Semantic category effect and emotional valence in female university students

The semantic category effect represents a category dissociation between biological and nonbiological objects in picture naming. The aim of this preliminary study was to further examine this phenomenon, and to explore the possible association between the effect and subjective emotional valence for the named objects. Using a speeded picture naming task, vocal reaction times for 45 items were divided into four categories based on emotional valence rating and semantic category, and examined in 36 female university students. Analyses of the data indicated an "animate/inanimate" category dissociation favouring animate objects, in tandem with a potential relationship between subjective emotional valence and semantic processing underlying picture naming.     

Pervasive influence of semantics in letter and category fluency: a multidimensional approach

We used multidimensional statistical procedures to study semantic and lexical processes underlying word retrieval in verbal-fluency performance. Forty healthy participants were given a two-choice letter task (i.e., generate items beginning with the letter 'A' or 'F', in any order) and a two-choice category task (i.e., generate animal or fruit names, in any order). Using correspondence analysis (CoA) and hierarchical clustering (HC), we found evidence of prominent semantic organization in both letter and category fluency. For example, a striking categorical segregation between animate and inanimate entities emerged during the letter task. Analysis of inter-item times revealed strong sequential priming effects in both tasks. Taken together, these results indicate that semantic facilitation is pervasive in word retrieval processes, even in the letter-fluency task, and therefore suggest that the traditional view of letter fluency as a purely phonemically based task should be revised. Finally, our findings may help explain patterns of verbal-fluency measures obtained in focal brain lesion patients.     

The effects of late acquisition of L2 and the consequences of immigration on L1 for semantic and morpho-syntactic language aspects

It has been hypothesized that some aspects of a second language (L2) might be learned easier than others if a language is learned late. On the other hand, non-use might result in a loss of language skills in one's native, i.e. one's first language (L1) (language attrition). To study which, if any, aspects of language are affected by either late acquisition or non-use, long-term German immigrants to the US and English native speakers who are long-term immigrants to Germany as well as two additional control groups of native German speakers were tested with an auditory semantic and morpho-syntactic priming paradigm. German adjectives correctly or incorrectly inflected for gender and semantically associated or not associated with the target noun served as primes. Participants made a lexical decision on the target word. All groups of native German speakers gained from semantically and morpho-syntactically congruent primes. Evidence for language attrition was neither found for semantic nor morpho-syntactic priming effects in the German immigrants. In contrast, English native speakers did not gain from a morpho-syntactic congruent prime, whereas semantic priming effects were similar as for the remaining groups. The present data suggest that the full acquisition of at least some syntactic functions may be restricted to limited periods in life while semantic and morpho-syntactic functions seem to be relatively inured to loss due to non-use.     

Semantic Memory Search and Retrieval in a Novel Cooperative Word Game: A Comparison of Associative and Distributional Semantic Models

Considerable work during the past two decades has focused on modeling the structure of semantic memory, although the performance of these models in complex and unconstrained semantic tasks remains relatively understudied. We introduce a two-player cooperative word game, Connector (based on the boardgame Codenames), and investigate whether similarity metrics derived from two large databases of human free association norms, the University of South Florida norms and the Small World of Words norms, and two distributional semantic models based on large language corpora (word2vec and GloVe) predict performance in this game. Participant dyads were presented with 20-item word boards with word pairs of varying relatedness. The speaker received a word pair from the board (e.g., exam-algebra) and generated a one-word semantic clue (e.g., math), which was used by the guesser to identify the word pair on the board across three attempts. Response times to generate the clue, as well as accuracy and latencies for the guessed word pair, were strongly predicted by the cosine similarity between word pairs and clues in random walk-based associative models, and to a lesser degree by the distributional models, suggesting that conceptual representations activated during free association were better able to capture search and retrieval processes in the game. Further, the speaker adjusted subsequent clues based on the first attempt by the guesser, who in turn benefited from the adjustment in clues, suggesting a cooperative influence in the game that was effectively captured by both associative and distributional models. These results indicate that both associative and distributional models can capture relatively unconstrained search processes in a cooperative game setting, and Connector is particularly suited to examine communication and semantic search processes.     

Probing Lexical Ambiguity: Word Vectors Encode Number and Relatedness of Senses

Lexical ambiguity—the phenomenon of a single word having multiple, distinguishable senses—is pervasive in language. Both the degree of ambiguity of a word (roughly, its number of senses) and the relatedness of those senses have been found to have widespread effects on language acquisition and processing. Recently, distributional approaches to semantics, in which a word's meaning is determined by its contexts, have led to successful research quantifying the degree of ambiguity, but these measures have not distinguished between the ambiguity of words with multiple related senses versus multiple unrelated meanings. In this work, we present the first assessment of whether distributional meaning representations can capture the ambiguity structure of a word, including both the number and relatedness of senses. On a very large sample of English words, we find that some, but not all, distributional semantic representations that we test exhibit detectable differences between sets of monosemes (unambiguous words; N = 964), polysemes (with multiple related senses; N = 4,096), and homonyms (with multiple unrelated senses; N = 355). Our findings begin to answer open questions from earlier work regarding whether distributional semantic representations of words, which successfully capture various semantic relationships, also reflect fine-grained aspects of meaning structure that influence human behavior. Our findings emphasize the importance of measuring whether proposed lexical representations capture such distinctions: In addition to standard benchmarks that test the similarity structure of distributional semantic models, we need to also consider whether they have cognitively plausible ambiguity structure.     

