ABSTRACT:
Incentivized blockchain-based online social media (BOSM), where creators and curators of popular content are paid in cryptocurrency, have recently emerged. Traditional social media ecosystems have experienced significant bot involvement in their platforms, which has often had a negative impact on both users and platforms. BOSM can provide additional direct financial incentives as motivation for both bots’ and human users’ engagement. Using the panel vector autoregression and regression discontinuity in time framework, we analyze two distinct data sets from Steemit, the largest and most popular BOSM, to study the impact of bot engagement on human users and the impact of changes in financial reward on user engagement. Interestingly, our findings demonstrate that while increased engagement by bots is positively associated with engagement by human users, the association between bot engagement and human user engagement decreases as the number of votes for a post increases. We also find that shifts in economic incentives significantly influence the behavior of both human users and bots. This research provides significant insights on how social media platforms can leverage economic incentives to influence user behavior and, more importantly, leverage bots’ activity to increase the engagement of their human users.
Key words and phrases: Blockchain, social media networks, bots, user engagement, online social media, online incentives, Steemit, PVAR model, RDiT model