ORGANIZING THE CROWD AT YELP by David Andrew Askay A dissertation submitted to the ...

198 Pages·2013·6.46 MB·English

CROWD CONTROL: ORGANIZING THE CROWD AT YELP

by

David Andrew Askay

A dissertation submitted to the faculty of
The University of North Carolina at Charlotte
in partial fulfillment of the requirements
for the degree of Doctor of Philosophy in
Organizational Science

Charlotte

2013

Approved by:

______________________________
Dr. Loril Gossett

______________________________
Dr. Anita Blanchard

______________________________
Dr. Cliff Scott

______________________________
Dr. Min Jiang
ii

©2013
David Andrew Askay
ALL RIGHTS RESERVED
iii
ABSTRACT

DAVID ANDREW ASKAY. Crowd control: organizing the crowd at yelp.
(Under the direction of DR. LORIL GOSSETT)

This dissertation investigates how businesses are able to align the collective
actions of a disconnected crowd with the strategic goals of the organization. I examined
this questions within the context of the business review website Yelp through a
quantitative analysis of nearly 60,000 business reviews, 17 in-depth qualitative interviews
with reviewers, and a two-year ethnography. Interpreting the results of this data within
the framework of the collective action space (Bimber, Flanagin, & Stohl, 2012) indicates
that Yelp is able to manage the contributions of a relatively small subset of reviewers
through the Yelp Elite Squad. Rather than simply motivating more reviews, the Elite
Squad encouraged reviewers to interact more personally with other reviewers and accept
increased institutional engagement with Yelp. In encouraging members of the crowd to
produce online reviews within this context, Yelp was able to use organizational culture as
a control strategy for encouraging Elite reviewers to adopt a pre-mediated reviewing
approach to their reviews. This increased the frequency of moderate reviews and
decreased the frequency of extreme reviews. This behavior ultimately furthers the
organizational goals of Yelp, as moderate reviews are considered to be more helpful for
reviews of businesses. Finally, implications for crowdsourcing, big data analysis, and
theory are discussed.
iv
ACKNOWLEDGEMENTS

This dissertation is culmination of five years in the interdisciplinary
Organizational Science program at the University of North Carolina at Charlotte. I am
grateful to faculty across the departments of Communication Studies, Psychology, and
Sociology and the Belk College of Business for patiently helping me to understand
organizations and organizing from the perspective of these disciplines. I want to also
thank the students of the Organizational Science program, who have frequently acted as
sounding boards for my ideas and as sources of inspiration. Also, this study would not
have been possible without the interview participants, who graciously provided me with
their time and trust so that I was able to pursue this research project.
Without the guidance and support for my committee members, this dissertation
would not have been possible. Dr. Loril Gossett has tirelessly served as my advisor since
the first year of my graduate education, introduced me to the field of communication
studies, and chaired both my master’s thesis and this dissertation. Over five years, she has
consistently challenged me to critically think about my research and somehow always
knew precisely the right questions to ask to get me there. I am thankful for her years of
enthusiastic mentoring, without which I would not have been here. Dr. Anita Blanchard
has also provided me with invaluable guidance in this dissertation and in my graduate
studies, developing my writing abilities and challenging me to situate my findings in
other domains. Dr. Min Jiang opened up another world of references that I would not
have otherwise been exposed to, introducing me even to the theoretical framework used
in this dissertation. Dr. Cliff Scott developed this dissertation by asking insightful
v
questions that challenged me to think about the larger theoretical issues of participation
and membership.
Also helping me to formulate this dissertation were the immeasurable
contributions from students and scholars from several doctoral developmental initiatives.
I want to acknowledge the students, scholars, and organizers of the Internet Research
12.0 Doctoral Colloquium, the 2012 Academy of Management OCIS Division Doctorial
Consortium, the 2012 Consortium for the Science of Sociotechnical Systems Summer
Research Institute, and the 2011 National Communication Association Doctoral Honors
Seminar. These individuals provided insight and direction during the development of this
dissertation.
Finally, I want to acknowledge my friends and family who have supported me
throughout graduate school. Despite the distance from moving so far from home in
California, my family provided me with love, money, and understanding that made this
dissertation possible. In particular I want to acknowledge my brother, Sean Askay, whose
guidance in developing Python code enabled me to acquire much of the data needed to
answer my research question. Additionally I am grateful to Bethany Ritter, who has
supported me in so many ways during this dissertation. I thank you for your enduring
patience and understanding during the late nights that I worked on this project, your
interest in listening to and thinking through ideas with me, and your willingness to
proofread this dissertation. I will always be thankful for you. Lastly, my friends both near
and far have given me much moral support and made my time in graduate school an
enjoyable experience. Thank you all.
vi
TABLE OF CONTENTS

