Semantic distance norms computed from an electronic dictionary (WordNet)

WordNet, an electronic dictionary (or lexical database), is a valuable resource for computational and cognitive scientists. Recent work on the computing of semantic distances among nodes (synsets) in WordNet has made it possible to build a large database of semantic distances for use in selecting word pairs for psychological research. The database now contains nearly 50,000 pairs of words that have values for semantic distance, associative strength, and similarity based on co-occurrence. Semantic distance was found to correlate weakly with these other measures but to correlate more strongly with another measure of semantic relatedness, featural similarity. Hierarchical clustering analysis suggested that the knowledge structure underlying semantic distance is similar in gross form to that underlying featural similarity. In experiments in which semantic similarity ratings were used, human participants were able to discriminate semantic distance. Thus, semantic distance as derived from WordNet appears distinct from other measures of word pair relatedness and is psychologically functional. This database may be downloaded fromwww.psychonomic.org/archive/.     

Psycholinguistic measures for German verb pairs: Semantic transparency,semantic relatedness,verb family size,and age of reading acquisition

A central issue in visual and spoken word recognition is the lexical representation of complex words—in particular, whether the lexical representation of complex words depends on semantic transparency: Is a complex verb like understand lexically represented as a whole word or via its base stand, given that its meaning is not transparent from the meanings of its parts? To study this issue, a number of stimulus characteristics are of interest that are not yet available in public databases of German. This article provides semantic association ratings, lexical paraphrases, and vector-based similarity measures for German verbs, measuring (a) the semantic transparency between 1,259 complex verbs and their bases, (b) the semantic relatedness between 1,109 verb pairs with 432 different bases, and (c) the vector-based similarity measures of 846 verb pairs. Additionally, we include the verb regularity of all verbs and two counts of verb family size for 184 base verbs, as well as estimates of age of acquisition and age of reading for 200 verbs. Together with lemma and type frequencies from public lexical databases, all measures can be downloaded along with this article. Statistical analyses indicate that verb family size, morphological complexity, frequency, and verb regularity affect the semantic transparency and relatedness ratings as well as the age of acquisition estimates, indicating that these are relevant variables in psycholinguistic experiments. Although lexical paraphrases, vector-based similarity measures, and semantic association ratings may deliver complementary information, the interrater reliability of the semantic association ratings for each verb pair provides valuable information when selecting stimuli for psycholinguistic experiments.     

Scope of Semantic Activation and Innovative Thinking in College Students with ADHD

Adults with attention-deficit/hyperactivity disorder (ADHD) show high divergent thinking on standardized laboratory measures. This study assessed innovative thinking in adults with ADHD using a realistic task and investigated a possible cognitive mechanism for ADHD-related advantages in innovative thinking. College students with and without ADHD (n = 30 per group) completed a cell-phone feature invention task and word association task. Latent semantic analysis was used to measure semantic distance within cue-associate pairs on the word association task. Compared to non-ADHD peers, students with ADHD scored higher in originality, novelty, and flexibility on the cell phone task, and produced associates of lower semantic relatedness on the word association task. Tests of statistical mediation confirmed that the higher flexibility of the ADHD group was explained by semantic distance within cue-associate pairs on the word association task. Results support the possibility that ADHD is positively associated with specific aspects of innovative thinking, which may in part be attributable to a wide scope of semantic activation.     

Examining the role of word identification in synonymy judgment

This paper examines the role of word identification in semantic judgment tasks. We argue that word-identification processes can substantially alter the functional properties of semantic judgment tasks. We investigate this empirically by examining the effects of semantic relatedness and relatedness proportion on synonymy judgments of non-synonym pairs. The results demonstrate that semantic relatedness slows synonymy judgments for non-synonym pairs when the relatedness proportion is low, but speeds them when the relatedness proportion is high. The former effect is a replication of traditional findings, while the latter effect reverses these findings. We explain these results by hypothesizing that increasing the relatedness proportion increases the beneficial effects of semantic relatedness in word identification, and this produces the reversal of traditional findings. We close by emphasizing that models of semantic judgment tasks can become more comprehensive by focusing on word identification.     

