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This paper presents results from a study exploring representations of “happiness” and “unhappiness.” Word associations with these concepts were produced by 16–18 and 29–34-year-old women from Finland, the country that the United Nation’s World Happiness Report has ranked the “happiest” in the world. Correspondence Analysis (CA) and Hierarchical Cluster Analysis show that participants in both age groups share three clusters of words associated with “happiness”: Tangible happiness, Affective happiness and Serene happiness. We noted more differences in the associations with “unhappiness,” for which the two groups share only two clusters: Loss and Everyday problems. A distinct third cluster, Affective unhappiness, emerged for the younger women, whereas older women’s associations are further differentiated into a more complex structure, including two more clusters: Dejection and Apprehension. Additionally, CA shows that in both age groups, self-reported happiness levels do not discriminate which words are associated with happiness and unhappiness. Finally, qualitative content analysis of a questionnaire item investigating how to reach complete happiness suggested that there are three recurring answer types: happiness can be improved through external changes, internal changes, or not at all because complete/permanent happiness does not exist. The study provides a methodological design which, unlike most happiness studies, allows participants the freedom to bring up the meaning of happiness and unhappiness. Thus, the study constitutes a contribution to a more nuanced understanding of happiness.

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.

In many classes, students are faced with the daunting task of remembering a lot of terms or structures in a relatively short period of time. Though there is much to memorize, students may not be aware of the many mnemonic mechanisms that can help them make quick and lasting memories. This article describes three such mechanisms: word associations, visual images, and stories. Examples of how these mechanisms can be applied, either individually or in combination, are provided in the context of teaching human anatomy. Whether used by teacher or student, these mechanisms can be incorporated into a class, providing fun and effective ways to both teach and learn.

Word associations have been used widely in psychology, but the validity of their application strongly depends on the number of cues included in the study and the extent to which they probe all associations known by an individual. In this work, we address both issues by introducing a new English word association dataset. We describe the collection of word associations for over 12,000 cue words, currently the largest such English-language resource in the world. Our procedure allowed subjects to provide multiple responses for each cue, which permits us to measure weak associations. We evaluate the utility of the dataset in several different contexts, including lexical decision and semantic categorization. We also show that measures based on a mechanism of spreading activation derived from this new resource are highly predictive of direct judgments of similarity. Finally, a comparison with existing English word association sets further highlights systematic improvements provided through these new norms. ispartof: BEHAVIOR RESEARCH METHODS vol:51 issue:3 pages:987-1006 ispartof: location:United States status: published

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. ispartof: Behavior Research Methods vol:48 issue:4 pages:1644-1652 ispartof: location:United States status: published

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. La similitud, que desempeña un papel clave en campos como la ciencia cognitiva, la psicolingüística y el procesamiento del lenguaje natural, es un concepto amplio y multifacético. En este trabajo analizamos cómo dos enfoques que pertenecen a diferentes perspectivas, la visión del corpus y la visión psicolingüística, articulan la semejanza entre los sentidos verbales en español. Específicamente, comparamos la similitud entre los sentidos verbales basados en su estructura argumental, que se capta a través de roles semánticos, con su similitud definida por las asociaciones de palabras. Abordamos la cuestión de si la estructura del argumento verbal, que refleja la expresión de los acontecimientos, y las asociaciones de palabras, que están relacionadas con la organización de los hablantes del léxico mental, forman similitud entre los verbos de una manera congruente, un tema que no ha sido explorado previamente. Mientras que encontramos correlaciones significativas entre las similitudes de los sentidos verbales obtenidas de estos dos enfoques, nuestros hallazgos también resaltan algunas discrepancias entre ellos y la importancia del grado de abstracción de la anotación del corpus y las representaciones psicolingüísticas. La similitud, que exerceix un paper clau en camps com la ciència cognitiva, la psicolingüística i el processament del llenguatge natural, és un concepte ampli i multifacètic. En aquest treball analitzem com dos enfocaments que pertanyen a diferents perspectives, la visió del corpus i la visió psicolingüística, articulen la semblança entre els sentits verbals en espanyol. Específicament, comparem la similitud entre els sentits verbals basats en la seva estructura argumental, que es capta a través de rols semàntics, amb la seva similitud definida per les associacions de paraules. Abordem la qüestió de si l'estructura de l'argument verbal, que reflecteix l'expressió dels esdeveniments, i les associacions de paraules, que estan relacionades amb l'organització dels parlants del lèxic mental, formen similitud entre els verbs d'una manera congruent, un tema que no ha estat explorat prèviament. Mentre que trobem correlacions significatives entre les similituds dels sentits verbals obtingudes d'aquests dos enfocaments, les nostres troballes també ressalten algunes discrepàncies entre ells i la importància del grau d'abstracció de l'anotació del corpus i les representacions psicolingüístiques.

