Core features: measures and characterization for different languages

According to the feature-based view of semantic representation, concepts can be represented as distributed networks of semantic features, which contribute with different weights to determine the overall meaning of a concept. The study of semantic features, typically collected in property generation tasks, is enriched with measures indicating the informativeness and distinctiveness of a given feature for the related concepts. However, while these measures have been provided in several languages (e.g. Italian, Spanish and English), they have hardly been applied comparatively across languages. The purpose of this paper is to investigate language-related differences and similarities emerging from the semantic representation of aggregated core features. Features with higher salience for a set of concrete concepts are identified and described in terms of their feature type. Then, comparisons are made between domains (natural vs. artefacts) and languages (Italian, Spanish and English) and descriptive statistics are provided. These results show that the characterization of concrete concepts is overall fairly stable across languages, although interesting cross-linguistic differences emerged. We will discuss the implications of our findings in relation to the theoretical paradigm of semantic feature norms, as well as in relation to speakers’ mutual understanding in multilingual settings.

[1]  S. Thompson-Schill,et al.  Putting concepts into context , 2016, Psychonomic bulletin & review.

[2]  Michaël A. Stevens,et al.  Norms of age of acquisition and concreteness for 30,000 Dutch words. , 2014, Acta psychologica.

[3]  E. Ambrosini,et al.  The adaptation of the Affective Norms for English Words (ANEW) for Italian , 2014, Behavior research methods.

[4]  Alex Martin.  GRAPES—Grounding representations in action, perception, and emotion systems: How object properties and categories are represented in the human brain , 2015, Psychonomic Bulletin & Review.

[5]  Karin Ackermann,et al.  Categories and Concepts , 2003, Job 28. Cognition in Context.

[6]  Giuseppe Sartori,et al.  Feature type effects in semantic memory: An event related potentials study , 2005, Neuroscience Letters.

[7]  George S. Cree,et al.  Distinctive features hold a privileged status in the computation of word meaning: Implications for theories of semantic memory. , 2006, Journal of experimental psychology. Learning, memory, and cognition.

[8]  Maria Montefinese,et al.  A practical primer on processing semantic property norm data , 2019, Cognitive Processing.

[9]  Marc Brysbaert,et al.  The Whorfian hypothesis and numerical cognition: is `twenty-four' processed in the same way as `four-and-twenty'? , 1998, Cognition.

[10]  L. Tyler,et al.  Neural Basis of Semantic Memory: The conceptual structure account: A cognitive model of semantic memory and its neural instantiation , 2007 .

[11]  G. Vigliocco,et al.  Grammatical gender effects on cognition: implications for language learning and language use. , 2005, Journal of experimental psychology. General.

[12]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[13]  Jelena Havelka,et al.  Affective norms for 210 British English and Finnish nouns , 2010, Behavior research methods.

[14]  Marco Baroni,et al.  A set of semantic norms for German and Italian , 2011, Behavior research methods.

[15]  Lawrence W. Barsalou,et al.  Are Automatic Conceptual Cores the Gold Standard of Semantic Processing? The Context-Dependence of Spatial Meaning in Grounded Congruency Effects , 2015, Cogn. Sci..

[16]  G. Storms,et al.  Mind the generation gap: Differences between young and old in everyday lexical categories , 2018 .

[17]  E. Ambrosini,et al.  No grammatical gender effect on affective ratings: evidence from Italian and German languages , 2018, Cognition & emotion.

[18]  G. Sartori,et al.  Semantic Relevance and Semantic Disorders , 2004, Journal of Cognitive Neuroscience.

[19]  B. Mesquita,et al.  Adjustment to Chronic Diseases and Terminal Illness Health Psychology : Psychological Adjustment to Chronic Disease , 2006 .

[20]  G. Sartori,et al.  Semantic relevance best predicts normal and abnormal name retrieval , 2005, Neuropsychologia.

[21]  S. C. Johnson.  Hierarchical clustering schemes , 1967, Psychometrika.

[22]  Maria Montefinese,et al.  Semantic similarity between old and new items produces false alarms in recognition memory , 2015, Psychological research.

[23]  M. Piazza,et al.  The neuro-cognitive representations of symbols: the case of concrete words , 2017, Neuropsychologia.

[24]  Ken McRae,et al.  Category - Specific semantic deficits , 2008 .

[25]  M. Garrett,et al.  Representing the meanings of object and action words: The featural and unitary semantic space hypothesis , 2004, Cognitive Psychology.

[26]  Wolf Vanpaemel,et al.  Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts , 2008, Behavior research methods.

[27]  L. Tyler,et al.  Conceptual Structure , 2006 .

[28]  James L. McClelland,et al.  Concepts, Control, and Context: A Connectionist Account of Normal and Disordered Semantic Cognition , 2018, Psychological review.

[29]  D. Perani,et al.  Semantic feature degradation and naming performance. Evidence from neurodegenerative disorders , 2015, Brain and Language.

[30]  M. Ashcraft.  Property dominance and typicality effects in property statement verification , 1978 .

[31]  Erin M Buchanan,et al.  English semantic feature production norms: An extended database of 4436 concepts , 2019, Behavior research methods.

[32]  Alessandro Lenci,et al.  BLIND: a set of semantic feature norms from the congenitally blind , 2013, Behavior research methods.

