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In this article, we describe the most extensive set of word associations collected to date. The database contains over 12,000 cue words for which more than 70,000 participants generated three responses in a multiple-response free association task. The goal of this study was (1) to create a semantic network that covers a large part of the human lexicon, (2) to investigate the implications of a multiple-response procedure by deriving a weighted directed network, and (3) to show how measures of centrality and relatedness derived from this network predict both lexical access in a lexical decision task and semantic relatedness in similarity judgment tasks. First, our results show that the multiple-response procedure results in a more heterogeneous set of responses, which lead to better predictions of lexical access and semantic relatedness than do single-response procedures. Second, the directed nature of the network leads to a decomposition of centrality that primarily depends on the number of incoming links or in-degree of each node, rather than its set size or number of outgoing links. Both studies indicate that adequate representation formats and sufficiently rich data derived from word associations represent a valuable type of information in both lexical and semantic processing.

In recent years, word associations have played a key role in cognitive research. The goal of this study is to propose a new system called Tarvajeh to construct and analyze the association norms found in the Persian language. In this paper, we present Tarvajeh, a data set for Persian words in a continuous word association task. For data collection, cue words have been categorized into groups and then, 30 of them were presented to each participant in two phases. Afterward, the participants were asked to write the first three words that are related to the initial cue words. After data collection, Tarvajeh included 240 frequent Persian cues and more than 20,000 different responses. Furthermore, we also propose a method that allows participants to compare their responses as well as their subconscious mind with those of their peers using a unique graph that is tailored to their responses and is displayed to them. Finally, we compared our data with those of associated words in other languages. The comparison reveals that, for some cues, most associated words are the same, while for others, the most frequent responses are unique within each data set. In addition, some gender-related differences were observed with male participants spending more time on their responses than female participants.

Many Management (sub-)disciplines, from Organizational Behavior and Marketing to Accounting and Strategy, are interested in antecedents and consequences of individual attitudes and traits. A key aspect of personality profiles are explicit and implicit motives. Yet, Management scholars mainly focus on explicit motives, with limited attention to implicit motives. We argue that this state of affairs probably came into being because current Management researchers mainly rely on implicit motive measures that are either difficult to apply or to develop, hampering researchers from applying implicit motive measures. To overcome the downsides of available instruments, we develop a Brief Implicit Association Test (BIAT) as an efficient, reliable and valid measure of implicit motives, particularly the needs for achievement, affiliation and power. To explore our BIAT's predictive validity, we apply this measure to a specific research domain within Management: Entrepreneurship. We examine implicit motives' association with entrepreneurial self-efficacy, business founding, and financial profitability. Our results show that the introduction of implicit motives can unlock stranded discussions in this research domain. Overall, we argue that implicit motives can help to push the boundaries of the study of deep-level attributes in a wide range of organizational and managerial settings.

The processes tapped by the widely-used word association (WA) paradigm remain a matter of debate: while some authors consider them as driven by lexical co-occurrences, others emphasize the role of meaning-based connections. To test these contrastive hypotheses, we analyzed responses in a WA task in terms of their normative defining features (those describing the object denoted by the cue word). Results indicate that 72.5% of the responses had medium-to-high coincidence with such defining semantic features. Moreover, 75.51% of responses had medium-to-high values of Relevance (a measure of the importance of the feature for construing a given concept). Furthermore, most responses (62.7%) referred to elements of the situation in which the concept usually appears, followed by sensory properties (e.g., color) of the denoted object (27.86%). These results suggest that the processes behind WA tasks involve a reactivation of the cue item’s semantic properties, particularly those most relevant to its core meaning.

China’s basic education and higher education are currently facing policies aimed at reducing and increasing the academic burden, respectively. In this context, we first review and assess the methods of measuring students’ academic burden and then apply the implicit association test for the first time to the academic burden of Chinese students from primary school to university under a unified framework. The results demonstrates that students’ academic burden increases with the school stage, and thus university students face a greater burden than primary and high school students, and that learning attitude fully mediates the relationship between objective and subjective views of academic burden. These results suggest the three policy approaches of implementing a management system for classifying academic burden, considering how to improve students’ learning quality, and developing their mental health education, thus providing a reference and inspiration for research and practice in the field of academic burden.