L’article présente le projet de création d’un nouvel outil lexicographique multilingue, « le dictionnaire usuel multilingue des bionymes », porté par une équipe de chercheurs russes et qui permettra de réunir les associations et les comparaisons évoquées spontanément par un substantif désignant un animal ou une plante, ainsi que des phrases contenant ce mot et des définitions. L’article présente la phase préparatoire du projet commencé en 2013 et qui permettra de compléter par les productions de locuteurs naïfs de la langue les descriptions lexicales élaborées par les lexicographes professionnels. The paper presents the project of a new lexicographic tool, the “Common Multilingual Dictionary of Bionyms”, led by a team of Russian linguists. In this dictionary we collect not only spontan associations and comparisons given for a noun (meaning an animal or a plant), but also phrases with this word and a definitions. The paper exposes the initial stage of the project, which begun in 2013 and will allow to complete lexicographic descriptions made by professionals with the results of the metalinguistic activity of naïve language users.

Previous studies have shown that self-generated information is better remembered than information that has been read passively. To further examine this subsequent memory effect, we investigated the effect of five different linguistic relationships on memory encoding. Ninety subjects were administered 60 paired associates during an encoding condition: 30 of the second words from each pair were to be read aloud and 30 were to be self-generated from clues as to the correct word. Word pairs were composed of five linguistic relationships: category, rhyme, opposite, synonym, and association. Subsequently, subjects were presented with the words that were read or generated in a forced recognition memory task. Overall, reading accuracy was higher than generation accuracy during the encoding phase (all P < 0.001). During the recognition phase, subjects' performance was better on the generate than on the read conditions for opposite, synonym, category, and association relationships (all P < 0.05), with no difference in the rhyme relationship. These results confirm previous findings that self-generated information is better remembered than read information and suggest that this advantage may be mediated by using opposite, synonym, category, and association relationships, while rhyme relationship may not extend such an advantage. These findings may have implications for future studies of memory interventions in healthy controls and subjects with cognitive impairments.

Many existing information retrieval models do not explicitly take into account in- formation about word associations. Our approach makes use of rst and second order relationships found in natural language, known as syntagmatic and paradigmatic associ- ations, respectively. This is achieved by using a formal model of word meaning within the query expansion process. On ad hoc retrieval, our approach achieves statistically sig- ni cant improvements in MAP (0.158) and P@20 (0.396) over our baseline model. The ERR@20 and nDCG@20 of our system was 0.249 and 0.192 respectively. Our results and discussion suggest that information about both syntagamtic and paradigmatic associa- tions can assist with improving retrieval eectiveness on ad hoc retrieval.

This paper develops a framework for classifying term dependencies in query expansion with respect to the role terms play in structural linguistic associations. The framework is used to classify and compare the query expansion terms produced by the unigram and positional relevance models. As the unigram relevance model does not explicitly model term dependencies in its estimation process it is often thought to ignore dependencies that exist between words in natural language. The framework presented in this paper is underpinned by two types of linguistic association, namely syntagmatic and paradigmatic associations. It was found that syntagmatic associations were a more prevalent form of linguistic association used in query expansion. Paradoxically, it was the unigram model that exhibited this association more than the positional relevance model. This surprising finding has two potential implications for information retrieval models: (1) if linguistic associations underpin query expansion, then a probabilistic term dependence assumption based on position is inadequate for capturing them; (2) the unigram relevance model captures more term dependency information than its underlying theoretical model suggests, so its normative position as a baseline that ignores term dependencies should perhaps be reviewed.

This paper develops and evaluates an enhanced corpus based approach for semantic processing. Corpus based models that build representations of words directly from text do not require pre-existing linguistic knowledge, and have demonstrated psychologically relevant performance on a number of cognitive tasks. However, they have been criticised in the past for not incorporating sufficient structural information. Using ideas underpinning recent attempts to overcome this weakness, we develop an enhanced tensor encoding model to build representations of word meaning for semantic processing. Our enhanced model demonstrates superior performance when compared to a robust baseline model on a number of semantic processing tasks.

