Exploring Time Aware Features in Microblog to Measure TV Ratings

Joon Yeon CHOEH  Hong Joo LEE  Eugene J. S. WON  

IEICE TRANSACTIONS on Information and Systems   Vol.E97-D    No.10    pp.2810-2813
Publication Date: 2014/10/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2014EDL8036
Type of Manuscript: LETTER
Category: Office Information Systems, e-Business Modeling
time awareness,  microblog,  TV ratings,  

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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.