Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Hunters, busybodies and the knowledge network building associated with deprivation curiosity

Nature Human Behaviour volume 5, pages 327–336 (2021)Cite this article

Subjects

Abstract

The open-ended and internally driven nature of curiosity makes characterizing the information seeking that accompanies it a daunting endeavour. We use a historico-philosophical taxonomy of information seeking coupled with a knowledge network building framework to capture styles of information-seeking in 149 participants as they explore Wikipedia for over 5 hours spanning 21 days. We create knowledge networks in which nodes represent distinct concepts and edges represent the similarity between concepts. We quantify the tightness of knowledge networks using graph theoretical indices and use a generative model of network growth to explore mechanisms underlying information-seeking. Deprivation curiosity (the tendency to seek information that eliminates knowledge gaps) is associated with the creation of relatively tight networks and a relatively greater tendency to return to previously visited concepts. With this framework in hand, future research can readily quantify the information seeking associated with curiosity.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Hunter and busybody styles of information seeking.
Fig. 2: Knowledge network construction and the association between deprivation curiosity and edge weight.
Fig. 3: Deprivation curiosity and the clustering and path length of knowledge networks.
Fig. 4: Generative model and associations with deprivation curiosity.
Fig. 5: Within-person variability in hunter and busybody styles.

Similar content being viewed by others

Data availability

All data used in the manuscript are available upon request from the corresponding author.

Code availability

The analyses in the manuscript used code available through R, MATLAB and the Brain Connectivity Toolbox. The code associated with the generative model is available at https://github.com/dalejn/kinestheticCuriosity.

References

  1. Gottlieb, J., Oudeyer, P. Y., Lopes, M. & Baranes, A. Information-seeking, curiosity, and attention: computational and neural mechanisms. Trends Cogn. Sci. 17, 585–593 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Gottlieb, J. & Oudeyer, P. Y. Towards a neuroscience of active sampling and curiosity. Nat. Rev. Neurosci. 19, 758–770 (2018).

    Article  CAS  PubMed  Google Scholar 

  3. Kidd, C. & Hayden, B. Y. The psychology and neuroscience of curiosity. Neuron 88, 449–460 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Blanchard, T. C., Hayden, B. Y. & Bromberg-Martin, E. S. Orbitofrontal cortex uses distinct codes for different choice attributes in decisions motivated by curiosity. Neuron 85, 602–614 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Brydevall, M., Bennett, D., Murawski, C. & Bode, S. The neural encoding of information prediction errors during non-instrumental information seeking. Sci. Rep. 8, 6134 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  6. Daddaoua, N., Lopes, M. & Gottlieb, J. Intrinsically motivated oculomotor exploration guided by uncertainty reduction and conditioned reinforcement in non-human primates. Sci. Rep. 6, 20202 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Lydon-Staley, D. M., Zurn, P. & Bassett, D. S. Within-person variability in curiosity during daily life and associations with well-being. J. Pers. 88, 625–641 (2020).

    Article  PubMed  Google Scholar 

  8. Park, S., Kim, M.-S. & Chun, M. M. Concurrent working memory load can facilitate selective attention: evidence for specialized load. J. Exp. Psychol. Hum. Percept. Perform. 33, 1062–1075 (2007).

    Article  PubMed  Google Scholar 

  9. Peterson, C., Ruch, W., Beermann, U., Park, N. & Seligman, M. E. Strengths of character, orientations to happiness, and life satisfaction. J. Posit. Psychol. 2, 149–156 (2007).

    Article  Google Scholar 

  10. Fredrickson, B. L. in Advances in Experimental Social Psychology (eds Plant, E. A. & Devine, P. G.) 1–53 (Academic Press, 2013).

  11. Fredrickson, B. L. The role of positive emotions in positive psychology. Am. Psychol. 56, 218–226 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kashdan, T. B., Rose, P. & Fincham, F. D. Curiosity and exploration: facilitating positive subjective experiences and personal growth opportunities. J. Pers. Assess. 82, 291–305 (2004).

