Earticle

현재 위치 Home

Too Much Information – Trying to Help or Deceive? An Analysis of Yelp Reviews

첫 페이지 보기
  • 발행기관
    한국경영정보학회 바로가기
  • 간행물
    Asia Pacific Journal of Information Systems KCI 등재 SCOPUS 바로가기
  • 통권
    제33권 제2호 (2023.06)바로가기
  • 페이지
    pp.261-281
  • 저자
    Hyuk Shin, Hong Joo Lee, Ruth Angelie Cruz
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A432818

※ 기관로그인 시 무료 이용이 가능합니다.

5,700원

원문정보

초록

영어
The proliferation of online customer reviews has completely changed how consumers purchase. Consumers now heavily depend on authentic experiences shared by previous customers. However, deceptive reviews that aim to manipulate customer decision-making to promote or defame a product or service pose a risk to businesses and buyers. The studies investigating consumer perception of deceptive reviews found that one of the important cues is based on review content. This study aims to investigate the impact of the information amount of review on the review truthfulness. This study adopted the Information Manipulation Theory (IMT) as an overarching theory, which asserts that the violations of one or more of the Gricean maxim are deceptive behaviors. It is regarded as a quantity violation if the required information amount is not delivered or more information is delivered; that is an attempt at deception. A topic modeling algorithm is implemented to reveal the distribution of each topic embedded in a text. This study measures information amount as topic diversity based on the results of topic modeling, and topic diversity shows how heterogeneous a text review is. Two datasets of restaurant reviews on Yelp.com, which have Filtered (deceptive) and Unfiltered (genuine) reviews, were used to test the hypotheses. Reviews that contain more diverse topics tend to be truthful. However, excessive topic diversity produces an inverted U-shaped relationship with truthfulness. Moreover, we find an interaction effect between topic diversity and reviews’ ratings. This result suggests that the impact of topic diversity is strengthened when deceptive reviews have lower ratings. This study contributes to the existing literature on IMT by building the connection between topic diversity in a review and its truthfulness. In addition, the empirical results show that topic diversity is a reliable measure for gauging information amount of reviews.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Literature Review
2.1. Online Customer Reviews and Consumer Behavior
2.2. Deceptive Review
2.3. Information Manipulation Theory
2.4. Interpersonal Deception Theory
Ⅲ. Hypothesis Development
3.1. The effect of topic diversity on its truthfulness
3.2. The moderating role of a review’s ratings
Ⅳ. Data and Variables
4.1. Data description
4.2. Variables
Ⅴ. Results
5.1. Descriptive Statistics
5.2. Data Preprocessing and Number of Topics
Ⅵ. Discussion & Conclusions
6.1. Theoretical implications
6.2. Practical implications
6.3. Limitations and future research
Acknowledgments

키워드

Online Consumer Review Topic Distribution Deceptive Review Topic Modeling

저자

  • Hyuk Shin [ Ph.D. Candidate, Department of Business Administration, The Catholic University of Korea ]
  • Hong Joo Lee [ Professor, Department of Business Administration, The Catholic University of Korea ] Corresponding Author
  • Ruth Angelie Cruz [ Professor, Decision Sciences and Innovation at De La Salle University (DLSU), Manila ]

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국경영정보학회 [The Korea Society of Management information Systems]
  • 설립연도
    1989
  • 분야
    사회과학>경영학
  • 소개
    이 학회는 경영정보학의 연구 및 교류를 촉진하고 학문의 발전과 응용에 공헌함을 목적으로 합니다.

간행물

  • 간행물명
    Asia Pacific Journal of Information Systems
  • 간기
    계간
  • pISSN
    2288-5404
  • eISSN
    2288-6818
  • 수록기간
    1990~2026
  • 등재여부
    KCI 등재,SCOPUS
  • 십진분류
    KDC 325 DDC 658

이 권호 내 다른 논문 / Asia Pacific Journal of Information Systems 제33권 제2호

    피인용수 : 0(자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      페이지 저장