CHAPTER I: INTRODUCTION 1
1.1 Rationale for Research 3
1.2 Purpose of the Dissertation 6
1.3 Context of the Dissertation 7
1.4 Organization of the Dissertation 8
CHAPTER II: LITERATURE REVIEW 11
2.1 Part I: The Crowd 12
2.1.1 Online Reviews 14
2.1.2 Search versus Experience Goods 14
2.1.3 Distribution of Reviews 16
2.1.4 Business Interests in Crowdsourced Platforms 19
2.1.5 Summary of Crowdsourced Online Reviews 21
2.2 Part II: Crowdsourcing as Collective Action 22
2.2.1 Collective Action 22
2.2.1.1 Civic Associations and Interest Groups 23
2.2.1.2 Informal Networks and Crowds 24
2.2.2 Crowdsourcing as Collective Action 25
2.2.3 Contemporary Collective Action 25
2.2.4 Collective Action Space 28
2.2.4.1 Interaction 29
2.2.4.2 Engagement 30
2.2.4.3 Quadrants of the Collective Action Space 32
vii
2.2.4.3.1 Traditionalists 33
2.2.4.3.1 Enthusiasts 34
2.2.4.3.1 Minimalists 34
2.2.4.3.1 Individualists 35
2.2.6 Summary of Crowdsourcing as Collective Action 38
2.2.7 Research Question 39
CHAPTER III: METHODOLOGY 40
3.1 Research Site 41
3.2 Description of Yelp 43
3.2.1 How Yelp Makes Money 43
3.2.2 Yelp’s Organizational Structure 45
3.2.2.1 Yelp, Inc. 45
3.2.2.2 Reviewers (The Crowd) 45
3.2.2.3 Scouts 45
3.2.2.4 Elite Squad 46
3.2.2.5 Community Manager 48
3.2.3 Structure of Yelp Website 48
3.2.3.1 Localized Homepage 48
3.2.3.2 Review of the Day 49
3.2.3.3 Business Reviews 50
3.2.3.4 Contributing a Review 52
3.2.3.5 Review Filter 53
3.2.3.6 Flagging Content 54
viii
3.2.3.7 Reviewer Profiles 54
3.2.3.8 Compliments 55
3.2.3.9 Talk Forums 56
3.2.3.10 Events 58
3.2.3.11 Yelp Elite Squad Page 60
3.2.3.12 Mobile Application 63
3.2.4 Summary of Yelp’s Structure 63
3.3 Philosophy of Science 64
3.4 Research Design 67
3.4.1 Quantitative Data Collection 68
3.4.2 Qualitative Interviews 69
3.4.2.1 Recruitment 70
3.4.2.2 Interviews 72
3.4.3 Organizational Documents 73
3.4.4 Data Analysis 73
3.4.5 Coding 76
CHAPTER IV: QUANTITATIVE RESULTS 78
4.1 Descriptive Statistics 79
4.1.1 Descriptive Statistics of Community Managers and Scouts 79
4.1.2 Descriptive Statistics for All Reviews 80
4.1.3 Descriptive Statistics of Elite and Non-Elite Reviewers 81
4.1.3.1 Descriptive Statistics of Non-Elite Reviewers 82
4.1.3.2 Impact of Filtered Reviews on Non-Elite Distribution 83
ix
4.1.3.3 Descriptive Statistics of Elite Reviewers 84
4.1.4 Impact of Elite Reviews on Overall Distribution 85
4.2 Mann-Whitney U-Test and Kolmogorov-Smirnov Test 87
4.2.1 Comparing Distribution of Elite versus Non-Elite Reviews 87
4.2.2 Comparing Distribution of Elite versus Scout Reviews 88
4.3 Chi-Square 88
4.4 Summary of Quantitative Analysis 89
CHAPTER V: QUALITATIVE FINDINGS 90
5.1 Being Yelpy 91
5.1.1 Balanced Reviews 92
5.1.1.1 Elite Bumping Up Reviews 94
5.1.1.2 Non-Elite Overcorrecting Reviews 94
5.1.2 Detailed Reviews 95
5.2 How Yelp Enables Balanced and Detailed Reviews 97
5.2.1 Organizational Messages 97
5.2.2. Technological Features 97
5.2.3 Community Enforcement 99
5.2.3.1 Yelp Jail 100
5.3 Eliminating Anonymity 103
5.3.1 Real Photo and Name 103
5.3.1.1 Recognized by Elites 105
5.3.1.2 Recognized by Personal Contacts 106
5.3.1.3 Recognized by a Business 107
x
5.3.1.4 Anonymity and Non-Elites 109
5.4 How Yelp Encourages Eliminating Anonymity 110
5.4.1 Vetting by the Community 110
5.4.2 Connecting Personal Contacts 112
5.4.2 Local Reviews 113
5.4.3 Libel 114
5.5 Peer Pressure 116
5.6 How Yelp Encourages Peer Pressure 118
5.7 Reviewing Extreme versus Reviewing Everything 120
5.7.1 Non-Elite Review Extreme Experiences 120
5.7.2 Elites Review Everything 122
5.8 How Yelp Encourages Elites to Review Everything 124
5.8.1 Monitoring by the Community Manager 124
5.8.2 Ambiguous Criteria for Elite Status 127
5.8.3 Organizational Messages 128
5.9 The Elite Squad: Everything to Everyone 130
5.9.1 Status-Seeking 131
5.9.2 Instrumental Rewards 133
5.9.3 Social Rewards 135
5.9.4 Soapbox 137
5.10 Methodological Rigor 138
5.11 Summary 140
CHAPTER VI: DISCUSSION 141