    Article  PubMed  Google Scholar 

  13. Nowotny, H. Insatiable Curiosity: Innovation in a Fragile Future (MIT Press, 2010).

  14. Zurn, P. in Toward New Philosophical Explorations of the Epistemic Desire to Know: Just Curious about Curiosity (ed. Papastefanou, M.) 27–49 (Cambridge Scholars Press, 2019).

  15. Heidegger, M. Being and Time (trans. Stambaugh, J.) (State Univ. of New York Press, 1996).

  16. Yonge, C. D. (trans.) The Works of Philo: Complete and Unabridged (Hendrickson, 1993).

  17. Helmbold, W. C. et al. Plutarch’s Moralia Vol. 1 (Harvard Univ. Press, 1960).

  18. Nietzsche, F. Beyond Good and Evil (trans. Kaufmann, W.) (Vintage Books, 1996).

  19. Zurn, P. & Bassett, D. S. On curiosity: a fundamental aspect of personality, a practice of network growth. Pers. Neurosci. 1, e13 (2018).

    Google Scholar 

  20. Baranes, A., Oudeyer, P. Y. & Gottlieb, J. Eye movements reveal epistemic curiosity in human observers. Vis. Res. 117, 81–90 (2015).

    Article  PubMed  Google Scholar 

  21. Risko, E. F., Anderson, N. C., Lanthier, S. & Kingstone, A. Curious eyes: individual differences in personality predict eye movement behavior in scene-viewing. Cognition 122, 86–90 (2012).

    Article  PubMed  Google Scholar 

  22. Bassett, D. S. in Curiosity Studies: Toward a New Ecology of Knowledge (eds Zurn, P. & Shankar, A.) 57–74 (Univ. of Minnesota Press, 2019).

  23. West, R. & Leskovec, J. Human wayfinding in information networks. Proc. 21st Int. Conf. World Wide Web 117, 619–628 (2012).

    Google Scholar 

  24. Gross, J. L. & Yellen, J. Handbook of Graph Theory (CRC, 2004).

  25. Newman, M. Networks (Oxford Univ. Press, 2018).

  26. Loewenstein, G. The psychology of curiosity: a review and reinterpretation. Psychol. Bull. 116, 75–98 (1994).

    Article  Google Scholar 

  27. Litman, J. A. & Mussel, P. Validity of the interest- and deprivation-type epistemic curiosity model in Germany. J. Individ. Differ. 34, 59–68 (2013).

    Article  Google Scholar 

  28. Litman, J. A. Interest and deprivation factors of epistemic curiosity. Pers. Individ. Differ. 44, 1585–1595 (2008).

    Article  Google Scholar 

  29. Litman, J. A. & Jimerson, T. L. The measurement of curiosity as a feeling of deprivation. J. Pers. Assess. 82, 147–157 (2004).

    Article  PubMed  Google Scholar 

  30. Kashdan, T. B. et al. The five-dimensional curiosity scale: capturing the bandwidth of curiosity and identifying four unique subgroups of curious people. J. Res. Pers. 73, 130–149 (2018).

    Article  Google Scholar 

  31. Litman, J. A. Relationships between measures of I- and D-type curiosity, ambiguity tolerance, and need for closure: an initial test of the wanting–liking model of information-seeking. Pers. Individ. Differ. 48, 397–402 (2010).

    Article  Google Scholar 

  32. Golman, R. & Loewenstein, G. Information gaps: a theory of preferences regarding the presence and absence of information. Decision 5, 143–164 (2018).

    Article  Google Scholar 

  33. Litman, J. in The Cambridge Handbook on Motivation and Learning (eds Renniger, K. A. & Hidi, S. E.) 418–422 (Cambridge Univ. Press, 2019).

  34. Lauriola, M. et al. Epistemic curiosity and self-regulation. Pers. Individ. Differ. 83, 202–207 (2015).

    Article  Google Scholar 

  35. FitzGibbon, L., Lau, J. K. L. & Murayama, K. The seductive lure of curiosity: information as a motivationally salient reward. Curr. Opin. Behav. Sci. 35, 21–27 (2020).

    Article  Google Scholar 

  36. Berridge, K. C. From prediction error to incentive salience: mesolimbic computation of reward motivation. Eur. J. Neurosci. 35, 1124–1143 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Berridge, K. C. The debate over dopamine’s role in reward: the case for incentive salience. Psychopharmacology 191, 391–431 (2007).

