Predicting user behavior in electronic markets based on personality-mining in large online social networks

Volume: 27, Issue: 3, Pages: 247 - 265
Published: Aug 1, 2017
Abstract
Determining a user’s preferences is an important condition for effectively operating automatic recommendation systems. Since personality theory claims that a user’s personality substantially influences preference, I propose a personality-based product recommender (PBPR) framework to analyze social media data in order to predict a user’s personality and to subsequently derive its personality-based product preferences. The PBRS framework will be...
Paper Details
Title
Predicting user behavior in electronic markets based on personality-mining in large online social networks
Published Date
Aug 1, 2017
Volume
27
Issue
3
Pages
247 - 265
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