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Traditional versus Facebook-based surveys: Evaluation of biases in self-reported demographic and psychometric information

Author

Listed:
  • Kyriaki Kalimeri

    (ISI Foundation)

  • Mariano G. Beiró

    (Universidad de Buenos Aires)

  • Andrea Bonanomi

    (Università Cattolica del Sacro Cuore)

  • Alessandro Rosina

    (Università Cattolica del Sacro Cuore)

  • Ciro Cattuto

    (ISI Foundation)

Abstract

Background: Social media in scientific research offers a unique digital observatory of human behaviours and hence great opportunities to conduct research at large scale, answering complex sociodemographic questions. We focus on the identification and assessment of biases in social-media-administered surveys. Objective: This study aims to shed light on population, self-selection, and behavioural biases, empirically comparing the consistency between self-reported information collected traditionally versus social-media-administered questionnaires, including demographic and psychometric attributes. Methods: We engaged a demographically representative cohort of young adults in Italy (approximately 4,000 participants) in taking a traditionally administered online survey and then, after one year, we invited them to use our ad hoc Facebook application (988 accepted) where they filled in part of the initial survey. We assess the statistically significant differences indicating population, self-selection, and behavioural biases due to the different context in which the questionnaire is administered. Results: Our findings suggest that surveys administered on Facebook do not exhibit major biases with respect to traditionally administered surveys in terms of neither demographics nor personality traits. Loyalty, authority, and social binding values were higher in the Facebook platform, probably due to the platform’s intrinsic social character. Conclusions: We conclude that Facebook apps are valid research tools for administering demographic and psychometric surveys, provided that the entailed biases are taken into consideration. Contribution: We contribute to the characterisation of Facebook apps as a valid scientific tool to administer demographic and psychometric surveys, and to the assessment of population, self-selection, and behavioural biases in the collected data.

Suggested Citation

  • Kyriaki Kalimeri & Mariano G. Beiró & Andrea Bonanomi & Alessandro Rosina & Ciro Cattuto, 2020. "Traditional versus Facebook-based surveys: Evaluation of biases in self-reported demographic and psychometric information," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(5), pages 133-148.
  • Handle: RePEc:dem:demres:v:42:y:2020:i:5
    DOI: 10.4054/DemRes.2020.42.5
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    References listed on IDEAS

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    Cited by:

    1. Andrea Bonanomi & Alessandro Rosina, 2022. "Employment Status and Well-Being: A Longitudinal Study on Young Italian People," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 581-598, June.
    2. Jurić, Tado, 2022. "Forecasting Migration and Integration Trends Using Digital Demography – A Case Study of Emigration Flows from Croatia to Austria and Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 70(1), pages 125-152.
    3. Georgios Lazaridis & Dimitris Panaretos & Antonia Matalas, 2022. "The Impact of the COVID-19 Pandemic on the Food-Related Behaviour of Tourists Visiting Greece," Tourism and Hospitality, MDPI, vol. 3(4), pages 1-22, September.
    4. Jurić Tado, 2022. "Forecasting Migration and Integration Trends Using Digital Demography – A Case Study of Emigration Flows from Croatia to Austria and Germany," Comparative Southeast European Studies, De Gruyter, vol. 70(1), pages 125-152, March.
    5. Jurić, Tado, 2022. "Predicting refugee flows from Ukraine with an approach to Big (Crisis) Data: a new opportunity for refugee and humanitarian studies," EconStor Preprints 251215, ZBW - Leibniz Information Centre for Economics.

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    More about this item

    Keywords

    demography; survey; bias; social media; psychometrics; Facebook; self-selection bias; recruitment bias; self-reporting bias; personality; moral foundations;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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