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This study aimed at examining the contribution of affective content to the organization of words in the lexicon. Based on existing free association norms and on a series of questionnaires we developed, we examined the characteristics of the words produced as associates to 840 Spanish cue words. Half of them were affective words and the other half were neutral (non-affective) words. Among the affective cue words, some words directly labeled an emotion (emotion words, EM) and others did not label an emotion but could elicit it (emotion-laden words, EL). The words produced as associates were also classified according to this distinction. Furthermore, we examined the relationship between the lexico-semantic and affective properties of the cue words and the associated words. The results revealed that EM, EL, and neutral associated words were elicited to a greater extent by cue words of the same type than by other types of cue words. Furthermore, the degree of correspondence between the affective properties of the cues and their associates was higher than that of lexico-semantic variables. These results have methodological implications for research on semantic memory and are of interest for applied studies focused on affective word organization in specific populations.

Distributional semantic models derive computational representations of word meaning from the patterns of co-occurrence of words in text. Such models have been a success story of computational linguistics, being able to provide reliable estimates of semantic relatedness for the many semantic tasks requiring them. However, distributional models extract meaning information exclusively from text, which is an extremely impoverished basis compared to the rich perceptual sources that ground human semantic knowledge. We address the lack of perceptual grounding of distributional models by exploiting computer vision techniques that automatically identify discrete “visual words” in images, so that the distributional representation of a word can be extended to also encompass its co-occurrence with the visual words of images it is associated with. We propose a flexible architecture to integrate text- and image-based distributional information, and we show in a set of empirical tests that our integrated model is superior to the purely text-based approach, and it provides somewhat complementary semantic information with respect to the latter.

The author reviews theory and research by Ehri and her colleagues to document how a scientific approach has been applied over the years to conduct controlled studies whose findings reveal how beginners learn to read words in and out of text. Words may be read by decoding letters into blended sounds or by predicting words from context, but the way that contributes most to reading and comprehending text is reading words automatically from memory by sight. The evidence shows that words are read from memory when graphemes are connected to phonemes. This bonds spellings of individual words to their pronunciations along with their meanings in memory. Readers must know grapheme–phoneme relations and have decoding skill to form connections, and must read words in text to associate spellings with meanings. Readers move through four developmental phases as they acquire knowledge about the alphabetic writing system and apply it to read and write words and build their sight vocabularies. Grapheme–phoneme knowledge and phonemic segmentation are key foundational skills that launch development followed subsequently by knowledge of syllabic and morphemic spelling–sound units. Findings show that when spellings attach to pronunciations and meanings in memory, they enhance memory for vocabulary words. This research underscores the importance of systematic phonics instruction that teaches students the knowledge and skills that are essential in acquiring word-reading skill.

\"This study provides a definition and a typology of swearing and compares its manifestations in English and 24 other languages. In addition the study traces the history of swearing from its first known appearance in Ancient Egypt to the present day\" -- Provided by publisher.

This study examined how Chinese native speakers (NSs) and second language (L2) learners process compound words. The findings showed that they used the hybrid model of coexistence for whole word and morphemes; and were influenced by word frequency, semantic transparency, and word structure. The results revealed that two groups of participants used hybrid representation when identifying high-frequency words and whole-word representation when identifying low-frequency words. Besides, semantic transparency might impact word structure awareness, and subject-predicate words were the most difficult to process. The research also showed that L2 learners’ word frequency effect was more robust than NSs’; morpheme location information might affect NSs, but L2 learners could not process it. There was variation in NSs’ speed in recognizing transparent and obscure words, but there was no difference among L2 learners. Besides, L2 learners’ word recognition speed could not reach the levels of NSs. Plain Language Summary Since the mental lexicon was put forward, researchers have begun to study the processing and representation of words. As an important part of vocabulary, the processing mechanism of compound words has also received much attention. There have been many studies on how native speakers process compound words so far, but researches on L2 learners are still in its infancy, and most of these studies have been done on English L2 learners, with little research on other languages, for example, Chinese as a second language. Compound words account for about 65% of the vocabulary in Mandarin Chinese. Therefore, research on the processing of Chinese compound words is of great significance. Two lexical judgment experiments were designed for the present study respectively with word frequency, semantic transparency, and lexical structure as independent variables to solve the disputes in the processing of compound words among native Chinese speakers and L2 learners adopting the repetitive priming paradigm based on the reaction time task. This work is the first to explore the interaction effects of semantic transparency and lexical structure on compound word processing. This study may be of particular interest to the general readers of your journal as it gives insight into the compound word processing mechanism of non-English second languages and enriches the theoretical knowledge of L2 word processing from a cross-language perspective. The findings show that they employ the hybrid model of coexistence for whole words and morphemes, and are affected by word frequency, semantic transparency, and word structure. We found that both Chinese native speakers (NS) and L2 learners use hybrid representation when identifying high-frequency words and whole-word representation when identifying low-frequency words; word structure awareness is affected by semantic transparency, and subject-predicate words are the most difficult to process. However, we also found that L2 learners’ word frequency effect is stronger than NSs’; morpheme location information may have an effect on NSs, but L2 learners cannot process it; There is variation in NSs’ speed in recognizing transparent and obscure words, but there is no difference among L2 learners. In addition, L2 learners’ word recognition speed and aptitude cannot reach the levels of NSs. Thus, Chinese L2 learners differ from English L2 learners in their lexical representations, as well as in the effects of semantic transparency, which further enriches the theory of L2 lexical processing.

Information about the affective meanings of words is used by researchers working on emotions and moods, word recognition and memory, and text-based sentiment analysis. Three components of emotions are traditionally distinguished: valence (the pleasantness of a stimulus), arousal (the intensity of emotion provoked by a stimulus), and dominance (the degree of control exerted by a stimulus). Thus far, nearly all research has been based on the ANEW norms collected by Bradley and Lang ( 1999 ) for 1,034 words. We extended that database to nearly 14,000 English lemmas, providing researchers with a much richer source of information, including gender, age, and educational differences in emotion norms. As an example of the new possibilities, we included stimuli from nearly all of the category norms (e.g., types of diseases, occupations, and taboo words) collected by Van Overschelde, Rawson, and Dunlosky (Journal of Memory and Language 50:289-335, 2004 ), making it possible to include affect in studies of semantic memory.