Publications

Publications are organized according to different topics.

Publications on integrating individual and social attitude/belief dynamics

Galesic, M., Bruine de Bruin,  Dalege, J., W., Feld, S. L., Kreuter, F., Olsson, H., Prelec, D., Stein, D. L., & van der Does, T. (2021). Human social sensing is an untapped resource for computational social science. Nature, 595, 214–222.

  • This paper argues that utilizing knowledge of individuals about their social environments can improve models in computational social science.

Galesic, M., Olsson, H., Dalege, J., van der Does, T., & Stein, D. L. (2021). Integrating social and cognitive aspects of belief dynamics: Towards a unifying framework. Journal of the Royal Society Interface, 18, 20200857.

  • This paper develops a unifying framework of studying social and cognitive aspects of belief dynamics.

van der Maas, H. L. J., Dalege, J., & Waldorp, L. J. (2020). The polarization within and across individuals: The hierarchical Ising opinion model. Journal of Complex Networks, 8, cnaa010.

  • This paper implements our network theory of attitudes in an opinion model of social dynamics.

Publications on the network theory of attitudes 

Dalege, J., & van der Maas, H. L. J. (2020). Accurate by being noisy: A formal network model of implicit measures of attitudes. Social Cognition, 38, S26-S41.

  • This paper applies our network theory of attitudes to the implicit measurement of attitudes. 

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2019). A network perspective on attitude strength: Testing the connectivity hypothesisSocial Psychological and Personality Science, 10, 746-756.

  • This paper tests the central postulate of the CAN model that strong attitudes correspond to highly connected networks. 

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2018). The Attitudinal Entropy (AE) Framework as a General Theory of Individual AttitudesPsychological Inquiry, 29, 175-193.

  • This paper develops a general theory of individual attitudes by connecting attitude dynamics to principles from statistical mechanics.

Dalege, J., Borsboom, D., van Harreveld, F., Lunansky, G., & van der Maas, H. L. J. (2018). The Attitudinal Entropy (AE) framework: Clarifications, Extensions, and Future DirectionsPsychological Inquiry, 29, 218-228.

  • This paper addresses the commentaries on the AE framework paper.

Dalege, J., Borsboom, D., van Harreveld, F., Waldorp, L. J., & van der Maas, H. L. J. (2017). Network structure explains the impact of attitudes on voting decisions. Scientific Reports, 7, 4909.

  • This paper shows that the impact of attitudes on decisions depends on the connectivity of the attitude network, with central evaluative reactions having higher impact on decisions than peripheral evaluative reactions. 

Dalege, J., Borsboom, D., van Harreveld, F., van den Berg, H., Conner, M., & van der Maas, H. L. J. (2016). Toward a formalized account of attitudes: The Causal Attitude Network (CAN) model. Psychological Review, 123, 2-22.

  • This paper introduces the Causal Attitude Network (CAN) model and shows that it provides a formalized measurement model of attitudes.

Publications on applications of network analysis 

Chambon, M., Dalege, J., Elberse, J. E., & van Harreveld, F. (2021). A psychological network approach to
attitudes and preventive behaviors during pandemics: A COVID-19 study in the United Kingdom and the Netherlands. Social Psychological and Personality Science. Advance online publication.

  • This paper applied network analysis to attitudes and preventive behaviors during the COVID-19 pandemic.

Sachisthal, M. S. M., Jansen, B. R. J., Dalege, J., & Raijmakers, M. E. J. (2020). Relating teenagers’ science interest network characteristics to later science course uptake: An analysis of Australian PISA 2006 and LSAY data. Australian Journal of Education, 64, 264-281.

  • This paper shows that centrality of nodes in a science interest network predicts which variables are most closely related to course uptake.

Zwicker, M. V., Nohlen, H. U., Dalege, J., Gruter, G.-J., & van Harreveld, F. (2020). Applying an attitude network approach to consumer behaviour towards plastic. Journal of Environmental Psychology, 69, 101433.

