Verfügbarkeit: Building web reputation systems

Building web reputation systems: [ratings, reviews & Karma to keep your community healthy]

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Bibliographische Detailangaben
Hauptverfasser:	Farmer, F. Randall (VerfasserIn), Glass, Bryce (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	Sebastopol, CA O'Reilly [u.a.] 2010
Ausgabe:	1. ed.
Schlagworte:	Gestaltung Website
Online-Zugang:	Inhaltsverzeichnis Klappentext
Beschreibung:	XVIII, 316 S. Ill.
ISBN:	9780596159795

Internformat

MARC


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Datensatz im Suchindex

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adam_text	Building Web Reputation Systems What do Amazon s product reviews, eBay s feedback score system, Slashdot s karma system, and Xbox Live s Achievements have in common? They re all examples of successful reputation systems that enable consumer websites to manage and present user contributions most effectively. This book shows you how to design and develop reputation systems for your own sites or web applications, written by experts who have designed web communities for Yahoo! and other prominent sites. Building Web Reputation Systems helps you ask the hard questions about these underlying mechanisms, and understand why they re critical for any organization that draws from or depends on user- generated content. It s a must-have for system architects, product managers, community support staff, and UI designers. Scale your reputation system to handle an overwhelming inflow of user contributions Determine the quality of contributions, and learn why some are more useful than others Become familiar with different models that encourage first-class contributions Discover tricks of moderation and how to stamp out the worst contributions quickly and efficiently Engage contributors and reward them in a way that gets them to return Examine a case study based on actual reputation deployments at industry-leading social sites, including Yahoo!, Flickr, and eBay Table of Contents Preface Part I. Reputation Defined and Illustrated Reputation Systems Are Everywhere ....................... An Opinionated Conversation People Have Reputations, but So Do Things Reputation Takes Place Within a Context We Use Reputation to Make Better Decisions The Reputation Statement Explicit: Talk the Talk Implicit: Walk the Walk The Minimum Reputation Statement Reputation Systems Bring Structure to Chaos Reputation Systems Deeply Affect Our Lives Local Reputation: It Takes a Village Global Reputation: Collective Intelligence FICO: A Study in Global Reputation and Its Challenges Web FICO? Reputation on the Web Attention Doesn t Scale There s a Whole Lotta Crap Out There People Are Good. Basically. The Reputation Virtuous Circle Who s Using Reputation Systems? Challenges in Building Reputation Systems Related Subjects Conceptualizing Reputation Systems 2. A (Graphical) Grammar for Reputation ........... The Reputation Statement and Its Components Reputation Sources: Who or What Is Making a Claim? 23 Reputation Claims: What Is the Target s Value to the Source? On What Scale? 24 Reputation Targets: What (or Who) Is the Focus of a Claim? 25 Molecules: Constructing Reputation Models Using Messages and Processes 26 Messages and Processes 26 Reputation Model Explained: Vote to Promote 28 Building on the Simplest Model 29 Complex Behavior: Containers and Reputation Statements As Targets 30 Solutions: Mixing Models to Make Systems 33 From Reputation Grammar to... 35 Part II. Extended Elements and Applied Examples 3. Building Blocksand Reputation Tips ...................................... 39 Extending the Grammar: Building Blocks 39 The Data: Claim Types 39 Processes: Computing Reputation , 46 Routers: Messages, Decisions, and Termination 54 Practitioner s Tips: Reputation Is Tricky 57 The Power and Costs of Normalization 57 Liquidity: You Won t Get Enough Input 58 Bias, Freshness, and Decay 60 Implementer s Notes 64 Making Buildings from Blocks 65 4. Common Reputation Models .............................................67 Simple Models 67 Favorites and Flags 68 This-or-That Voting 69 Ratings 70 Reviews 70 Points 71 Karma 72 Combining the Simple Models 74 User Reviews with Karma 75 eBay Seller Feedback Karma 78 Flickr Interestingness Scores for Content Quality 82 When and Why Simple Models Fail 89 Party Crashers 89 Keep Your Barn Door Closed (but Expect Peeking) 91 Reputation from Theory to Practice 94 Part III. Building Web Reputation Systems 5. Planning Your System s Design ........................................... 97 Asking the Right Questions 97 What Are Your Goals? 98 Content Control Patterns 102 Incentives for User Participation, Quality, and Moderation 111 Consider Your Community 121 Better Questions 123 6. Objects, Inputs, Scope, and Mechanism ...................................125 The Objects in Your System 125 Architect, Understand Thyself 126 What Makes for a Good Reputable Entity? 