[Proposal] The role of economic and cultural capital in paid consumption in the digitally-mediated Creator Economy

This proposed project examines the social implications of the rise of the Creator Economy, as denoted primarily by the emergence of digital content creators who monetize their audiences and communities in the form of subscriptions. Specifically, I propose an empirical investigation of how economic and cultural capital affects individuals’ choice in partaking as a consumer in the Creator Economy, with a focus on youths (aged 18 to 30) in the US and UK.

The main research question for this project is summarized as follows:

How does a consumer’s disposition, in the form of economic and cultural capital, influence what types of paid content one chooses to consume in the digitally-mediated Creator Economy?

Theoretical background

Information and communications has long been a territory that perpetuated the offline social divide. Indeed, there appears to be a stark difference between how people use the internet depending on their digital skills as well as educational attainment, among other structural factors (Hargittai, 2002; Blank & Groselj, 2014; Dutton & Reisford, 2019). Those who have higher educational attainment, for instance, tend to seek out “capital-enhancing activities” on the internet (DiMaggio & Hargittai, 2002), such as searching for information or looking for jobs.

Fast forward several years, in the age of TikTok and influencers, I theorize that we are witnessing a “third-level digital divide,” in line with recent research (Robinson et al., 2020).

Because the Creator Economy often comes with a price tag, disparity between who has the economic means to partake in this nascent sociodigital phenomenon would necessarily emerge. My first hypothesis is therefore:

H1 - Those with more economic capital are more likely to take part as a consumer in the Creator Economy.

Furthermore, just like how different groups differing in terms of income level or education attainment opt to use the internet in varying ways, these groups would once again differ in what types of creator content or goods they choose to pay for and consume. To help operationalize the concept of the Creator Economy, broadly, there are three categories of creators and the contents they produce:

1. knowledge sharing
2. cultural analysis/ opinion imparting
3. entertainment

Based on this framework, it seems likely that:

H2a - Of the consumers who do take part in the Creator Economy, those who have higher levels of cultural capital and economic capital would necessarily be more disproportionately prone to pay for and consume content/ goods produced and delivered by creators in the 1) knowledge disseminating/ sharing and 2) cultural analysis/ opinion imparting categories.

H2b - On the other hand, those with lower levels of economic, cultural, and to a lesser extent social capital would be more likely to pay for and consume content/ goods in the entertainment category.

The following section briefly outlines how I plan on testing above mentioned hypotheses.


The study will be multivariate in nature, and data will be collected via a Qualtrics survey distributed to participants recruited through Prolific. Due to the straightforward nature of the design of a survey, and the fact that my target audience are young adults aged 18 to 30 in the US and UK, Prolific is well-suited as a participant recruitment tool.

Sample size

This is a survey study, and therefore sample size estimation is based on the desired margin of error and confidence interval.

Both my US and UK samples will therefore be 1537, assuming a 0.25% margin of error and 95% confidence level. The combined sample size is 3074.


The main dependent variables are 1) whether an individual consumes paid content online produced by non-institutions, which will be coded as a binary categorical variable (0 = no, 1 = yes), and 2) which type of paid content one consumes, coded as a nominal categorical variable (knowledge, opinion, or entertainment).

The core independent variables are 1) one’s household income level (which operationalizes economic capital), as a continuous variable, and 2) one’s highest level of education completed (operationalizing cultural capital), coded as a ordinal categorical variable (1 = no education, 2 = secondary education, 3 = postsecondary education, 4 = postgraduate education).


For hypothesis H1, binary logistic regression will be used to examine the relationship between economic and cultural capital and one’s participation as a paying consumer in the Creator Economy.

For hypotheses H2a and H2b, nominal logistic regression will be used to examine the relationship between economic and cultural capital and one’s consumption choice in the Creator Economy.


With a sample size of 3074, this proposed project would require £4769.82 for data collection (assuming £7/hour reward rate and the survey would take 10 minutes).

I plan on pilot testing with 50 participants each for the US and UK, and assuming the same remuneration rate and completion time, this would require £155.17.

In total, I am requesting £5000, rounded up from £4924.99 to account for any unforeseen circumstances such as underpayment.


This project is preregistered with OSF. See link for more details.

Distribution plans

The outcomes of this proposed project will be distributed first as an open sourced preprint. It will also be submitted to peer-reviewed journals in the field of media and communications or digital sociology for publication. All data collected will be anonymized and uploaded to OSF.


Blank, G., Groselj, D. (2014). Dimensions of Internet use: amount, variety, and types. Information, Communication & Society 17(4).

DiMaggio, P., & Hargittai, E. (2002). The new digital inequality: Social stratification among Internet users. In American Sociological Association annual meetings, Chicago.

Dutton, W.H., Reisdorf, B.C. (2019). Cultural divides and digital inequalities: attitudes shaping Internet and social media divides. Information, Communication & Society 22(1).

Hargittai, E. (2002). Second-level digital divide: differences in people’s online skills. First Monday, 7.

Robinson, L., Schulz, J., Dunn, H. S., Casilli, A. A., Tubaro, P., Carvath, R., Chen, W., Wiest, J. B., Dodel, M., Stern, M. J., Ball, C., Huang, K.-T., Blank, G., Ragnedda, M., Ono, H., Hogan, B., Mesch, G. S., Cotten, S. R., Kretchmer, S. B., … Khilnani, A. (2020). Digital inequalities 3.0: Emergent inequalities in the information age. First Monday, 25(7).