematic variance, rather than noise, and that the results of megastudies are rather robust with respect to the selection and presentation of the stimuli. Because of its design, the BLP makes the same analyses possible as the DLP, offering researchers with a new interesting data set of word-processing times for mixed effects analyses and mathematical modeling. The BLP data are available at http://crr.ugent.be/blp and as Electronic Supplementary Materials. Electronic supplementary material The online version of this article (doi:10.3758/s13428-011-0118-4) contains supplementary material, which is available to authorized users.

In three experiments we compared the performance of native English speakers to that of Spanish–English and Dutch–English bilinguals on a masked morphological priming lexical decision task. The results do not show significant differences across the three experiments. In line with recent meta-analyses, we observed a graded pattern of facilitation across stem priming with transparent suffixed primes (e.g., viewer–view), opaque suffixed or pseudo-suffixed primes (e.g., corner–corn) and form control primes (e.g., freeze–free). Priming was largest in the transparent condition, smallest in the form condition and intermediate in the opaque condition. Our data confirm the hypothesis that bilinguals largely adopt the same processing strategies as native speakers (e.g., Lemhofer et al., 2008 ), and constrain the hypothesis that bilinguals rely more heavily on whole-word processing in their second language ( Clahsen et al., 2010 , Ullman, 2004 , Ullman, 2005 ). The observed pattern of morphological priming is in line with earlier monolingual studies, further highlighting the reality of semantic transparency effects in the initial stages of word recognition.

Pseudowords play an important role in psycholinguistic experiments, either because they are required for performing tasks, such as lexical decision, or because they are the main focus of interest, such as in nonword-reading and nonce-inflection studies. We present a pseudoword generator that improves on current methods. It allows for the generation of written polysyllabic pseudowords that obey a given language's phonotactic constraints. Given a word or nonword template, the algorithm can quickly generate pseudowords that match the template in subsyllabic structure and transition frequencies without having to search through a list with all possible candidates. Currently, the program is available for Dutch, English, German, French, Spanish, Serbian, and Basque, and, with little effort, it can be expanded to other languages.

We present a new database of Dutch word frequencies based on film and television subtitles, and we validate it with a lexical decision study involving 14,000 monosyllabic and disyllabic Dutch words. The new SUBTLEX frequencies explain up to 10% more variance in accuracies and reaction times (RTs) of the lexical decision task than the existing CELEX word frequency norms, which are based largely on edited texts. As is the case for English, an accessibility measure based on contextual diversity explains more of the variance in accuracy and RT than does the raw frequency of occurrence counts. The database is freely available for research purposes and may be downloaded from the authors’ university site at http://crr.ugent.be/subtlex-nl or from http://brm psychonomic-journals.org/content/supplemental.

The French Lexicon Project involved the collection of lexical decision data for 38,840 French words and the same number of nonwords. It was directly inspired by the English Lexicon Project (Balota et al., 2007) and produced very comparable frequency and word length effects. The present article describes the methods used to collect the data, reports analyses on the word frequency and the word length effects, and describes the Excel files that make the data freely available for research purposes. The word and pseudoword data from this article may be downloaded from http://brm.psychonomic-journals.org/content/supplemental.

We develop the view that inflection is driven partly by non-phonological analogy and that non-phonological information is of particular importance to the inflection of non-canonical roots, which in the view of [Marcus, G. F., Brinkmann, U., Clahsen, H., Wiese, R., & Pinker, S. (1995). German inflection: the exception that proves the rule. Cognitive Psychology, 29, 189-256.] are inflected by a symbolic rule process. We used the Dutch plural to evaluate these claims. An analysis of corpus data shows that a model using non-phonological information (orthography) produces significantly fewer errors on plurals of non-canonical Dutch nouns, in particular borrowings, than a model that includes only phonological information. Moreover, we show that a double default system, as proposed by Pinker [Pinker, S. (1999). Words and rules. London: Phoenix.], does not offer an advantage over the latter model. A second study, examining the use of orthography in an online plural production task, shows that, in Dutch, the chosen pseudoword plural is significantly affected by non-phonological information. A final simulation study confirms that these results are in line with a model of inflectional morphology that explains the inflection of non-canonical roots by non-phonological analogy instead of by a default rule process.