The relation between body semantics and spatial body representations

The present study addressed the relation between body semantics (i.e. semantic knowledge about the human body) and spatial body representations, by presenting participants with word pairs, one below the other, referring to body parts. The spatial position of the word pairs could be congruent (e.g. EYE / MOUTH) or incongruent (MOUTH / EYE) with respect to the spatial position of the words’ referents. In addition, the spatial distance between the words’ referents was varied, resulting in word pairs referring to body parts that are close (e.g. EYE / MOUTH) or far in space (e.g. EYE / FOOT). A spatial congruency effect was observed when subjects made an iconicity judgment (Experiments 2 and 3) but not when making a semantic relatedness judgment (Experiment 1). In addition, when making a semantic relatedness judgment (Experiment 1) reaction times increased with increased distance between the body parts but when making an iconicity judgment (Experiments 2 and 3) reaction times decreased with increased distance. These findings suggest that the processing of body-semantics results in the activation of a detailed visuo-spatial body representation that is modulated by the specific task requirements. We discuss these new data with respect to theories of embodied cognition and body semantics.     

Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations

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.     

Polysemy and the subjective lexicon: Semantic relatedness and the salience of intraword senses

Subjective perceptions of the senses of polysemous English words are collected in questionnaire studies and the effects of variability in semantic distances among these senses are examined in an experiment. In the first of two questionnaire studies, native speakers produce meanings for 175 polysemous words; from their responses, the most frequently produced meaning for each word is identified as its dominant sense. In a second questionnaire, independent subjects rate the semantic relatedness between the dominant meaning and the other senses generated for each word in the first study. Relatedness measures vary, raising the possibility that polysemous words vary in terms of the salience of their different senses in different contexts. This is confirmed in an experiment showing that salience ratings are influenced by the interacting factors of sentential context, extent of relatedness of the senses, and the dominance status of the senses.This research was supported by a grant from the Special Research Fund, University of Western Australia, to Kevin Durkin.     

Semantic priming effects on picture and word processing

The effects of semantic priming on picture and word processing were assessed under conditions in which subjects were required simply to identify stimuli (label pictures or read words) as rapidly as possible. Stimuli were presented in pairs (a prime followed by a target), with half of the pairs containing members of the same semantic category and half containing unrelated concepts. Semantic relatedness was found to facilitate the identification of both pictures (Experiment 1) and words (Experiment 2), and obtained interactions of semantic relatedness and stimulus quality in both experiments suggested that semantic priming affects the initial encoding of both types of stimuli. In Experiment 3, subjects received pairs of pictures, pairs of words, and mixed pairs composed of a picture and a word or of a word and a picture. Significant priming effects were obtained on mixed as well as unmixed pairs, supporting the assumption that pictures and words access semantic information from a common semantic store. Of primary interest was the significantly greater priming obtained in picture-picture pairs than in word-word or mixed pairs. This suggests that, in addition to priming that is mediated by the semantic system, priming may occur in picture-picture pairs that results from the overlap in visual features common to the pictorial representations of objects from the same semantic category.     

Examining lateralized semantic access using pictures

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness judgment in response to sequentially presented pictures. We found that when pictures are presented to the right hemisphere responses are generally more accurate than the left hemisphere for semantic relatedness judgments for picture pairs. Furthermore, consistent with earlier DVF studies employing words, we conclude that the RH is better at accessing or maintaining access to information that has a weak or more remote semantic relationship. We also found evidence of faster access for pictures presented to the LH in the strongly-related condition. Overall, these results are consistent with earlier DVF word studies that argue that the cerebral hemispheres each play an important and separable role during semantic retrieval.     

An Attractor Model of Lexical Conceptual Processing: Simulating Semantic Priming

An attractor network was trained to compute from word form to semantic representations that were based on subject-generated features. The model was driven largely by higher-order semantic structure. The network simulated two recent experiments that employed items included in its training set (McRae and Boisvert, 1998). In Simulation 1, short stimulus onset asynchrony priming was demonstrated for semantically similar items. Simulation 2 reproduced subtle effects obtained by varying degree of similarity. Two predictions from the model were then tested on human subjects. In Simulation 3 and Experiment 1, the items from Simulation 1 were reversed, and both the network and subjects showed minimally different priming effects in the two directions. In Experiment 2, consistent with attractor networks but contrary to a key aspect of hierarchical spreading activation accounts priming was determined by featural similarity rather than shared superordinate category. It is concluded that semantic-similarity priming is due to featural overlap that is a natural consequence of distributed representations of word meaning.     