Marcel Neckar, Petr Bob Center for Neuropsychiatric Research of Traumatic Stress, Department of Psychiatry, First Faculty of Medicine, Charles University, Prague, Czech Republic Background: Synesthesia manifests as unusual associative connections that may cause intriguing experiences due to various cross-modal connections, for example, a sound may be experienced as color. Several findings indicate that temporal lobe seizures or seizure-like conditions and increased excitability may influence various unusual cross-sensory links and synesthetic experiences.Methods: In this context, the purpose of this study is to find relationships between word–color associations and psychopathological symptoms related to temporal lobe epilepsy and limbic irritability (Limbic System Checklist [LSCL-33]), symptoms of traumatic stress (Trauma Symptoms Checklist [TSC-40]), and depressive symptoms (Beck Depression Inventory [BDI-II]) in 71 participants (mean age =25.23 years) recruited from the general population. The whole sample included two subgroups according to levels of psychosensory and affective symptoms related to temporal epilepsy measured by LSCL-33.Results: The results in both subgroups indicate specific words correlated with the scores of psychopathological symptoms measured by LSCL-33, BDI-II, and TSC-40. Significant Spearman correlations have been predominantly found in the subgroup of participants with higher levels of LSCL-33.Conclusion: The results indicate a specific synesthetic-like mechanism in association processes that reflects psychopathological symptoms related to increased temporo-limbic excitability. Keywords: word associations, colors, stress, synesthesia, temporal lobe epilepsy, limbic irritability

The paper comprises basic findings and conclusions reached by studying frequency glossaries, development of speech and language behavior in education, teaching of foreign languages, culture of speech communication. Basic theoretical and empirical investigations of language in education using interdisciplinary approach are provided. Investigations founded on (a) establishing age-based abilities for mastering language components and its structures, and (b) effects of exercises conducted for developing language abilities in students, depending on their age are surveyed. The investigations are to point to the development of child speech in general to establishing speech norms as well as to deviations in oral and written expression. Pedagogic and psychological value of the findings obtained is in developing learning strategies and cognitive styles, level of concepts acquired, developing of student creative thinking. The overall development of speech and language in students is considered within communication processes and their socialization. Rad sadrži osnovne nalaze i zaključke proučavanja sledećih tema frekvencijski rečnici, razvitak dečjeg govornog i jezičkog ponašanja u obrazovanju, nastava stranih jezika, kultura govorne komunikacije. Prikazana su fundamentalna teorijska i empirijska istraživanja jezika u obrazovanju sa interdisciplinarnim pristupom. Dat je pregled istraživanja zasnovanih na (a) utvrđivanju uzrasnih mogućnosti za savlađivanje jezičke građe i njene strukture i (b) efekata urađenih vežbi za razvoj jezičkih sposobnosti učenika zavisno od uzrasta. Značaj ovih istraživanja je ukazivanje na razvitak dečjeg govora uopšte, utvrđivanju govornih normi, kao i na devijacije u usmenom i pismenom izražavanju. Pedagoška i psihološka vrednost dobijenih nalaza je u razvijanju strategija učenja i kognitivnih stilova stepena usvojenosti pojmova, razvoja kreativnog mišljenja učenika. Čitav ovaj razvoj jezika i govora učenika razmatra se u procesima komunikacije i njihove socijalizacije.

We have developed tools and applied methods for automated identification of potential news from textual data for an automated news search system called Software Newsroom. The purpose of the tools is to analyze data collected from the internet and to identify information that has a high probability of containing new information. The identified information is summarized in order to help understanding the semantic contents of the data, and to assist the news editing process. It has been demonstrated that words with a certain set of syntactic and semantic properties are effective when building topic models for English. We demonstrate that words with the same properties in Finnish are useful as well. Extracting such words requires knowledge about the special characteristics of the Finnish language, which are taken into account in our analysis. Two different methodological approaches have been applied for the news search. One of the methods is based on topic analysis and it applies Multinomial Principal Component Analysis (MPCA) for topic model creation and data profiling. The second method is based on word association analysis and applies the log-likelihood ratio (LLR). For the topic mining, we have created English and Finnish language corpora from Wikipedia and Finnish corpora from several Finnish news archives and we have used bag-of-words presentations of these corpora as training data for the topic model. We have performed topic analysis experiments with both the training data itself and with arbitrary text parsed from internet sources. The results suggest that the effectiveness of news search strongly depends on the quality of the training data and its linguistic analysis. In the association analysis, we use a combined methodology for detecting novel word associations in the text. For detecting novel associations we use the background corpus from which we extract common word associations. In parallel, we collect the statistics of word co-occurrences from the documents of interest and search for associations with larger likelihood in these documents than in the background. We have demonstrated the applicability of these methods for Software Newsroom. The results indicate that the background-foreground model has significant potential in news search. The experiments also indicate great promise in employing background-foreground word associations for other applications. A combined application of the two methods is planned as well as the application of the methods on social media using a pre-translator of social media language.