Essays on the economics of online social interactions

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Ajzenman, Nicolás Matias
Ferman, Bruno
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This thesis consists of two independent chapters, each reporting the results of field experiments conducted on Twitter. Both are based on joint work with Nicolás Ajzenman and Bruno Ferman. The first chapter discusses an experiment designed to identify discrimination in users’ following behavior on Twitter. Specifically, we created fictitious bot accounts that resembled humans and claimed to be PhD students in economics. The accounts differed in their gender (male or female), race (Black or White), and university affiliation (top- or lower-ranked). The bot accounts randomly followed Twitter users who form part of the #EconTwitter academic community. We measured how many follow-backs each account obtained after a given period. Twitter users from this community were 12% more likely to follow accounts of White students compared to those of Black students; 21% more likely to follow accounts of students from top-ranked, prestigious universities compared to accounts of lower-ranked institutions; and 25% more likely to follow female compared to male students. The racial gap persisted even among students from top-ranked institutions, suggesting that Twitter users racially discriminate even in the presence of a signal that could be interpreted as indicative of high academic potential. The second chapter studies the interplay between political and other social identities in the formation of social ties. We created accounts on Twitter that signaled their political preference for one of the two leading candidates in the 2022 Brazilian Presidential election, their preference for a football club (interpreted as an affective dimension of identity, given football’s importance to socialization in Brazil), or both. The bots randomly followed Twitter accounts with congruent and incongruent identities across these dimensions. We computed the proportion of follow-backs and blocks received. Both dimensions of identity are relevant to forming ties, but the effect of sharing political identity is larger. Affective identity becomes substantially less relevant when information about political identity is available, indicating that political identity can overshadow the affective dimension. Finally, we document using Twitter data that Brazilians’ reactions to events in the 2022 FIFA World Cup depended on their political alignment with the national team’s players and coach. This reinforces the experimental conclusion that, in a polarized setting, political identities can hinder the potential of other shared identities to increase social cohesion.

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