This study examined word class effects on Yi students’ L2 Chinese word associations. 108 stimulus words, consisting of 36 nouns, 36 verbs, and 36 adjectives, were chosen from Corpus of Modern Chinese, with their frequencies and concreteness being strictly controlled. 80 students from grade 4 and 85 students from grade 10 finished the word association test successfully. The data collected were analyzed under a three-layer framework. The findings show that meaning-based associations seize a predominant position in all the three word classes, among which the semantic network of adjectives develops best. Meanwhile, phonological association is also an important connection mode for the three word classes, although adjectives trigger a relatively lower proportion. All the three word classes can elicit a substantial proportion of encyclopedic associations, with nouns demonstrating the highest triggering rate. As for the subcategories of paradigmatic and syntagmatic associations, nouns are dominated by synonymous, determinative and hierarchical associations, verbs by governing and synonymous associations, and adjectives by determinative, synonymous and antonymous associations. Plain language summary Study on how words from different word classes influence L2 Chinese learners’word association patterns How words are stored and connected to each other in our minds has been a hot issue attracting the attention of researchers for decades. From the 1980s onward, the organization of L2 mental lexicon has received growing attention. While much progress has been made, some issues related to the nature of L2 mental lexicon are still unclear. How words from different word classes might influence L2 learners’ word association patterns is an issue worthy of further exploration. This study, adopting free word association test (WAT), investigated word class effects on L2 Chinese word associations. 165 Yi students taking Chinese as their L2 were recruited from one elementary school and one high school in a Yi-inhabited County in China. The 108 stimulus words were chosen from the 9,000 most frequently used words in modern Chinese, consisting of 36 nouns, 36 verbs, and 36 adjectives. Participants were required to write down the first word popping up in their mind when they see the stimulus words. We used a three-layer framework previously used to analyze L1 Chinese to analyze the WAT results. The findings revealed that Yi students’ L2 Chinese word associations share some common features with other L2 learners while particular characteristics of word class effects are also found. These findings are of great significance to L2 Chinese education of Yi students.

To investigate individual differences in creativity as measured with a complex problem-solving task, we developed a computational model of the remote associates test (RAT). For 50 years, the RAT has been used to measure creativity. Each RAT question presents three cue words that are linked by a fourth word, which is the correct answer. We hypothesized that individuals perform poorly on the RAT when they are biased to consider high-frequency candidate answers. To assess this hypothesis, we tested individuals with 48 RAT questions and required speeded responding to encourage guessing. Results supported our hypothesis. We generated a norm-based model of the RAT using a high-dimensional semantic space, and this model accurately identified correct answers. A frequency-biased model that included different levels of bias for highfrequency candidate answers explained variance for both correct and incorrect responses. Providing new insight into the nature of creativity, the model explains why some RAT questions are more difficult than others, and why some people perform better than others on the RAT.

We present a new Japanese dataset, Japanese Word Similarity and Association Norm (JWSAN), comprising human rating scores of similarity and association for 2145 word pairs, with a clear distinction between word similarity and word association. Computational models of human semantic memory or mental lexicon, such as distributed semantic models, must predict not only association but also similarity. People can distinguish between word similarity and association. However, although the SimLex-999 dataset is publicly available for English, there is no Japanese similarity dataset with a clear distinction between the two types of word relatedness. JWSAN is the first large Japanese dataset with similarity and association ratings, containing noun, verb, and adjective word pairs. It is also characterized by data collection from a sufficient number of age- and-gender-controlled assessors, with similarity and association ratings obtained via a web-based survey conducted of 6450 native speakers of Japanese. In addition, the effects of the gender and age of the raters were also examined; these factors were only given scant consideration in the past. This dataset can act as a benchmark for improving distributed semantic models in Japanese.

Purpose: This study uses projective techniques to explore how consumers perceive private labels and provides retailers with actionable findings for developing successful private label strategies. Design/Methodology: The research employed a qualitative design using two projective techniques, word association and a combined sentence completion and role-playing task, on a sample of 98 graduate students from the University of Zagreb. Findings: Projective techniques help uncover how consumers evaluate private labels by using a rational risk–reward analysis based on price and quality. Spontaneous associations confirm that price and affordability remain the primary mental triggers, but the decision to purchase is a value-driven substitution, frequently rationalized as receiving “equal quality at a lower price”. The study establishes a strong link between private labels and the retailer’s identity. Practical Implications: From a managerial perspective, the results indicate that retailers must move beyond simple low-price positioning and focus on communicating superior value and tangible savings. Managers should address quality polarization by actively improving product quality, cooperating with local suppliers, and using explicit quality-assurance claims to mitigate perceived risk. At the same time, they should recognize that confidence in private labels is fundamentally tied to the retailer’s image. Originality/Value: What is new in this study is the use of projective techniques in this context, which leads to several specific implications for retailers.

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.