    Article  CAS  PubMed  Google Scholar 

  38. Robinson, T. E. & Berridge, K. C. Incentive-sensitization and drug ‘wanting’. Psychopharmacology 171, 352–353 (2004).

    Article  CAS  Google Scholar 

  39. Berridge, K. C. & Robinson, T. E. What is the role of dopamine in reward: hedonic impact, reward learning, or incentive salience? Brain Res. Rev. 28, 309–369 (1998).

    Article  CAS  PubMed  Google Scholar 

  40. Lau, J. K. L., Ozono, H., Kuratomi, K., Komiya, A. & Murayama, K. Shared striatal activity in decisions to satisfy curiosity and hunger at the risk of electric shocks. Nat. Hum. Behav. 4, 531–543 (2020).

    Article  PubMed  Google Scholar 

  41. Kobayashi, K. & Hsu, M. Common neural code for reward and information value. Proc. Natl Acad. Sci. USA 116, 13061–13066 (2019).

    Article  CAS  PubMed  Google Scholar 

  42. Gruber, M. J., Gelman, B. D. & Ranganath, C. States of curiosity modulate hippocampus-dependent learning via the dopaminergic circuit. Neuron 84, 486–496 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Shin, D. D. & Kim, S.-i. Homo curious: curious or interested? Educ. Psychol. Rev. 31, 853–874 (2019).

    Article  Google Scholar 

  44. Scholtes, I. When is a network a network? Multi-order graphical model selection in pathways and temporal networks. Preprint at arXiv https://arxiv.org/abs/1702.05499 (2017).

  45. West, R. & Leskovec, J. Automatic versus human navigation in information networks. In Proc. 6th International AAAI Conference on Weblogs and Social Media (ed. Breslin, J.) 362–369 (AAAI, 2012).

  46. Lamprecht, D., Lerman, K., Helic, D. & Strohmaier, M. How the structure of Wikipedia articles influences user navigation. New Rev. Hypermedia Multimed. 23, 29–50 (2017).

    Article  PubMed  Google Scholar 

  47. Lemmerich, F., Sáez-Trumper, D., West, R. & Zia, L. Why the world reads Wikipedia: beyond English speakers. In Proc. 12th ACM International Conference on Web Search and Data Mining (eds. Culpepper, J. S. & Moffat, A.) 618–626 (ACM, 2019).

  48. Singer, P. et al. Why we read Wikipedia. In Proc. 26th International Conference on World Wide Web (eds. Barrett, R. & Cummings, R.) 1591–1600 (International World Wide Web Conferences Steering Committee, 2017).

  49. Kashdan, T. B. & Steger, M. F. Curiosity and pathways to well-being and meaning in life: traits, states, and everyday behaviors. Motiv. Emot. 31, 159–173 (2007).

    Article  Google Scholar 

  50. Zuckerman, M. Behavioral Expressions and Biosocial Bases of Sensation Seeking (Cambridge Univ. Press, 1994).

  51. Lydon-Staley, D. & Bassett, D. Within-person variability in sensation-seeking during daily life: positive associations with alcohol use and self-defined risky behaviors. Psychol. Addict. Behav. 34, 257–268 (2020).

    Article  PubMed  Google Scholar 

  52. Kleiman, E. E. MAtools: Data management tools for real-time monitoring/ecological momentary assessment data. R package version 0.1.3 (2017).

  53. Onnela, J. P., Saramäki, J., Kertész, J. & Kaski, K. Intensity and coherence of motifs in weighted complex networks. Phys. Rev. E 71, 065103 (2005).

    Article  CAS  Google Scholar 

  54. Latora, V. & Marchiori, M. Efficient behavior of small-world networks. Phys. Rev. Lett. 87, 198701 (2001).

    Article  CAS  PubMed  Google Scholar 

  55. Van Wijk, B. C., Stam, C. J. & Daffertshofer, A. Comparing brain networks of different size and connectivity density using graph theory. PLoS ONE 5, e13701 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  56. Viswanathan, G. M. et al. Optimizing the success of random searches. Nature 401, 911–914 (1999).

