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Investigating how infants first establish relationships between words is a necessary step towards understanding how an interconnected network of semantic relationships develops in the adult lexical-semantic system. Stimuli selection for these child studies is critical since words must be both familiar and highly imageable. However, there has been a reliance on adult word association norms to inform stimuli selection in English infant studies to date, as no resource currently exists for child-specific word associations. We present three experiments that explore the strength of word-word relationships in 3-year-olds. Experiment 1 collected children's word associations (WA) (N = 150; female = 84, L1 = British English) and compared them to adult associative norms (Moss & Older, 1996; Nelson et al., 2004 (Behavior Research Methods, Instruments, & Computers, 36(3), 402-407)). Experiment 2 replicated WAs from Experiment 1 in an online adaptation of the task (N = 24: 13 female, L1 = British English). Both experiments indicated a high proportion of child-specific WAs not represented in adult norms (Moss & Older, 1996; Nelson et al., 2004 (Behavior Research Methods, Instruments, & Computers, 36(3), 402-407)). Experiment 3 tested noun-noun WAs from these responses in an online semantic priming study (N = 40: 19 female, L1 = British English) and found that association type modulated priming (F(2.57, 100.1) = 13.13, p <. 0001, generalized η 2 = .19). This research presents a resource of child-specific imageable noun-noun word pair stimuli suitable for testing young children in word recognition and semantic priming studies., (© 2024. The Author(s).)

How words are associated within the linguistic environment conveys semantic content; however, different contexts induce different linguistic patterns. For instance, it is well known that adults speak differently to children than to other adults. We present results from a new word association study in which adult participants were instructed to produce either unconstrained or child-oriented responses to each cue, where cues included 672 nouns, verbs, adjectives, and other word forms from the McArthur-Bates Communicative Development Inventory (CDI; Fenson et al., 2006). Child-oriented responses consisted of higher frequency words with fewer letters, earlier ages of acquisition, and higher contextual diversity. Furthermore, the correlations among the responses generated for each pair of cues differed between unconstrained (adult-oriented) and child-oriented responses, suggesting that child-oriented associations imply different semantic structure. A comparison of growth models guided by a semantic network structure revealed that child-oriented associations are more predictive of early lexical growth. Additionally, relative to a growth model based on a corpus of naturalistic child-directed speech, the child-oriented associations explain added unique variance to lexical growth. Thus, these new child-oriented word association norms provide novel insight into the semantic context of young children and early lexical development., (© 2022. The Author(s).)

Background: It has been suggested that mood influences the breadth of associated information available for retrieval, with positive mood broadening and negative mood constricting the scope of associations. In this study, we asked whether this mood-associations connection is related to controlled processes which were linked to clinical symptoms in depression., Methods: We used the semantic priming paradigm, which allows the dissociation of automatic and controlled processes by using short and long intervals between prime and target words. We further examined whether the strength of semantic relations (weak or strong) influence the priming effects in both neurotypical and depressed individuals., Results: Experiment 1, testing neurotypical individuals, showed priming effects for strong semantically-related words regardless of interval length, but priming effects for weak semantically-related words were smaller in short intervals than in long intervals. Experiment 2, testing depressed individuals in long intervals, showed smaller priming effects for weak semantically-related words than shown by neurotypicals, but priming effects for strong semantically-related words which were comparable between the groups., Limitations: This study cannot determine the source for the differences in priming effects between depressed individuals and neurotypicals, and further studies are needed., Conclusions: This is the first study to show priming impairments in depressed individuals. We discuss our results in light of leading theories concerning cognitive impairment in depression, as well as the newly emerged field of digital psychiatry., (Copyright © 2022 Elsevier B.V. All rights reserved.)

We examined word associations in Swedish children with Developmental Language Disorder (DLD) compared to their typically developing (TD) peers. Furthermore, the study aimed to explore the dimensions of vocabulary knowledge (breadth, depth, and fluency) in these children. Fifty children (15 DLD and 35 TD) participated in the study, aged six to nine years. This age span is commonly associated with substantial lexical reorganisation, by some referred to as the syntagmatic-paradigmatic shift. Fifty items from the Kent-Rosanoff list were used to elicit word associations (say the first word that comes to mind). Word associations were coded as paradigmatic (lion-tiger), syntagmatic (chair-sit), phonological (moon-poon), and other/no answer (foot-hello/bed- -). A semantic depth score (paradigmatic and syntagmatic associations) was calculated and analysed. The children with DLD showed significantly lower semantic depth scores than their TD peers, in line with previous research in English-speaking children. However, the vocabulary dimensions were uniformly affected for the DLD group, contradicting previous findings of semantic depth as a particular area of weakness in this group.