  • This paper applies network analysis to attitudes towards plastics and shows that the network structure of attitudes can inform interventions.

Sayans-Jiménez, P., van Harreveld, F., Dalege, J., & Rojas Tajada, A. J. (2019). Investigating stereotype structure with empirical network models. European Journal of Social Psychology, 49, 604-621.

  • This paper applies network analysis to the competence and warmth dimensions of stereotypes.

Sachisthal, M. S. M., Jansen, B. R. J., Peetsma, T. T. D., Dalege, J., van der Maas, H. L. J., & Raijmakers, M. E. J. (2019). Introducing a science interest network model to reveal country differences. Journal of Educational Psychology, 111, 1063–1080.

  • This paper uses network analysis to detect country differences in science interests.

Publications on psychometric network analysis

Borsboom, D., Deserno, M. K., Rhemtulla, M., Epskamp, S., Fried, E. I., McNally, R. J., Robinaugh, D. J., Perugini, M., Dalege, J., Costantini, G., Isvoranu, A.-M., Wysocki, A. C., van Borkulo, C. D., van Bork, R. & Waldorp, L. J. (2021). Network analysis of multivariate data in psychological science. Nature Reviews Methods Primers, 1, 58.

  • This paper provides a primer on psychometric network analysis.

Epskamp, S., Fried, E. I., van Borkulo, C. D., Robinaugh, D. J., Marsman, M., Dalege, J., Rhemtulla, M., & Cramer, A. O. J. (2021). Investigating the utility of fixed-margin sampling in network psychometricsMultivariate Behavioral Research, 56, 314-328.

  • This paper shows that fixed-margin sampling is of limited utility for estimating psychological networks.

Blanken, T. F., Deserno, M., Dalege, J., Borsboom, D., Blanken, P., Kerkhof, G. A., & Cramer, A. O. J. (2018). The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks. Scientific Reports, 8, 5854.

  • This paper applies a clustering technique, which allows for overlapping communities, to data on psychopathological symptoms.

Dalege, J., Borsboom, D., van Harreveld, F., & van der Maas, H. L. J. (2017). Network analysis on attitudes: A brief tutorialSocial Psychological and Personality Science, 8, 528-537.

  • This paper provides a brief tutorial on how to estimate and analyze attitude networks.

Publications on theory construction

Borsboom, D., van der Maas, H. L. J., Dalege, J., Kievit, R. A., & Haig, B. D. (2021). Theory construction methodology: A practical framework for theory formation in psychology. Perspectives on Psychological Science, 17, 756-766.

  • This paper introduces a methodology of theory construction that is based on analogical modeling.

Lange, J., Dalege, J., Borsboom, D., van Kleef, G. A., & Fischer, A. H. (2020). Toward an integrative psychometric model of emotions. Perspectives on Psychological Science15, 444-468.

  • This paper discusses different frameworks for formalized theories on emotions.

Other empirical studies 

Conner, M., Wilding, S., van Harreveld, F., & Dalege, J. (2021). Cognitive-affective inconsistency and ambivalence: Impact on evaluative attitude-behavior relationships. Personality and Social Psychology Bulletin, 47, 673-687.

  • This paper shows that cognitive-affective inconsistency is a stronger moderator of attitude-behavior congruence than ambivalence.

Degner, J. & Dalege, J. (2013). The apple does not fall far from the tree, or does it? A meta-analysis of parent-child similarity in intergroup attitudes. Psychological Bulletin, 139, 1270-1304.

  • This paper describes a meta-analysis showing that parents’ and their children’s intergroup attitudes are moderately related. 

Dalege, J. & Kreemers, L. (2012). Measurement invariance. In H. J. Adér & G. J. Mellenbergh (Eds.), Advising on research methods: Selected topics 2012 (pp. 9-30). Huizen, The Netherlands: Johannes van Kessel Publishing.

  • This chapter provides a tutorial on measurement invariance.

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