    Article  CAS  PubMed  Google Scholar 

  57. Viswanathan, G. et al. Lévy flights in random searches. Physica A 282, 208–213 (2000).

    Article  Google Scholar 

  58. Sims, D. W. et al. Scaling laws of marine predator search behaviour. Nature 451, 1098–1102 (2008).

    Article  CAS  PubMed  Google Scholar 

  59. Hills, T. T., Maouene, M., Maouene, J., Sheya, A. & Smith, L. Longitudinal analysis of early semantic networks: preferential attachment or preferential acquisition? Psychol. Sci. 20, 729–739 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  60. Santos, M., Viswanathan, G., Raposo, E. & da Luz, M. Optimization of random searches on regular lattices. Phys. Rev. E 72, 046143 (2005).

    Article  CAS  Google Scholar 

  61. Wosniack, M., Santos, M., Raposo, E., Viswanathan, G. & Da Luz, M. Robustness of optimal random searches in fragmented environments. Phys. Rev. E 91, 052119 (2015).

    Article  CAS  Google Scholar 

  62. Raposo, E. P. et al. How landscape heterogeneity frames optimal diffusivity in searching processes. PLoS Comput. Biol. 7, e1002233 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Harris, T. H. et al. Generalized Lévy walks and the role of chemokines in migration of effector CD8+ T cells. Nature 486, 545–548 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Rhee, I. et al. On the Levy-walk nature of human mobility. IEEE ACM Trans. Netw. 19, 630–643 (2011).

    Article  Google Scholar 

  65. Rhodes, T. & Turvey, M. T. Human memory retrieval as Lévy foraging. Physica A 385, 255–260 (2007).

    Article  Google Scholar 

  66. Bartumeus, F. Lévy processes in animal movement: an evolutionary hypothesis. Fractals 15, 151–162 (2007).

    Article  Google Scholar 

  67. Humphries, N. E. et al. Environmental context explains Lévy and Brownian movement patterns of marine predators. Nature 465, 1066–1069 (2010).

    Article  CAS  PubMed  Google Scholar 

  68. Viswanathan, G. M., Da Luz, M. G., Raposo, E. P. & Stanley, H. E. The Physics of Foraging: An Introduction to Random Searches and Biological Encounters (Cambridge Univ. Press, 2011).

  69. Wosniack, M. E., Santos, M. C., Raposo, E. P., Viswanathan, G. M. & da Luz, M. G. The evolutionary origins of Lévy walk foraging. PLoS Comput. Biol. 13, e1005774 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  70. Hills, T. T. Animal foraging and the evolution of goal-directed cognition. Cogn. Sci. 30, 3–41 (2006).

    Article  PubMed  Google Scholar 

  71. Todd, P. M., Hills, T. T. & Robbins, T. W. Cognitive Search: Evolution, Algorithms, and the Brain Vol. 9 (MIT Press, 2012).

  72. Berlyne, D. E. Conflict, Arousal, and Curiosity (McGraw-Hill, 1960).

  73. Day, H. An Instrument for the Measurement of Intrinsic Motivation: An Interim Report to the Department of Manpower and Immigration (York University, 1969).

  74. Leherissey, B. L. The Development of a Measure of State Epistemic Curiosity (ERIC, 1971).

  75. Litman, J. A. & Spielberger, C. D. Measuring epistemic curiosity and its diversive and specific components. J. Pers. Assess. 80, 75–86 (2003).

    Article  PubMed  Google Scholar 

  76. Zurn, P. & Bassett, D. S. Philosophy of biology: seizing an opportunity. eLife 8, e48336 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Johnson, K. T. in Curiosity Studies: Toward a New Ecology of Knowledge (eds Zurn, P. & Shankar, A.) 129–146 (Univ. of Minnesota Press, 2020).

  78. Kenett, Y. N., Anaki, D. & Faust, M. Investigating the structure of semantic networks in low and high creative persons. Front. Hum. Neurosci. 8, 407 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  79. Kenett, Y. N. & Faust, M. A semantic network cartography of the creative mind. Trends Cogn. Sci. 23, 271–274 (2019).

