Exploring time aware features in microblog to measure TV ratings

Joon Yeon Choeh, Hong Joo Lee, Eugene J.S. Won

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

In measuring TV ratings, some features can be significant at a certain time, whereas they can be meaningless in other time periods. Because the importance of features can change, a model capturing the time changing relevance is required in order to estimate TV ratings more accurately. Therefore, we focus on the time-awareness of features, particularly the time when the words of tweets are used. We develop a correlation-based, time-aware feature selection algorithm which finds the optimal time period of each feature, and the estimation method using e-SVR based on top-n-features that are ordered by correlation. We identify that the correlation values between features and TV ratings vary according to the time of postings - before and after the broadcast time. This implies that the relevance of features can change according to the time of the tweets. Experimental results indicate that the proposed method has better performance compared with the method based on count-based features. This result implies that understanding the time-dependency of features can be helpful in improving the accuracy of measuring TV ratings.

Original languageEnglish
Pages (from-to)2810-2813
Number of pages4
JournalIEICE Transactions on Information and Systems
VolumeE97D
Issue number10
DOIs
StatePublished - 1 Oct 2014

Bibliographical note

Publisher Copyright:
Copyright © 2014 The Institute of Electronics, Information and Communication Engineers.

Keywords

  • Microblog
  • Time awareness
  • TV ratings

Fingerprint

Dive into the research topics of 'Exploring time aware features in microblog to measure TV ratings'. Together they form a unique fingerprint.

Cite this