On discovering bucket orders from preference data
Sreyash Kenkre, Arindam Khan, et al.
SDM 2011
Various industries are turning to social media to identify key influencers on topics of interest. Following this trend, the All England Lawn Tennis and Croquet Club (AELTC) is keen to analyze the 'social pulse' around the famous Wimbledon Championships. IBM developed and deployed social influence analysis capability for AELTC during the 2014 edition of the Championship. The design and implementation of influence analysis technology in the real world involves several challenges. In this paper, we define various functional and usability criteria that social influence scores should satisfy, and propose a multi-dimensional definition of influence that satisfies these criteria. We highlight the need to identify both all-time influencers and recent influencers, and track user influences over multiple time-scales for this purpose. We also stress the importance of aspect-specific influence analysis, and investigate an approach that uses an aspect hierarchy that annotates tweets with topics or aspects before analyzing them for influence. We also describe interesting insights discovered by our tool and the lessons that we learnt from this engagement.
Sreyash Kenkre, Arindam Khan, et al.
SDM 2011
Amit Dhurandhar, Bruce Graves, et al.
KDD 2015
Ermyas Abebe, Yining Hu, et al.
ICBC 2021
Guo-Jun Qi, Charu Aggarwal, et al.
KDD 2015