| The “Small World of Words” English word association norms for over 12,000 cue words S De Deyne, DJ Navarro, A Perfors, M Brysbaert, G Storms Behavior research methods 51, 987-1006, 2019 | 363 | 2019 |
| Word associations: Network and semantic properties S De Deyne, G Storms Behavior research methods 40 (1), 213-231, 2008 | 348 | 2008 |
| Age-of-acquisition effects in semantic processing tasks M Brysbaert, I Van Wijnendaele, S De Deyne Acta psychologica 104 (2), 215-226, 2000 | 336 | 2000 |
| Better explanations of lexical and semantic cognition using networks derived from continued rather than single-word associations S De Deyne, DJ Navarro, G Storms Behavior research methods 45, 480-498, 2013 | 262 | 2013 |
| Norms of age of acquisition and concreteness for 30,000 Dutch words M Brysbaert, M Stevens, S De Deyne, W Voorspoels, G Storms Acta psychologica 150, 80-84, 2014 | 231 | 2014 |
| Word associations: Norms for 1,424 Dutch words in a continuous task S De Deyne, G Storms Behavior research methods 40 (1), 198-205, 2008 | 211 | 2008 |
| Exemplar by feature applicability matrices and other Dutch normative data for semantic concepts S De Deyne, S Verheyen, E Ameel, W Vanpaemel, MJ Dry, W Voorspoels, ... Behavior research methods 40, 1030-1048, 2008 | 167 | 2008 |
| Similarity of fMRI activity patterns in left perirhinal cortex reflects semantic similarity between words R Bruffaerts, P Dupont, R Peeters, S De Deyne, G Storms, ... Journal of Neuroscience 33 (47), 18597-18607, 2013 | 163 | 2013 |
| New perspectives on the aging lexicon DU Wulff, S De Deyne, MN Jones, R Mata Trends in cognitive sciences 23 (8), 686-698, 2019 | 134 | 2019 |
| Dutch norm data for 13 semantic categories and 338 exemplars W Ruts, S De Deyne, E Ameel, W Vanpaemel, T Verbeemen, G Storms Behavior Research Methods, Instruments, & Computers 36 (3), 506-515, 2004 | 120 | 2004 |
| Quantifying the structure of free association networks across the life span. H Dubossarsky, S De Deyne, TT Hills Developmental psychology 53 (8), 1560, 2017 | 113 | 2017 |
| Large-scale network representations of semantics in the mental lexicon S De Deyne, YN Kenett, D Anaki, M Faust Big data in cognitive science, 183-189, 2016 | 107 | 2016 |
| The influence of working memory load on semantic priming. T Heyman, B Van Rensbergen, G Storms, KA Hutchison, S De Deyne Journal of Experimental Psychology: Learning, Memory, and Cognition 41 (3), 911, 2015 | 100 | 2015 |
| Predicting human similarity judgments with distributional models: The value of word associations. S De Deyne, A Perfors, DJ Navarro Proceedings of COLING 2016, the 26th international conference on …, 2016 | 95 | 2016 |
| Emotions in “the world”: cultural practices, products, and meanings of anger and shame in two individualist cultures M Boiger, SD Deyne, B Mesquita Frontiers in psychology 4, 867, 2013 | 95 | 2013 |
| Predicting lexical norms: A comparison between a word association model and text-based word co-occurrence models H Vankrunkelsven, S Verheyen, G Storms, S De Deyne Journal of cognition 1 (1), 2018 | 94 | 2018 |
| Structure at every scale: A semantic network account of the similarities between unrelated concepts. S De Deyne, DJ Navarro, A Perfors, G Storms Journal of Experimental Psychology: General 145 (9), 1228, 2016 | 93 | 2016 |
| #lockdown: Network-Enhanced Emotional Profiling in the Time of COVID-19 M Stella, V Restocchi, S De Deyne Big Data and Cognitive Computing 4 (2), 14, 2020 | 75 | 2020 |
| Left perirhinal cortex codes for similarity in meaning between written words: comparison with auditory word input AG Liuzzi, R Bruffaerts, P Dupont, K Adamczuk, R Peeters, S De Deyne, ... Neuropsychologia 76, 4-16, 2015 | 69 | 2015 |
| Structure and organization of the mental lexicon: A network approach derived from syntactic dependency relations and word associations S De Deyne, S Verheyen, G Storms Towards a theoretical framework for analyzing complex linguistic networks, 47-79, 2016 | 67 | 2016 |
gert stormspsychologie, universiteit leuven在 kuleuven.be 的电子邮件经过验证
