Predicting short interval tracking polls with online social media

Ho Leung Li, Vincent To Yee Ng, Chi Keung Simon Shiu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationProceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2013
Pages587-592
Number of pages6
DOIs
Publication statusPublished - 19 Sep 2013
Event2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2013 - Whistler, BC, Canada
Duration: 27 Jun 201329 Jun 2013

Conference

Conference2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2013
Country/TerritoryCanada
CityWhistler, BC
Period27/06/1329/06/13

Keywords

  • online social media
  • opinion tracking
  • prediction
  • public polling

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

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