JOURNAL ARTICLE

Winter is here: Summarizing Twitter Streams related to Pre-Scheduled Events

Abstract

Pre-scheduled events, such as TV shows and sports games, usually garner considerable attention from the public. Twitter captures large volumes of discussions and messages related to these events, in real-time. Twitter streams related to pre-scheduled events are characterized by the following: (1) spikes in the volume of published tweets reflect the highlights of the event and (2) some of the published tweets make reference to the characters involved in the event, in the context in which they are currently portrayed in a subevent. In this paper, we take advantage of these characteristics to identify the highlights of pre-scheduled events from tweet streams and we demonstrate a method to summarize these highlights. We evaluate our algorithm on tweets collected around 2 episodes of a popular TV show, Game of Thrones, Season 7.

Keywords:
Event (particle physics) Computer science Context (archaeology) STREAMS Volume (thermodynamics) Social media Data science World Wide Web History

Metrics

6
Cited By
0.46
FWCI (Field Weighted Citation Impact)
21
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Text Analysis Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Complex Network Analysis Techniques
Physical Sciences →  Physics and Astronomy →  Statistical and Nonlinear Physics
Digital Games and Media
Social Sciences →  Social Sciences →  Sociology and Political Science

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