# The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams

## TL;DR

This paper investigates how online collective memories form by analyzing the emergence patterns of entities in social media and news streams before their inclusion in Wikipedia, revealing bursty and delayed emergence behaviors.

## Contribution

It introduces a large-scale analysis of nearly 80,000 entities in online text streams, identifying distinct emergence patterns leading to collective memory formation.

## Key findings

- Entities show bursty emergence patterns without prior mention.
- Some entities have delayed emergence with periods of inactivity.
- Emergence patterns help understand online collective memory formation.

## Abstract

We study how collective memories are formed online. We do so by tracking entities that emerge in public discourse, that is, in online text streams such as social media and news streams, before they are incorporated into Wikipedia, which, we argue, can be viewed as an online place for collective memory. By tracking how entities emerge in public discourse, i.e., the temporal patterns between their first mention in online text streams and subsequent incorporation into collective memory, we gain insights into how the collective remembrance process happens online. Specifically, we analyze nearly 80,000 entities as they emerge in online text streams before they are incorporated into Wikipedia. The online text streams we use for our analysis comprise of social media and news streams, and span over 579 million documents in a timespan of 18 months. We discover two main emergence patterns: entities that emerge in a "bursty" fashion, i.e., that appear in public discourse without a precedent, blast into activity and transition into collective memory. Other entities display a "delayed" pattern, where they appear in public discourse, experience a period of inactivity, and then resurface before transitioning into our cultural collective memory.