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Language, demographics, emotions, and the structure of online social networks

Author

Listed:
  • Kristina Lerman

    (USC Information Sciences Institute)

  • Luciano G. Marin

    (USC Information Sciences Institute)

  • Megha Arora

    (Carnegie Mellon University)

  • Lucas H. Costa Lima

    (Federal University of Minas Gerais)

  • Emilio Ferrara

    (USC Information Sciences Institute)

  • David Garcia

    (Complexity Science Hub Vienna and Medical University of Vienna)

Abstract

Social networks affect individuals’ economic opportunities and well-being. However, few of the factors thought to shape networks—culture, language, education, and income—were empirically validated at scale. To fill this gap, we collected a large number of social media posts from a major US metropolitan area. By associating these posts with US Census tracts through their locations, we linked socioeconomic indicators to group-level signals extracted from social media, including emotions, language, and online social ties. Our analysis shows that tracts with higher education levels have weaker social ties, but this effect is attenuated for tracts with high ratio of Hispanic residents. Negative emotions are associated with more frequent online interactions, or stronger social ties, while positive emotions are associated with weaker ties. These results hold for both Spanish and English tweets, evidencing that language does not affect this relationship between emotion and social ties. Our findings highlight the role of cognitive and demographic factors in online interactions and demonstrate the value of traditional social science sources, like US Census data, within social media studies.

Suggested Citation

  • Kristina Lerman & Luciano G. Marin & Megha Arora & Lucas H. Costa Lima & Emilio Ferrara & David Garcia, 2018. "Language, demographics, emotions, and the structure of online social networks," Journal of Computational Social Science, Springer, vol. 1(1), pages 209-225, January.
    • Handle: RePEc:spr:jcsosc:v:1:y:2018:i:1:d:10.1007_s42001-017-0001-x
    DOI: 10.1007/s42001-017-0001-x
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    References listed on IDEAS

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    1. Mike Thelwall & Kevan Buckley & Georgios Paltoglou, 2012. "Sentiment strength detection for the social web," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 163-173, January.
    2. Sean Reardon & Stephen Matthews & David O’Sullivan & Barrett Lee & Glenn Firebaugh & Chad Farrell & Kendra Bischoff, 2008. "The geographic scale of Metropolitan racial segregation," Demography, Springer;Population Association of America (PAA), vol. 45(3), pages 489-514, August.
    3. Mike Thelwall & Kevan Buckley & Georgios Paltoglou, 2012. "Sentiment strength detection for the social web," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 163-173, January.
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    Cited by:

    1. Juan Miguel Rodriguez-Lopez & Meike Schickhoff & Shubhankar Sengupta & Jürgen Scheffran, 2021. "Technological and social networks of a pastoralist artificial society: agent-based modeling of mobility patterns," Journal of Computational Social Science, Springer, vol. 4(2), pages 681-707, November.

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