One of the most significant recent advances in the study of semantic processing is the advent of models based on text and other corpora. In this study, we address what impact both the quantitative and qualitative properties of corpora have on mental representations derived from them. More precisely, we evaluate models with different linguistic and mental constraints on their ability to predict semantic relatedness between items from a vast range of domains and categories. We find that a model based on syntactic dependency relations captures significantly less of the variability for all kinds of words, regardless of the semantic relation between them or their abstractness. The largest difference was found for concrete nouns, which are commonly used to assess semantic processing. For both models we find that limited amounts of data suffice in order to obtain reliable predictions. Together, these findings suggest new constraints for the construction of mental models from corpora, both in terms of the corpus size and in terms of the linguistic properties that contribute to mental representations.

Similarity, which plays a key role in fields like cognitive science, psycholinguistics and natural language processing, is a broad and multifaceted concept. In this work we analyse how two approaches that belong to different perspectives, the corpus view and the psycholinguistic view, articulate similarity between verb senses in Spanish. Specifically, we compare the similarity between verb senses based on their argument structure, which is captured through semantic roles, with their similarity defined by word associations. We address the question of whether verb argument structure, which reflects the expression of the events, and word associations, which are related to the speakers' organization of the mental lexicon, shape similarity between verbs in a congruent manner, a topic which has not been explored previously. While we find significant correlations between verb sense similarities obtained from these two approaches, our findings also highlight some discrepancies between them and the importance of the degree of abstraction of the corpus annotation and psycholinguistic representations. [ABSTRACT FROM AUTHOR]

Word ratings on affective dimensions are an important tool in psycholinguistic research. Traditionally, they are obtained by asking participants to rate words on each dimension, a time-consuming procedure. As such, there has been some interest in computationally generating norms, by extrapolating words' affective ratings using their semantic similarity to words for which these values are already known. So far, most attempts have derived similarity from word co-occurrence in text corpora. In the current paper, we obtain similarity from word association data. We use these similarity ratings to predict the valence, arousal, and dominance of 14,000 Dutch words with the help of two extrapolation methods: Orientation towards Paradigm Words and k-Nearest Neighbors. The resulting estimates show very high correlations with human ratings when using Orientation towards Paradigm Words, and even higher correlations when using k-Nearest Neighbors. We discuss possible theoretical accounts of our results and compare our findings with previous attempts at computationally generating affective norms. [ABSTRACT FROM AUTHOR]

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The study set out to examine the effects of multicompetence on proficient L2 users' associative links. Three groups of 36 participants each were recruited – NSs of English, NSs of Bulgarian, and proficient Bulgarian L2 users of English – who completed a familiarity and word association test. The findings revealed that L2 users' natural drive to main connectivity of their lexicons was the motivation for their building lexicosemantic connectedness – which, however, was unlike the patterns of connectivity maintained by the native speakers of both their languages. This showed that, as a result of their developing multicompetence, the L2 users were unlike nativelike in that they developed their lexicosemantic associative links favoring diversity over communality and language-neutral idiosyncrasy over L1 or L2 nativelikeness. [ABSTRACT FROM AUTHOR]

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia. [ABSTRACT FROM AUTHOR]

An astronomical set of sentences can be produced in natural language by combining relatively simple sentence structures with a human-size lexicon. These sentences are within the range of human language performance. Here, we investigate the ability of simple recurrent networks (SRNs) to handle such combinatorial productivity. We successfully trained SRNs to process sentences formed by combining sentence structures with different groups of words. Then, we tested the networks with test sentences in which words from different training sentences were combined. The networks failed to process these sentences, even though the sentence structures remained the same and all words appeared on the same syntactic positions as in the training sentences. In these combination cases, the networks produced work-word associations, similar to the condition in which words are presented in the context of a random word sequence. The results show that SRNs have serious difficulties in handling the combinatorial productivity that underlies human language performance. We discuss implications of this result for a potential neural architecture of human language processing. [ABSTRACT FROM AUTHOR]

An abnormal facilitation of the spreading activation within semantic networks is thought to underlie schizophrenics' remote associations and referential ideas. In normal subjects, elevated magical ideation (MI) has also been associated with a style of thinking similar to that of schizotypal subjects. We thus wondered whether normal subjects with a higher MI score would judge “loose associations” as being more closely related than do subjects with a lower MI score. In two experiments, we investigated whether judgments of the semantic distance between stimulus words varied as a function of MI. In the first experiment, random word pairs of two word classes, animals and fruits, were presented. Subjects had to judge the semantic distance between word pairs. In the second experiment, sets of three words were presented, consisting of a pair of indirectly related, or unrelated nouns plus a third noun. Subjects had to judge the semantic distance of the third noun to the word pair. The results of both experiments showed that higher MI subjects considered unrelated words as more closely associated than did lower MI subjects. We conjecture that for normal subjects high on MI “loose associations” may not be loose after all. We also note that the tendency to link uncommon, nonobvious, percepts may not only be the basis of paranormal and paranoid ideas of reference, but also a prerequisite of creative thinking. [ABSTRACT FROM AUTHOR]