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Does Twitter Data Mirror the European North–South Family Ties Divide? A Comparative Analysis of Tweets About Family

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  • Sofia Gil-Clavel

    (Delft University of Technology)

  • Clara H. Mulder

    (University of Groningen)

Abstract

Previous research on the relationship between geographical distance and the frequency of contact between family members has shown that the strength of family ties differs between Northern and Southern Europe. However, little is known about how family ties are reflected in peoples’ conversations on social media, despite research showing the relevance of social media data for understanding users’ daily expressions of emotions and thoughts based on their immediate experiences. This work investigates the question of whether Twitter use patterns in Europe mirror the North–South divide in the strength of family ties by analyzing potential differences in family-related tweets between users in Northern and Southern European countries. This study relies on a longitudinal database derived from Twitter collected between January 2012 and December 2016. We perform a comparative analysis of Southern and Northern European users’ tweets using Bayesian generalized multilevel models together with the Linguistic Inquiry and Word Count software. We analyze the association between regional differences in the strength of family ties and patterns of tweeting about family. Results show that the North–South divide is reflected in the frequency of tweets that are about family, that refer to family in the past versus in the present tense, and that are about close versus extended family.

Suggested Citation

  • Sofia Gil-Clavel & Clara H. Mulder, 2024. "Does Twitter Data Mirror the European North–South Family Ties Divide? A Comparative Analysis of Tweets About Family," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(4), pages 1-24, August.
  • Handle: RePEc:kap:poprpr:v:43:y:2024:i:4:d:10.1007_s11113-024-09891-6
    DOI: 10.1007/s11113-024-09891-6
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    References listed on IDEAS

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    1. Hadfield, Jarrod D., 2010. "MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i02).
    2. Michael Murphy, 2008. "Variations in Kinship Networks Across Geographic and Social Space," Population and Development Review, The Population Council, Inc., vol. 34(1), pages 19-49, March.
    3. Delia Mocanu & Andrea Baronchelli & Nicola Perra & Bruno Gonçalves & Qian Zhang & Alessandro Vespignani, 2013. "The Twitter of Babel: Mapping World Languages through Microblogging Platforms," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
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