DocumentCode
2921098
Title
Predicting short interval tracking polls with online social media
Author
Li Ho Leung ; Ng, Vincent T. Y. ; Shiu, Simon C. K.
Author_Institution
Dept. of Comput., Hong Kong Polytech. Univ., Hong Kong, China
fYear
2013
fDate
27-29 June 2013
Firstpage
587
Lastpage
592
Abstract
The of behavioral patterns in online social media are often reflecting the happenings in our society. These patterns, which can be considered as opinions, are often correlated with public opinion polling. However, many correlation analyses done previously were for subsequent discoveries and not being able to handle short interval polling opinions. For opinions obtained from tracking polling with short opinion collection interval, like rolling polling, it cannot perform well in tracing the latest trends. This paper describes an extended correlation model for such kind of polling in examining the correlation between opinion in online social media and the public opinion from tracking poll. It has been tested with a recent rolling polling and it outperformed the previous correlation models.
Keywords
correlation methods; social networking (online); behavioral patterns; extended correlation model; online social media; public opinion polling; rolling polling; short interval tracking polls prediction; short opinion collection interval; Blogs; Correlation; Data collection; Data models; Joining processes; Media; PSNR; online social media; opinion tracking; prediction; public polling;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Supported Cooperative Work in Design (CSCWD), 2013 IEEE 17th International Conference on
Conference_Location
Whistler, BC
Print_ISBN
978-1-4673-6084-5
Type
conf
DOI
10.1109/CSCWD.2013.6581027
Filename
6581027
Link To Document