The Road to Popularity: The Dilution of Growing Audience on Twitter

TL;DR

This paper investigates how the characteristics and engagement of followers on Twitter evolve as a user’s audience grows, revealing early followers tend to be more elite, similar, and engaged than later followers.

Contribution

It provides a detailed analysis of audience dilution on Twitter, distinguishing effects of audience growth from overall platform growth, and examines follower similarity and engagement patterns.

Findings

Early followers are more likely to be verified and expert users.

Early followers share more interests and characteristics with the followed user.

Engagement levels differ between early and late followers, with early followers more likely to retweet.

Abstract

On social media platforms, like Twitter, users are often interested in gaining more influence and popularity by growing their set of followers, aka their audience. Several studies have described the properties of users on Twitter based on static snapshots of their follower network. Other studies have analyzed the general process of link formation. Here, rather than investigating the dynamics of this process itself, we study how the characteristics of the audience and follower links change as the audience of a user grows in size on the road to user's popularity. To begin with, we find that the early followers tend to be more elite users than the late followers, i.e., they are more likely to have verified and expert accounts. Moreover, the early followers are significantly more similar to the person that they follow than the late followers. Namely, they are more likely to share time zone, language, and topics of interests with the followed user. To some extent, these phenomena are related with the growth of Twitter itself, wherein the early followers tend to be the early adopters of Twitter, while the late followers are late adopters. We isolate, however, the effect of the growth of audiences consisting of followers from the growth of Twitter's user base itself. Finally, we measure the engagement of such audiences with the content of the followed user, by measuring the probability that an early or late follower becomes a retweeter.