[33]  D. Casasanto,et al.  Who's Afraid of the Big Bad Whorf? Crosslinguistic Differences in Temporal Language and Thought , 2008 .

[34]  J. Sims.  The Whorfian Hypothesis. , 1997 .

[35]  L. Barsalou,et al.  Perceptual simulation in conceptual combination: evidence from property generation. , 2009, Acta psychologica.

[36]  S. Levinson,et al.  LANGUAGE AND SPACE , 1996 .

[37]  Jeroen Geertzen,et al.  The Centre for Speech, Language and the Brain (CSLB) concept property norms , 2013, Behavior research methods.

[38]  Thomas T. Hills,et al.  Quantifying the Structure of Free Association Networks Across the Life Span , 2017, Developmental psychology.

[39]  Mauro Ursino,et al.  A feature-based neurocomputational model of semantic memory , 2018, Cognitive Neurodynamics.

[40]  M. L. Lambon Ralph,et al.  Prototypicality, distinctiveness, and intercorrelation: Analyses of the semantic attributes of living and nonliving concepts , 2001, Cognitive neuropsychology.

[41]  Stavroula Kousta,et al.  Toward a theory of semantic representation , 2009, Language and Cognition.

[42]  R. Sánchez-Casas,et al.  Semantic similarity: normative ratings for 185 Spanish noun triplets , 2014, Behavior Research Methods.

[43]  Erin M Buchanan,et al.  English semantic word-pair norms and a searchable Web portal for experimental stimulus creation , 2013, Behavior research methods.

[44]  Ettore Ambrosini,et al.  Semantic memory: A feature-based analysis and new norms for Italian , 2013, Behavior research methods.

[45]  Silvia P. Gennari,et al.  Knowing versus Naming: Similarity and the Linguistic Categorization of Artifacts , 1999 .

[46]  D. Vinson,et al.  Recognition memory and featural similarity between concepts: The pupil’s point of view , 2018, Biological Psychology.

[47]  Carlo Caltagirone,et al.  Analysis of the semantic representations of living and nonliving concepts: A normative study , 2006, Cognitive neuropsychology.

[48]  B. Bahrami,et al.  Coming of age: A review of embodiment and the neuroscience of semantics , 2012, Cortex.

[49]  Jun Ye,et al.  Cosine Measures of Linguistic Neutrosophic Numbers and Their Application in Multiple Attribute Group Decision-Making , 2017, Inf..

[50]  Marianna Bolognesi,et al.  Using semantic feature norms to investigate how the visual and verbal modes afford metaphor construction and expression* , 2016, Language and Cognition.

[51]  Adolfo M. García,et al.  Core Semantic Links or Lexical Associations: Assessing the Nature of Responses in Word Association Tasks , 2018, Journal of Psycholinguistic Research.

[52]  D. Slobin.  From “thought and language” to “thinking for speaking” , 1996 .

[53]  Jorge Vivas,et al.  Organización reticular de la memoria semántica. Natural Finder y Definition Finder, dos métodos informatizados para recuperar conocimiento Reticular organization of semantic memory. Natural and Finder Definition finder, two computerized methods for retrieving knowledge , 2014 .

[54]  D. Gentner,et al.  Language in Mind: Advances in the Study of Language and Thought , 2003 .

[55]  David P Vinson,et al.  Semantic feature production norms for a large set of objects and events , 2008, Behavior research methods.

[56]  Mark S. Seidenberg,et al.  Semantic feature production norms for a large set of living and nonliving things , 2005, Behavior research methods.

[57]  Silvia P. Gennari,et al.  Universality and language specificity in object naming , 2003 .

[58]  Carlo Caltagirone,et al.  The contribution of neurodegenerative diseases to the modelling of semantic memory: A new proposal and a review of the literature , 2015, Neuropsychologia.

[59]  Massimo Poesio,et al.  Strudel: A distributional semantic model based on properties and types , 2010 .

[60]  Michael C. Frank,et al.  Russian blues reveal effects of language on color discrimination , 2007, Proceedings of the National Academy of Sciences.

[61]  Massimo Poesio,et al.  Strudel: A Corpus-Based Semantic Model Based on Properties and Types , 2010, Cogn. Sci..

[62]  L. E. Bourne,et al.  Mathematical theory of concept identification. , 1959, Psychological review.

[63]  Wolf Vanpaemel,et al.  Dutch norm data for 13 semantic categories and 338 exemplars , 2004, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[64]  J. Vivas,et al.  Spanish semantic feature production norms for 400 concrete concepts , 2017, Behavior research methods.

[65]  Enrique Canessa,et al.  The role of variability in the property listing task , 2017, Behavior Research Methods.

[66]  E. Rosch,et al.  Family resemblances: Studies in the internal structure of categories , 1975, Cognitive Psychology.

[67]  E. Ambrosini,et al.  Semantic significance: a new measure of feature salience , 2014, Memory & cognition.

[68]  E. Warrington,et al.  Categories of knowledge. Further fractionations and an attempted integration. , 1987, Brain : a journal of neurology.

[69]  Ettore Ambrosini,et al.  Erratum to: Semantic memory: A feature-based analysis and new norms for Italian , 2013 .