Socioeconomic inequality in daily behaviour and social interactions: evidence from digital trace data

He, Yuanmo (2024) Socioeconomic inequality in daily behaviour and social interactions: evidence from digital trace data. PhD thesis, London School of Economics and Political Science.

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Abstract

This PhD thesis leverages large-scale digital trace data and advanced computational methods to examine how socioeconomic inequality is reflected and reinforced in daily life and social interactions. Grounded in Bourdieu’s theory of economic, cultural, and social capital, the thesis comprises three empirical papers that explore different dimensions of socioeconomic inequality. The first paper proposes and validates a method to estimate individual Twitter users’ SES based on the brands they follow. Rooted in Bourdieu’s definition of socioeconomic status, the method measures a combination of economic and cultural capital. The SES estimates show significant correlations with traditional SES proxies, including income, education, and occupational social class. The second paper delves into the relationship between economic and cultural capital by utilising newly available mobile-tracking data to study inequality in daily consumption. Incorporating theories of conspicuous consumption, cultural omnivorousness, and inconspicuous consumption, the study presents a coherent theoretical framework suggesting that SES is positively associated with consumption diversity and offers large-scale empirical evidence supporting the hypothesis. The third paper utilises the SES estimates from the first paper to illustrate that Twitter users with higher SES tend to have higher social capital and more advantageous communication behaviour. It also shows that while high and low SES users mostly talk about similar topics, they tend to use different hashtags and have divergent sentiments towards immigration. Collectively, the thesis demonstrates the social and cultural factors in the persistence of inequality with large-scale digital trace data. The thesis not only extends existing social theories with innovative data and methods but also bridges the gap between theory-driven and data-driven research traditions.4

Item Type:	Thesis (PhD)
Additional Information:	© 2024 Yuanmo He
Library of Congress subject classification:	H Social Sciences > H Social Sciences (General) H Social Sciences > HC Economic History and Conditions
Sets:	Departments > Methodology
Supervisor:	Tsvetkova, Milena and Benoit, Kenneth
URI:	http://etheses.lse.ac.uk/id/eprint/4800

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