Understanding individuals' proclivity for novelty seeking

Licia Amichi, Aline Carneiro Viana, Mark Crovella, Antonio A.F. Loureiro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

Human mobility literature is limited in their ability to capture the novelty-seeking or the exploratory tendency of individuals. Mainly, the vast majority of mobility prediction models rely uniquely on the history of visited locations (as captured in the input dataset) to predict future visits. This hinders the prediction of new unseen places and reduces prediction accuracy. In this paper, we show that a two-dimensional modeling of human mobility, which explicitly captures both regular and exploratory behaviors, yields a powerful characterization of users. Using such model, we identify the existence of three distinct mobility profiles with regard to the exploration phenomenon - Scouters (i.e., extreme explorers), Routiners (i.e., extreme returners), and Regulars (i.e., without extreme behavior). Further, we extract and analyze the mobility traits specific to each profile. We then investigate temporal and spatial patterns in each mobility profile and show the presence of recurrent visiting behavior of individuals even in their novelty-seeking moments. Our results unveil important novelty preferences of people, which are ignored by literature prediction models. Finally, we show that prediction accuracy is dramatically affected by exploration moments of individuals. We then discuss how our profiling methodology could be leveraged to improve prediction.

Original languageEnglish
Title of host publicationProceedings of the 28th International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020
EditorsChang-Tien Lu, Fusheng Wang, Goce Trajcevski, Yan Huang, Shawn Newsam, Li Xiong
PublisherAssociation for Computing Machinery
Pages314-324
Number of pages11
ISBN (Electronic)9781450380195
DOIs
StatePublished - Nov 3 2020
Externally publishedYes
Event28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020 - Virtual, Online, United States
Duration: Nov 3 2020Nov 6 2020

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Conference

Conference28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2020
Country/TerritoryUnited States
CityVirtual, Online
Period11/3/2011/6/20

Funding

We would like to thank the research agencies CAPES, CNPq, FAPEMIG, and FAPESP (grant 18/23064-8) and the support from INRIA, Sorbonne UPMC, LINCS, ANR (French National Research Agency) MITIK project - call PRC AAPG2019.

FundersFunder number
LINCS
Sorbonne UPMC
Institut national de recherche en informatique et en automatique (INRIA)
Agence Nationale de la RechercheAAPG2019
Fundação de Amparo à Pesquisa do Estado de São Paulo18/23064-8
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Conselho Nacional de Desenvolvimento Científico e Tecnológico
Fundação de Amparo à Pesquisa do Estado de Minas Gerais

    Keywords

    • Exploration
    • Individual Mobility
    • Mobility Profiling

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