Personalized Advertisement in the Video Games Using Deep Social Network Sentiment Analysis

Abstract

In the past few years, integration of the advertising campaigns in the video games is growing rapidly. Targeted and personalized advertising can increase the impact of the adverts significantly. In personalized advertising the advert is especially designed to have maximum impact on specific consumers. The requirement for personalized advertising is knowing individual consumers in details and to design the adverts based on the preferences of individual consumers. This knowledge can be extracted from the online behaviour of the video game players in social networks. In this paper, a framework for extraction of personal preferences of the video game players from their online activities in the social networks is proposed. The proposed framework uses deep neural network based sentiment analysis of the writings of the video game players in order to provide personalized knowledge for targeted advertising in the video game environments. These advertisements can be in form of brand integration or through the line advertisement in the video games. The proposed framework can improve the impact of the adverts in the video games and facilitate the personalization of the advertising in the video game environments.