A COMPUTER AIDED CONTENT ANALYSIS OF ONLINE REVIEWS

被引：2

作者：

Simmons, Lakisha L. ^{[1
]}

Conlon, Sumali ^{[2
]}

Mukhopadhyay, Surma ^{[2
]}

Yang, Jun ^{[3
]}

机构：

[1] Indiana State Univ, Terre Haute, IN 47809 USA

[2] Univ Mississippi, University, MS 38677 USA

[3] Univ Houston Victoria, Victoria, TX 77901 USA

来源：

JOURNAL OF COMPUTER INFORMATION SYSTEMS | 2011年 / 52卷 / 01期

关键词：

Computer aided text analysis; electronic word-of-mouth (eWOM); content analysis; movie reviews; WORD-OF-MOUTH; INFORMATION EXTRACTION; BOX-OFFICE; CHALLENGES; AMERICAN; DRIVE; POWER;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Published information extraction (IE) research generally discusses the technological improvement of IF software, yet little addresses the valuable application of such technology. IE and content analysis together enhance the rigor of qualitative research through computer based content analysis. We use CAINES to illustrate an effective application of IF and computer aided content analysis on eWOM reviews. CAINES is a system based on linguistic techniques that can extract and analyze online movie reviews. In this research we demonstrate how CAINES is able to analyze the most important factor a moviegoer considers when rating a movie online. CAINES extracted and analyzed movie reviews from 18 action and adventure movies consisting of 20,679 individual reviews. By using CAINES we were able to show that storylinc is most important to moviegoers and they tend to leave more positive than negative reviews. Our results also reveal that reviewers mainly discuss their personal evaluation of the movie, rather than discouraging or encouraging readers to see the movie.

引用

页码：43 / 55

页数：13

共 56 条

[41] Information extraction from research papers using conditional random fields [J].