Sport prosumer networks: exploring prosumption value in Twitter conversations during COVID-19

ABSTRACT

Purpose

Value within prosumption systems such as Twitter is underexplored. We adopt an economic sociology perspective to measure prosumption value, using the #ProjectRestart campaign as football looked to resume following COVID-19.

Design

We use social network analysis to analyse 21,000 tweets involving 10,810 Twitter users using the #ProjectRestart hashtag. Specifically, we apply network theory measures, community clustering, betweenness, domain prestige and proximity prestige to explore how prosumption value can be measured.

Findings

Our empirical findings demonstrate how value can be perceived within prosumption systems. Specifically, it shows how developing cohesive prosumer networks is vital in exploiting prosumer capital, creating value in the virtual space, which is imperative in negotiating through times of uncertainty, like COVID-19.

Practical Implications

The practical implications encourage the industry to think of value in the virtual space differently, embedding this into future management strategies.

Research Contribution

This research provides a theoretical contribution of prosumer value, blending prosumption and economic sociology theories. Empirically, it demonstrates how actors in the football world used prosumer networks to create value during the COVID-19 pandemic.

KEYWORDS:

• Prosumption
• networks
• economic sociology
• sport
• COVID-19

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 The Union of European Football Associations (UEFA) is the supranational federation for football governance across Europe.

2 Since NodeXL gathers tweets within a 6–9 day window or an upper limit of 18,000 tweets. We chose to collect every four days for two reasons, (1) the first web scrape demonstrated that tweets were collected over seven days; therefore, daily data collection was unnecessary; (2) four days allowed new data to be gathered without considerable and unnecessary duplication; reducing data processing.