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From Live TV Events to Twitter Status Updates - a Study on Delays

  • Rita Oliveira
  • Pedro Almeida
  • Jorge Ferraz de Abreu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 689)

Abstract

This paper reports on a preliminary study of a research project that proposes a new integration between the activity generated in social networks and television programs. The research team aimed to develop a tool that automatically creates summaries of popular TV programs based on the buzz (peaks of Twitter status updates) on Twitter, and, therefore, having as an editorial criterion the related status updates on Twitter.

In a preparatory stage of the project, in order to understand the best correlation between the sources of information and the foreseen narrative dynamics of the TV summaries, the research team analyzed four TV programs (two football matches and two entertainment programs) by means of manual observation and comparing it with the data gathered by a data mining Application Programming Interface (API) (being created by one of the research team partners), that would handle the detection and extraction of the activity on Twitter related to television TV programs, identifying the moments of greater buzz. The decision on these genres of TV programs was made based on Portuguese TV audience rankings (usually with higher audiences than other genres) and, also, in a previous analysis made through the data mining API, which confirmed the higher buzz on Twitter related to this kind of TV programs. This analysis provided important data to determine the elapsed time between the real events and the correlated comments on Twitter and the most optimized duration for a typical segment (a short video clip of an event) to be included in the automatically created summaries. This information provides support to better understand the time and narrative correlation between TV programs and related Twitter activity.

Keywords

TV highlights Twitter updates Delays TV programs TV summary 

Notes

Acknowledgements

Authors are grateful to the project partners: Altice Labs and Telecommunications Institute.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of Aveiro-DigimediaAveiroPortugal

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