129 Determining Inputs 131 User Actions Make Good Inputs 131 But Other Types of Inputs Are Important, Too 134 Good Inputs 135 Common Explicit Inputs 136 Common Implicit Inputs 143 Constraining Scope 146 Context Is King 146 Limit Scope: The Rule of Email 148 Applying Scope to Yahoo! EuroSport Message Board Reputation 149 Generating Reputation: Selecting the Right Mechanisms 150 The Heart of the Machine: Reputation Does Not Stand Alone 151 Common Reputation Generation Mechanisms and Patterns 151 Practitioner s Tips: Negative Public Karma 161 Draw Your Diagram 163 7. Displaying Reputation ................................................. 165 How to Use a Reputation: Three Questions 165 Who Will See a Reputation? 166 To Show or Not to Show? 166 Personal Reputations: For the Owner s Eyes Only 169 Personal and Public Reputations Combined 171 Public Reputations: Widely Visible 171 Corporate Reputations Are Internal Use Only: Keep Them Hush-hush 172 How Will You Use Reputation to Modify Your Site s Output? 172 Reputation Filtering 173 Reputation Ranking and Sorting 173 Reputation Decisions 174 Content Reputation Is Very Different from Karma 175 Content Reputation 176 Karma 176 Reputation Display Formats 178 Reputation Display Patterns 180 Normalized Score to Percentage 180 Points and Accumulators 182 Statistical Evidence 183 Levels 185 Ranked Lists 189 Practitioner s Tips 192 Leaderboards Considered Harmful 192 Going Beyond Displaying Reputation 195 8. Using Reputation: The Good, The Bad, and the Ugly ........................ 197 Up with the Good . 198 Rank-Order Items in Lists and Search Results 199 Content Showcases 200 Down with the Bad 204 Configurable Quality Thresholds 205 Expressing Dissatisfaction 206 Out with the Ugly 207 Reporting Abuse 207 Teach Your Users How to Fish 209 Inferred Reputation for Content Submissions 210 A Private Conversation 212 Course-Correcting Feedback 213 Reputation Is Identity 214 On the User Profile 216 At the Point of Attribution 219 To Differentiate Within Listings 220 Putting It All Together 221 9. Application Integration, Testing, and Tuning ..............................223 Integrating with Your Application 223 Implementing Your Reputation Model 223 Rigging Inputs 225 Applied Outputs 225 Beware Feedback Loops! 226 Plan for Change 226 Testing Your System 227 Bench Testing Reputation Models 228 Environmental (Alpha) Testing Reputation Models 229 Predeployment (Beta) Testing Reputation Models 230 Tuning Your System 232 Tuning for ROI: Metrics 232 Tuning for Behavior 236 Tuning for the Future 241 Learning by Example 241 10. Case Study: Yahoo! Answers Community Content Moderation ................243 What Is Yahoo! Answers? 243 A Marketplace for Questions and Yahoo! Answers 244 Attack of the Trolls 245 Built with Reputation 248 Avengers Assemble! 248 Initial Project Planning 249 Setting Goals 249 Who Controls the Content? 250 Incentives 250 The High-Level Project Model 251 Objects, Inputs, Scope, and Mechanism 252 The Objects 252 Limiting Scope 254 An Evolving Model 255 Displaying Reputation 268 Who Will See the Reputation? 268 How Will the Reputation Be Used to Modify Your Site s Output? 268 Is This Reputation for a Content Item or a Person? 268 Using Reputation: The...Ugly 269 Application Integration, Testing, and Tuning 270 Application Integration 270 Testing Is Harder Than You Think 270 Lessons in Tuning: Users Protecting Their Power 271 Deployment and Results 273 Operational and Community Adjustments 274 Adieu 276 A. The Reputation Framework .............................................279 B. Related Resources .................................................... 303 Index .....................................................................307
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author	Farmer, F. Randall Glass, Bryce
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discipline	Informatik Wirtschaftswissenschaften
edition	1. ed.
format	Book
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title	Building web reputation systems [ratings, reviews & Karma to keep your community healthy]
title_auth	Building web reputation systems [ratings, reviews & Karma to keep your community healthy]
title_exact_search	Building web reputation systems [ratings, reviews & Karma to keep your community healthy]
title_full	Building web reputation systems [ratings, reviews & Karma to keep your community healthy] F. Randall Farmer and Bryce Glass
title_fullStr	Building web reputation systems [ratings, reviews & Karma to keep your community healthy] F. Randall Farmer and Bryce Glass
title_full_unstemmed	Building web reputation systems [ratings, reviews & Karma to keep your community healthy] F. Randall Farmer and Bryce Glass
title_short	Building web reputation systems
title_sort	building web reputation systems ratings reviews karma to keep your community healthy
title_sub	[ratings, reviews & Karma to keep your community healthy]
topic	Gestaltung (DE-588)4157139-3 gnd Website (DE-588)4596172-4 gnd
topic_facet	Gestaltung Website
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