IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v47y2018i3p458-491.html
   My bibliography  Save this article

Utilizing Smartphones to Study Disadvantaged and Hard-to-Reach Groups

Author

Listed:
  • Naomi F. Sugie

Abstract

Mobile technologies, specifically smartphones, offer social scientists a potentially powerful approach to examine the social world. They enable researchers to collect information that was previously unobservable or difficult to measure, expanding the realm of empirical investigation. For research that concerns resource-poor and hard-to-reach groups, smartphones may be particularly advantageous by lessening sample selection and attrition and by improving measurement quality of irregular and unstable experiences. At the same time, smartphones are nascent social science tools, particularly with less advantaged populations that may have different phone usage patterns and privacy concerns. Using findings from a smartphone study of men recently released from prison, this article discusses the strengths and challenges of smartphones as data collection tools among disadvantaged and hard-to-reach groups.

Suggested Citation

  • Naomi F. Sugie, 2018. "Utilizing Smartphones to Study Disadvantaged and Hard-to-Reach Groups," Sociological Methods & Research, , vol. 47(3), pages 458-491, August.
    • Handle: RePEc:sae:somere:v:47:y:2018:i:3:p:458-491
    DOI: 10.1177/0049124115626176
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124115626176
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124115626176?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. McCormick, Tyler H. & Salganik, Matthew J. & Zheng, Tian, 2010. "How Many People Do You Know?: Efficiently Estimating Personal Network Size," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 59-70.
    2. John Palmer & Thomas Espenshade & Frederic Bartumeus & Chang Chung & Necati Ozgencil & Kathleen Li, 2013. "New Approaches to Human Mobility: Using Mobile Phones for Demographic Research," Demography, Springer;Population Association of America (PAA), vol. 50(3), pages 1105-1128, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. D. Woods & A. Cunningham & C. E. Utazi & M. Bondarenko & L. Shengjie & G. E. Rogers & P. Koper & C. W. Ruktanonchai & E. zu Erbach-Schoenberg & A. J. Tatem & J. Steele & A. Sorichetta, 2022. "Exploring methods for mapping seasonal population changes using mobile phone data," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-17, December.
    2. Lee Fiorio & Emilio Zagheni & Guy J. Abel & Johnathan Hill & Gabriel Pestre & Emmanuel Letouzé & Jixuan Cai, 2020. "Analyzing the effect of time in migration measurement using geo-referenced digital trace data," MPIDR Working Papers WP-2020-024, Max Planck Institute for Demographic Research, Rostock, Germany.
    3. Delclòs-Alió, Xavier & Miralles-Guasch, Carme, 2017. "Suburban travelers pressed for time: Exploring the temporal implications of metropolitan commuting in Barcelona," Journal of Transport Geography, Elsevier, vol. 65(C), pages 165-174.
    4. Elizabeth Sully & Margaret Giorgio & Selena Anjur-Dietrich, 2020. "Estimating abortion incidence using the network scale-up method," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 43(56), pages 1651-1684.
    5. Feehan, Dennis & Son, Vo Hai & Abdul-Quader, Abu, 2021. "Survey methods for estimating the size of weak-tie personal networks," SocArXiv z2t4p, Center for Open Science.
    6. Arun G. Chandrasekhar & Paul Goldsmith-Pinkham & Matthew O. Jackson & Samuel Thau, 2021. "Interacting regional policies in containing a disease," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(19), pages 2021520118-, May.
    7. Haley, Danielle F. & Matthews, Stephen A. & Cooper, Hannah L.F. & Haardörfer, Regine & Adimora, Adaora A. & Wingood, Gina M. & Kramer, Michael R., 2016. "Confidentiality considerations for use of social-spatial data on the social determinants of health: Sexual and reproductive health case study," Social Science & Medicine, Elsevier, vol. 166(C), pages 49-56.
    8. Shen, Yue & Chai, Yanwei & Kwan, Mei-Po, 2015. "Space–time fixity and flexibility of daily activities and the built environment: A case study of different types of communities in Beijing suburbs," Journal of Transport Geography, Elsevier, vol. 47(C), pages 90-99.
    9. Tyler H. McCormick & Tian Zheng, 2015. "Latent Surface Models for Networks Using Aggregated Relational Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(512), pages 1684-1695, December.
    10. Carlos Mejia-Arbelaez & Olga L. Sarmiento & Rodrigo Mora Vega & Mónica Flores Castillo & Ricardo Truffello & Lina Martínez & Catalina Medina & Oscar Guaje & José David Pinzón Ortiz & Andres F Useche &, 2021. "Social Inclusion and Physical Activity in Ciclovía Recreativa Programs in Latin America," IJERPH, MDPI, vol. 18(2), pages 1-24, January.
    11. Nina Cesare & Hedwig Lee & Tyler McCormick & Emma Spiro & Emilio Zagheni, 2018. "Promises and Pitfalls of Using Digital Traces for Demographic Research," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1979-1999, October.
    12. Hipp, John R., 2020. "Simulating spatial crime patterns: What do we learn in standard ecological studies of crime?," Journal of Criminal Justice, Elsevier, vol. 70(C).
    13. Shareck, Martine & Kestens, Yan & Frohlich, Katherine L., 2014. "Moving beyond the residential neighborhood to explore social inequalities in exposure to area-level disadvantage: Results from the Interdisciplinary Study on Inequalities in Smoking," Social Science & Medicine, Elsevier, vol. 108(C), pages 106-114.
    14. Emma Zang & Jessica West & Nathan Kim & Christina Pao, 2021. "U.S. regional differences in physical distancing: Evaluating racial and socioeconomic divides during the COVID-19 pandemic," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-17, November.
    15. Aparajithan Venkateswaran & Jishnu Das & Tyler H. McCormick, 2023. "Feasible contact tracing," Papers 2312.05718, arXiv.org.
    16. Fei Li & Donggen Wang, 2017. "Measuring urban segregation based on individuals’ daily activity patterns: A multidimensional approach," Environment and Planning A, , vol. 49(2), pages 467-486, February.
    17. Malia Jones & Anne Pebley, 2014. "Redefining Neighborhoods Using Common Destinations: Social Characteristics of Activity Spaces and Home Census Tracts Compared," Demography, Springer;Population Association of America (PAA), vol. 51(3), pages 727-752, June.
    18. Nolan E. Phillips & Brian L. Levy & Robert J. Sampson & Mario L. Small & Ryan Q. Wang, 2021. "The Social Integration of American Cities: Network Measures of Connectedness Based on Everyday Mobility Across Neighborhoods," Sociological Methods & Research, , vol. 50(3), pages 1110-1149, August.
    19. Alex Carballo-Diéguez & Ivan Balan & Rubén Marone & María A Pando & Curtis Dolezal & Victoria Barreda & Cheng-Shiun Leu & María Mercedes Ávila, 2011. "Use of Respondent Driven Sampling (RDS) Generates a Very Diverse Sample of Men Who Have Sex with Men (MSM) in Buenos Aires, Argentina," PLOS ONE, Public Library of Science, vol. 6(11), pages 1-8, November.
    20. Luigi Curini & Stefano Iacus & Luciano Canova, 2015. "Measuring Idiosyncratic Happiness Through the Analysis of Twitter: An Application to the Italian Case," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 121(2), pages 525-542, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:47:y:2018:i:3:p:458-491. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.