Activity Concentration and Participation Scaling in Livestream Chats: A Reanalysis of 694,728 Twitch Channels
DOI:
https://doi.org/10.64747/17y12371Keywords:
livestreaming, Twitch, synchronous chat, digital participation, concentration, scalingAbstract
Synchronous chat makes one component of participation visible on livestreaming platforms, yet averages may conceal extreme inequalities across channels. This study quantified the concentration of messages and active chatters and estimated how accumulated activity scales with the number of active chatters. We reanalyzed an anonymized public Twitch dataset comprising 694,728 channels observed from 26 August to 10 November 2014. Descriptive statistics, Gini coefficients, cumulative shares, size strata, and a robust log10(messages) ~ log10(active chatters) regression were calculated, with a sensitivity analysis excluding the top 0.1% of channels by messages. The channels accumulated 496,580,654 messages. Medians were 7 messages and 2 active chatters, compared with means of 714.78 and 36.42. Gini coefficients were 0.9653 for messages and 0.9313 for active-chatter counts. The top 1% accounted for 71.00% of messages and 71.60% of active-chatter counts, whereas the bottom 50% accounted for 0.16% and 1.64%. The scaling slope was 1.5301 (95% CI: 1.5280–1.5322; R² = 0.8229) and remained 1.5407 after excluding the top 0.1%. Activity and active participation were highly concentrated, and message volume had a superlinear association with active-chatter counts. The design does not identify causality: accumulated counts combine exposure, duration, and frequency and do not measure passive audiences, retention, or community quality.
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