Visual and Affective Multimodal Models of Word Meaning in Language and Mind

One of the main limitations of natural language-based approaches to meaning is that they do not incorporate multimodal representations the way humans do. In this study, we evaluate how well different kinds of models account for people's representations of both concrete and abstract concepts. The models we compare include unimodal distributional linguistic models as well as multimodal models which combine linguistic with perceptual or affective information. There are two types of linguistic models: those based on text corpora and those derived from word association data. We present two new studies and a reanalysis of a series of previous studies. The studies demonstrate that both visual and affective multimodal models better capture behavior that reflects human representations than unimodal linguistic models. The size of the multimodal advantage depends on the nature of semantic representations involved, and it is especially pronounced for basic-level concepts that belong to the same superordinate category. Additional visual and affective features improve the accuracy of linguistic models based on text corpora more than those based on word associations; this suggests systematic qualitative differences between what information is encoded in natural language versus what information is reflected in word associations. Altogether, our work presents new evidence that multimodal information is important for capturing both abstract and concrete words and that fully representing word meaning requires more than purely linguistic information. Implications for both embodied and distributional views of semantic representation are discussed.     

汉字刺激质量与语义启动间的交互作用

本研究探讨汉字刺激质量与语义启动的相互作用,深入考察汉字识别的内在机制。实验采用真假字判断范式,实验1使用语义相关词对比率较高的实验材料,实验2使用语义相关词对比率较低的实验材料,结果发现：（1）无论语义相关词对比率高还是低,均存在语义启动效应和刺激质量效应,且汉字刺激质量与语义启动之间均存在交互作用;（2）轻度模糊刺激较重度模糊刺激受到的语义启动效应更大。结果表明,即使排除了额外反馈的作用,汉字刺激质量与语义启动之间仍存在交互作用,进一步支持交互激活模型。     

Semantic alignment across whole-number arithmetic and rational numbers: evidence from a Russian perspective

ABSTRACT

Solutions to word problems are moderated by the semantic alignment of real-world relations with mathematical operations. Categorical relations between entities (tulips, roses) are aligned with addition, whereas certain functional relations between entities (tulips, vases) are aligned with division. Similarly, discreteness vs. continuity of quantities (marbles, water) is aligned with different formats for rational numbers (fractions and decimals, respectively). These alignments have been found both in textbooks and in the performance of college students in the USA and in South Korea. The current study examined evidence for alignments in Russia. Textbook analyses revealed semantic alignments for arithmetic word problems, but not for rational numbers. Nonetheless, Russian college students showed semantic alignments both for arithmetic operations and for rational numbers. Since Russian students exhibit semantic alignments for rational numbers in the absence of exposure to examples in school, such alignments likely reflect intuitive understanding of mathematical representations of real-world situations.     

The Semantic Drift of Quotations in Blogspace: A Case Study in Short‐Term Cultural Evolution

We present an empirical case study that connects psycholinguistics with the field of cultural evolution, in order to test for the existence of cultural attractors in the evolution of quotations. Such attractors have been proposed as a useful concept for understanding cultural evolution in relation with individual cognition, but their existence has been hard to test. We focus on the transformation of quotations when they are copied from blog to blog or media website: by coding words with a number of well‐studied lexical features, we show that the way words are substituted in quotations is consistent (a) with the hypothesis of cultural attractors and (b) with known effects of the word features. In particular, words known to be harder to recall in lists have a higher tendency to be substituted, and words easier to recall are produced instead. Our results support the hypothesis that cultural attractors can result from the combination of individual cognitive biases in the interpretation and reproduction of representations.     

Grounding by Attention Simulation in Peripersonal Space: Pupils Dilate to Pinch Grip But Not Big Size Nominal Classifier

Grammatical categories represent implicit knowledge, and it is not known if such abstract linguistic knowledge can be continuously grounded in real‐life experiences, nor is it known what types of mental states can be simulated. A former study showed that attention bias in peripersonal space (PPS) affects reaction times in grammatical congruency judgments of nominal classifiers, suggesting that simulated semantics may include reenactment of attention. In this study, we contrasted a Chinese nominal classifier used with nouns denoting pinch grip objects with a classifier for nouns with big object referents in a pupil dilation experiment. Twenty Chinese native speakers read grammatical and ungrammatical classifier‐noun combinations and made grammaticality judgment while their pupillary responses were measured. It was found that their pupils dilated significantly more to the pinch grip classifier than to the big object classifier, indicating attention simulation in PPS. Pupil dilations were also significantly larger with congruent trials on the whole than in incongruent trials, but crucially, congruency and classifier semantics were independent of each other. No such effects were found in controls.