Abstract

In this paper we developed a framework and a measure for news impact forecasting. We proved the viability of our impact forecasting approach using a SVM based forecaster on six months of NYT corpus - consisting of 16,852 articles. We experimented with different feature selection and ranking algorithms including standard frequency based methods, as well as a new method named ImpactRank. Our ImpactRank based forecaster performed as the best feature ranking technique while providing a graph suitable for browsing and identifying the most influential topics, entities and interrelationships going into its impact predictions.

Original languageEnglish (US)
Title of host publicationProceedings - SocialCom 2010
Subtitle of host publication2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust
Pages488-493
Number of pages6
DOIs
StatePublished - 2010
Event2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010 - Minneapolis, MN, United States
Duration: Aug 20 2010Aug 22 2010

Publication series

NameProceedings - SocialCom 2010: 2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust

Other

Other2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010
CountryUnited States
CityMinneapolis, MN
Period8/20/108/22/10

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems

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