Evaluating Acceptance of Video Games using Convolutional Neural Networks for Sentiment Analysis of User Reviews

被引：1

作者：

Vieira, Augustode de Castro ^{[1
]}

Brandao, Wladmir Cardoso ^{[1
]}

机构：

[1] Pontificia Univ Catolica Minas Gerais, PUC Minas, Belo Horizonte, MG, Brazil

来源：

PROCEEDINGS OF THE 30TH ACM CONFERENCE ON HYPERTEXT AND SOCIAL MEDIA (HT '19) | 2019年

关键词：

Video Game; Game Acceptance; Sentiment Analysis; Opinion Mining; Machine Learning; Neural Network;

D O I：

10.1145/3342220.3344924

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Video game and interactive media are currently among the most profitable industries in the world. In this competitive marketing, game producers are interested in designing products with aspects that increase user acceptance, such as a well written story, stable servers for multiplayer games, and fluid combat mechanics. Although user-expressed feelings about game aspects seem to correlate with user acceptance, sentiment analysis is under-exploited for video games user acceptance evaluation. In this poster, we propose an approach to evaluate the user acceptance of video games by using convolutional neural networks for aspect-based sentiment analysis of user text reviews.

引用

页码：273 / 274

页数：2

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