The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams
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.
- Publication:
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arXiv e-prints
- Pub Date:
- January 2017
- DOI:
- 10.48550/arXiv.1701.04039
- arXiv:
- arXiv:1701.04039
- Bibcode:
- 2017arXiv170104039G
- Keywords:
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- Computer Science - Information Retrieval;
- Computer Science - Computation and Language
- E-Print:
- To appear in JASIST