Chapter

Database Systems for Adanced Applications

Volume 6637 of the series Lecture Notes in Computer Science pp 390-401

Crowd-Powered TV Viewing Rates: Measuring Relevancy between Tweets and TV Programs

  • Shoko WakamiyaAffiliated withCarnegie Mellon UniversityGraduate School of Human Science and Environment, University of Hyogo
  • , Ryong LeeAffiliated withCarnegie Mellon UniversitySchool of Human Science and Environment, University of Hyogo
  • , Kazutoshi SumiyaAffiliated withCarnegie Mellon UniversitySchool of Human Science and Environment, University of Hyogo

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Abstract

Due to the advance of many social networking sites, social analytics by aggregating and analyzing crowds’ life logs are attracting a great deal of attention. In the meantime, there is an interesting trend that people watching TVs are also writing Twitter messages pertaining to their opinions. With the utilization of bigger and broader crowds over Twitter, surveying massive audiences’ lifestyles will be an important aspect of exploitation of crowd-sourced data. In this paper, for better TV viewing rates in the light of the evolving TV lifestyles beyond home environments, we propose a TV rating method by means of Twitter where we can easily find crowd voices relative to TV watching. In the experiment, we describe our exploratory survey to exploit a large amount of Twitter messages to populate TV programs and on-line video sites.

Keywords

TV Viewing Rates Micro-blogging Social Network