Connectivity among semantic associates: an fMRI study of semantic priming

Semantic priming refers to a reduction in the reaction time to identify or make a judgment about a stimulus that has been immediately preceded by a semantically related word or picture and is thought to result from a partial overlap in the semantic associates of the two words. A semantic priming lexical decision task using spoken words was presented in event-related fMRI and behavioral paradigms. Word pairs varied in terms of semantic relatedness and the connectivity between associates. Thirteen right-handed subjects underwent fMRI imaging and 10 additional subjects were tested in a behavioral version of the semantic priming task. It was hypothesized priming would be greatest, reaction time fastest, and cortical activation reduced the most for related word pairs of high connectivity, followed by related word pairs of low connectivity, and then by unrelated word pairs. Behavioral and fMRI results confirmed these predictions. fMRI activity located primarily in bilateral posterior superior and middle temporal regions showed modulation by connectivity and relatedness. The results suggest that these regions are involved in semantic processing.     

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.     

Gradients versus dichotomies: How strength of semantic context influences event-related potentials and lexical decision times

In experiments devoted to word recognition and/or language comprehension, reaction time in the lexical decision task is perhaps the most commonly used behavioral dependent measure, and the amplitude of the N400 component of the event-related potential (ERP) is the most common neural measure. Both are sensitive to multiple factors, including frequency of usage, orthographic similarity to other words, concreteness of word meaning, and preceding semantic context. All of these factors vary continuously. Published results have shown that both lexical decision times and N400 amplitudes show graded responses to graded changes of word frequency and orthographic similarity, but a puzzling discrepancy in their responsivity to the strength of a semantic context has received little attention. In three experiments, we presented pairs of words varying in the strengths of their semantic relationships, as well as unrelated pairs. In all three experiments, N400 amplitudes showed a gradient from unrelated to weakly associated to strongly associated target words, whereas lexical decision times showed a binary division rather than a gradient across strengths of relationship. This pattern of results suggests that semantic context effects in lexical decision and ERP measures arise from fundamentally different processes.     

Triadic decision making in lexical memory

Word and category recognition was investigated in the context of other stimuli, where the semantic distance relationships among the stimuli were derived from multidimensional scaling. On each trial, three horizontal strings of letters were presented. In the word condition, a positive response was required when the three strings formed three words; in the category condition, a positive response was required when the three strings formed words belonging to the same category. The results indicated that: (a) category decisions take about 150-200 msec longer than do word decisions, (b) word decisions are facilitated by a common categorical membership but semantic distances within the category are relatively unimportant, and (c)within-category semantic distances systematically altered response time for the category condition. It was hypothesized that semantic distance relationships may be sensitized for categorical decisions, but that only large semantic distances function effectively for word decisions.     

Abstract Conceptual Feature Ratings Predict Gaze Within Written Word Arrays: Evidence From a Visual Wor(l)d Paradigm

The Abstract Conceptual Feature (ACF) framework predicts that word meaning is represented within a high‐dimensional semantic space bounded by weighted contributions of perceptual, affective, and encyclopedic information. The ACF, like latent semantic analysis, is amenable to distance metrics between any two words. We applied predictions of the ACF framework to abstract words using eyetracking via an adaptation of the classical “visual word paradigm” (VWP). Healthy adults (n = 20) selected the lexical item most related to a probe word in a 4‐item written word array comprising the target and three distractors. The relation between the probe and each of the four words was determined using the semantic distance metrics derived from ACF ratings. Eye movement data indicated that the word that was most semantically related to the probe received more and longer fixations relative to distractors. Importantly, in sets where participants did not provide an overt behavioral response, the fixation rates were nonetheless significantly higher for targets than distractors, closely resembling trials where an expected response was given. Furthermore, ACF ratings which are based on individual words predicted eye fixation metrics of probe‐target similarity at least as well as latent semantic analysis ratings which are based on word co‐occurrence. The results provide further validation of Euclidean distance metrics derived from ACF ratings as a measure of one facet of the semantic relatedness of abstract words and suggest that they represent a reasonable approximation of the organization of abstract conceptual space. The data are also compatible with the broad notion that multiple sources of information (not restricted to sensorimotor and emotion information) shape the organization of abstract concepts. While the adapted “VWP” is potentially a more metacognitive task than the classical visual world paradigm, we argue that it offers potential utility for studying abstract word comprehension.     

