Literature DB >> 18411545

Word associations: network and semantic properties.

Simon De Deyne1, Gert Storms.   

Abstract

A number of properties of word associations, generated in a continuous task, were investigated. First, we investigated the correspondence of word class in association cues and responses. Nouns were the modal word class response, regardless of the word class of the cue, indicating a dominant paradigmatic response style. Next, the word association data were used to build an associative network to investigate the centrality of nodes. The study of node centrality showed that central nodes in the network tended to be highly frequent and acquired early. Small-world properties of the association network were investigated and compared with a large English association network (Steyvers & Tenenbaum, 2005). Networks based on a multiple association procedure showed small-world properties despitebeing denser than networks based on a discrete task. Finally, a semantic taxonomy was used to investigate the composition of semantic types in association responses. The majority of responses were thematically related situation responses and entity responses referring to parts, shape, or color. Since the association task required multiple responses per cue, the interaction between generation position and semantic role could be investigated and discussed in the framework of recent theories of natural concept representations (Barsalou, Santos, Simmons, & Wilson, in press).

Entities:  

Mesh:

Year:  2008        PMID: 18411545     DOI: 10.3758/brm.40.1.213

Source DB:  PubMed          Journal:  Behav Res Methods        ISSN: 1554-351X


  29 in total

1.  Estimating semantic networks of groups and individuals from fluency data.

Authors:  Jeffrey C Zemla; Joseph L Austerweil
Journal:  Comput Brain Behav       Date:  2018-06-06

2.  How activation, entanglement, and searching a semantic network contribute to event memory.

Authors:  Douglas L Nelson; Kirsty Kitto; David Galea; Cathy L McEvoy; Peter D Bruza
Journal:  Mem Cognit       Date:  2013-08

3.  Semantic similarity between old and new items produces false alarms in recognition memory.

Authors:  Maria Montefinese; Gian Daniele Zannino; Ettore Ambrosini
Journal:  Psychol Res       Date:  2014-09-30

4.  The multiplex structure of the mental lexicon influences picture naming in people with aphasia.

Authors:  Nichol Castro; Massimo Stella
Journal:  J Complex Netw       Date:  2019-04-23

5.  Using free association networks to extract characteristic patterns of affect dynamics.

Authors:  Yaniv Dover; Zohar Moore
Journal:  Proc Math Phys Eng Sci       Date:  2020-04-15       Impact factor: 2.704

6.  Right temporal alpha oscillations as a neural mechanism for inhibiting obvious associations.

Authors:  Caroline Di Bernardi Luft; Ioanna Zioga; Nicholas M Thompson; Michael J Banissy; Joydeep Bhattacharya
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-12       Impact factor: 11.205

7.  Tarvajeh: Word Association Norms for Persian Words.

Authors:  Fatemeh Karimkhani; Hossein Rahmani; Arezoo Zare; Raana Sahebnassagh; Kiarash Aghakasiri
Journal:  J Psycholinguist Res       Date:  2021-01-04

8.  Not just semantics: strong frequency and weak cognate effects on semantic association in bilinguals.

Authors:  Inés Antón-Méndez; Tamar H Gollan
Journal:  Mem Cognit       Date:  2010-09

9.  Global and local features of semantic networks: evidence from the Hebrew mental lexicon.

Authors:  Yoed N Kenett; Dror Y Kenett; Eshel Ben-Jacob; Miriam Faust
Journal:  PLoS One       Date:  2011-08-24       Impact factor: 3.240

10.  Linking concepts in the ecology and evolution of invasive plants: network analysis shows what has been most studied and identifies knowledge gaps.

Authors:  Sonia Vanderhoeven; Cynthia S Brown; Carolyn K Tepolt; Neil D Tsutsui; Valérie Vanparys; Sheryl Atkinson; Grégory Mahy; Arnaud Monty
Journal:  Evol Appl       Date:  2010-03       Impact factor: 5.183

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.