Hot Streaks on Social Media

TL;DR

This study analyzes Twitter user careers to identify patterns of impact, revealing that impactful content tends to cluster in time, with users experiencing 'hot streaks' of high impact, influenced by network, content, and activity factors.

Contribution

The paper uncovers the existence of hot streaks and temporal clustering in social media impact, providing insights into the dynamics of influence and virality on Twitter.

Findings

Impact is temporally clustered in user careers.

Users experience extended hot streaks of high impact.

Impact dynamics are linked to changes in network, content, and activity.

Abstract

Measuring the impact and success of human performance is common in various disciplines, including art, science, and sports. Quantifying impact also plays a key role on social media, where impact is usually defined as the reach of a user's content as captured by metrics such as the number of views, likes, retweets, or shares. In this paper, we study entire careers of Twitter users to understand properties of impact. We show that user impact tends to have certain characteristics: First, impact is clustered in time, such that the most impactful tweets of a user appear close to each other. Second, users commonly have 'hot streaks' of impact, i.e., extended periods of high-impact tweets. Third, impact tends to gradually build up before, and fall off after, a user's most impactful tweet. We attempt to explain these characteristics using various properties measured on social media, including the user's network, content, activity, and experience, and find that changes in impact are associated with significant changes in these properties. Our findings open interesting avenues for future research on virality and influence on social media.