    Article  PubMed  Google Scholar 

  80. Fosco, G. M. & Lydon-Staley, D. M. A within-family examination of interparental conflict, cognitive appraisals, and adolescent mood and well-being. Child Dev. 90, e421–e436 (2019).

    Article  PubMed  Google Scholar 

  81. Carver, C. S. & White, T. L. Behavioral inhibition, behavioral activation, and affective responses to impending reward and punishment: the bis/bas scales. J. Pers. Soc. Psychol. 67, 319–333 (1994).

    Article  Google Scholar 

  82. Costa, P. T. & McCrae, R. R. Normal personality assessment in clinical practice: the neo personality inventory. Psychol. Assess. 4, 5–13 (1992).

    Article  Google Scholar 

Download references

Acknowledgements

We thank J. Dworkin, C. W. Lynn and S. Patankar for feedback on earlier versions of the manuscript. D.S.B., D.M.L.-S., D.Z. and A.S.B. acknowledge support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the ISI Foundation, the Paul Allen Foundation, the Army Research Laboratory (grant no. W911NF-10-2-0022), the Army Research Office (grant nos Bassett-W911NF-14-1-0679, Grafton-W911NF-16-1-0474 and DCIST-W911NF-17-2-0181), the Office of Naval Research, the National Institute of Mental Health (grant nos 2-R01-DC-009209-11, R01-MH112847, R01-MH107235 and R21-M MH-106799), the National Institute of Child Health and Human Development (grant no. 1R01HD086888-01), the National Institute of Neurological Disorders and Stroke (grant no. R01 NS099348), the National Science Foundation (grant nos PHY-1554488 and BCS-1631550) and the National Institute on Drug Abuse (grant no. 1K01DA047417). All authors acknowledge support from the Center for Curiosity. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Authors and Affiliations

  1. Annenberg School for Communication, University of Pennsylvania, Philadelphia, PA, USA

    David M. Lydon-Staley

  2. Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, USA

    David M. Lydon-Staley, Ann Sizemore Blevins & Danielle S. Bassett

  3. Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Dale Zhou

  4. Department of Philosophy, American University, Washington DC, USA

    Perry Zurn

  5. Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, USA

    Danielle S. Bassett

  6. Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Danielle S. Bassett

  7. Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA, USA

    Danielle S. Bassett

  8. Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Danielle S. Bassett

  9. Santa Fe Institute, Santa Fe, NM, USA

    Danielle S. Bassett

Authors
  1. David M. Lydon-Staley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dale Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ann Sizemore Blevins
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Perry Zurn
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Danielle S. Bassett
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.M.L.-S. designed the research with input from D.Z., P.Z. and D.S.B. D.M.L.-S., A.S.B. and D.Z. analysed the data. D.M.L.-S. wrote the paper. A.S.B., D.Z., P.Z. and D.S.B. edited the paper.

Corresponding author

Correspondence to Danielle S. Bassett.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary handling editor: Aisha Bradshaw.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5, Supplementary Tables 1–23, methods, results, discussion and references.

Reporting Summary

Supplementary Video 1

An illustration of the effects of varying levels of reinforcement and regularity parameters on network exploration. We modelled different styles of knowledge network growth using a generative model consisting of two growth rules: reinforcement and regularity. Reinforcement is the value an agent places on similar and previously sought information while traversing a knowledge network. Regularity reflects the preference to take short versus long topological steps while exploring a knowledge network. The four panels in the video illustrate how varying levels of reinforcement and regularity influence knowledge network growth. High values of reinforcement are associated with a greater likelihood of returning to previously visited concepts, resulting in networks akin to the hunter style of curious information seeking. High regularity values are associated with a preference to take shorter topological leaps when walking on the knowledge network, resulting in tight networks akin to the style of the hunter. Loose networks associated with the busybody style of information seeking are reflected in low values of reinforcement and low values of regularity.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lydon-Staley, D.M., Zhou, D., Blevins, A.S. et al. Hunters, busybodies and the knowledge network building associated with deprivation curiosity. Nat Hum Behav 5, 327–336 (2021). https://doi.org/10.1038/s41562-020-00985-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-020-00985-7

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing