Research Article: “Elites Tweet? Characterizing the Twitter Verified User Network”

The following research article (preprint) was recently shared on arXiv.
Title
Elites Tweet? Characterizing the Twitter Verified User Network
Authors
Indraneil Paul
International Institute of Information Technology, Hyderabad
Abhinav Khattar
Indraprastha Institute of Information Technology, Delhi
Ponnurangam Kumaraguru
International Institute of Information Technology, Hyderabad
Indraprastha Institute of Information Technology, Delhi
Manish Gupta
Microsoft India
Shaan Chopra
International Institute of Information Technology, Hyderabad
Source
via arXiv
Abstract

Social network and publishing platforms, such as Twitter, support the concept of verification. Verified accounts are deemed worthy of platform-wide public interest and are separately authenticated by the platform itself. There have been repeated assertions by these platforms about verification not being tantamount to endorsement. However, a significant body of prior work suggests that possessing a verified status symbolizes enhanced credibility in the eyes of the platform audience. As a result, such a status is highly coveted among public figures and influencers. Hence, we attempt to characterize the network of verified users on Twitter and compare the results to similar analysis performed for the entire Twitter network. We extracted the entire network of verified users on Twitter (as of July 2018) and obtained 231,246 user profiles and 79,213,811 connections. Subsequently in the network analysis, we found that the sub-graph of verified users mirrors the full Twitter users graph in some aspects such as possessing a short diameter. However, our findings contrast with earlier findings on multiple aspects, such as the possession of a power law out-degree distribution, slight dissortativity and a significantly higher reciprocity rate, as elucidated in the paper. Moreover, we attempt to gauge the presence of salient components within this sub-graph and detect the absence of homophily with respect to popularity, which again is in stark contrast to the full Twitter graph. Finally, we demonstrate stationarity in the time series of verified user activity levels. To the best of our knowledge, this work represents the first quantitative attempt at characterizing verified users on Twitter.

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