Similarity Judgment Within and Across Categories: A Comprehensive Model Comparison

Similarity is one of the most important relations humans perceive, arguably subserving category learning and categorization, generalization and discrimination, judgment and decision making, and other cognitive functions. Researchers have proposed a wide range of representations and metrics that could be at play in similarity judgment, yet have not comprehensively compared the power of these representations and metrics for predicting similarity within and across different semantic categories. We performed such a comparison by pairing nine prominent vector semantic representations with seven established similarity metrics that could operate on these representations, as well as supervised methods for dimensional weighting in the similarity function. This approach yields a factorial model structure with 126 distinct representation-metric pairs, which we tested on a novel dataset of similarity judgments between pairs of cohyponymic words in eight categories. We found that cosine similarity and Pearson correlation were the overall best performing unweighted similarity functions, and that word vectors derived from free association norms often outperformed word vectors derived from text (including those specialized for similarity). Importantly, models that used human similarity judgments to learn category-specific weights on dimensions yielded substantially better predictions than all unweighted approaches across all types of similarity functions and representations, although dimension weights did not generalize well across semantic categories, suggesting strong category context effects in similarity judgment. We discuss implications of these results for cognitive modeling and natural language processing, as well as for theories of the representations and metrics involved in similarity.     

Monotone mapping of similarities into a general metric space

A method of “maximum variance nondimensional scaling” is described and tested that transforms similarity measures into distances that meet just three conditions: (C1) they exactly satisfy the metric axioms, (C2) they are, as nearly as possible, monotonically related to the similarity measures, (C3) they have maximum variance possible under the two preceding conditions. By achieving an appropriate balance between the last two conditions, one can determine the true underlying distances and the form of the unknown monotone function relating the similarity measures to those distances without assuming that the underlying space has any particular Euclidean, Minkowskian, or even dimensional strucutre. The method appears to have potential applications, e.g., to studies of stimulus generalization and the structure and processing of semantic information.     

Semantic interference in language production is due to graded similarity,not response relevance

There is an ongoing debate on the question whether semantic interference effects in language production reflect competitive processes at the level of lexical selection or whether they reflect a post-lexical bottleneck, occupied in particular by response-relevant distractor words. To disentangle item-inherent categorical relatedness and task-related response relevance effects, we combined the picture–word interference task with the conditional naming paradigm in an orthogonal design, varying categorical relatedness and task-related response relevance independent of each other. Participants were instructed to name only objects that are typically seen in or on the water (e.g. canoe) and refrain from naming objects that are typically located outside the water (e.g. bike), and vice versa. Semantic relatedness and the response relevance of superimposed distractor words were manipulated orthogonally. The pattern of results revealed no evidence for response relevance as a major source of semantic interference effects in the PWI paradigm. In contrast, our data demonstrate that semantic similarity beyond categorical relations is critical for interference effects to be observed. Together, these findings provide support for the assumption that lexical selection is competitive and that semantic interference effects in the PWI paradigm reflect this competition.     

Latent structure in measures of associative,semantic, and thematic knowledge

There has been much debate about the relation between knowledge for meaning (semantic memory) and knowledge for words in context (associative memory). Many measures of that knowledge exist, but do they all measure the same thing? In this study, scaling, clustering, and factor-analytic techniques were used to reveal the structure underlying 13 variables. Semantic similarity determined from lexicographic measures is shown to be separable from the associative strength determined from word association norms, and these semantic and associative measures are in turn separable from abstract representations derived from computational analyses of large bodies of text. The three-factor structure is at odds with traditional views of word knowledge. The expression of long-term knowledge about words and the concepts they represent may be better viewed in terms of associative, semantic, and thematic information.     

Discriminating Semantic from Episodic Relatedness in Young and Older Adults

ABSTRACT

The ability of young (aged 18–30) and older (aged 60–80) adults to discriminate pre-experimental (semantic) from experimental (episodic) associations was examined. Participants studied a list containing semantically related and unrelated word pairs and then made either associative recognition (Experiments 1a and b) or semantic relatedness (Experiment 2) judgments at various response deadlines. For associative recognition judgments, both young and older adults benefited from semantic relatedness, leading to more hits for related than unrelated pairs, and at the long response deadline, older adults' performance on those pairs matched that of young participants. Also, both young and older adults demonstrated superior discrimination for unrelated lures whose members had originally been studied in related pairs – evidence for recall-to-reject processing in both age groups. In making semantic relatedness judgments, both young and older adults showed an episodic priming effect. When older adults can rely on long-standing associations, their performance resembles that of young adults – both in associative recognition and in episodic priming.