By Randy Farmer, Bryce Glass
What do Amazon's product stories, eBay's suggestions rating method, Slashdot's Karma procedure, and Xbox Live's Achievements have in universal? They're all examples of profitable acceptance platforms that permit buyer web content to regulate and current consumer contributions so much successfully. This e-book exhibits you the way to layout and advance attractiveness platforms on your personal websites or internet functions, written by way of specialists who've designed internet groups for Yahoo! and different renowned sites.
Building internet popularity Systems is helping you ask the tough questions on those underlying mechanisms, and why they're severe for any association that attracts from or relies on user-generated content material. It's essential for process architects, product managers, neighborhood help employees, and UI designers.
* Scale your recognition procedure to address an overpowering influx of person contributions
* make certain the standard of contributions, and study why a few are extra worthy than others
* familiarize yourself with assorted types that inspire first class contributions
* notice tips of moderation and the way to stamp out the worst contributions speedy and successfully
* interact individuals and gift them in a manner that will get them to come
* research a case research in keeping with real attractiveness deployments at industry-leading social websites, together with Yahoo!, Flickr, and eBay
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Additional info for Building Web Reputation Systems
Quantitative or numeric claims Numeric or quantitative scores are what most people think of as reputation, even if they are displayed in a stylized format such as letter grades, thumbs, stars, or percentage bars. Since computers handle numbers easily, most of the complexity of reputation systems has to do with managing these score classes. Examples of common numerical score classes are accumulators, votes, segmented enumerations (that is, stars), and roll-ups such as averages and rankings. Qualitative claims Any reputation information that can’t be readily parsed by software is called qualitative, but such information plays a critical role in helping people determine the value of the target.
The Abusive Content Score process uses one external variable: WebReputation. This variable is stored in a reputation statement with the same target IP address as was provided with the flag input message. The AbuseScore starts at 0 and is increased by the value of Flag multiplied by WebReputation. The system stores the score in a reputation statement with an aggregate source, numeric score type, and the comment identifier as the target, then passes the statement in a message to the Is Abusive? process.
Will people come to your site and post great content because… • • • • They crave attention? It’s intrinsically rewarding to them in some way? They expect some monetary reward? They’re acting altruistically? In reality, members of your community will act (and act out) for all of these reasons and more. And the better you can understand why they do what they do, the better you can fine-tune your reputation system to reflect the real desires of the people that it represents. We’ll talk more about your community members and their individual motivations in Chapter 5, but we’ll generalize about them a bit here.