Dear All,
My name is Avanidhar Chandrasekaran (http://en.wikipedia.org/wiki/User_talk:Avanidhar).
I work with GroupLens Research at the University of Minnesota, Twin Cities. As part of my research, I am involved in analyzing the usefulness and Necessity of author reputation in Wikipedia.
In lieu of this, I have simulated an Interface to color words in an article based on their Age.
Being experienced contributors to Wikipedia, I invite you to participate in this study, which involves the following.
1. Please visit the following Instances of wikipedia and evaluate the interface components which have been incorporated into each of them. Each of these use their own algorithm to color text.
a) The Wikitrust project
http://wiki-trust.cse.ucsc.edu/index.php/Main_Page
b) The Wiki-reputation project at Grouplens research
http://wiki-reputation.cs.umn.edu/index.php/Main_Page
2) Once you have evaluated the two interfaces, kindly complete this survey on Wikipedia quality
http://www.surveymonkey.com/s.aspx?sm=hagN5S1JZHxH6pF9SmXkkA_3d_3d
We hope to get your valuable feedback on these interfaces and how Wikipedia article quality can be improved.
Thanks for your time
Avanidhar Chandrasekaran,
GroupLens Research, University of Minnesota
Dear All,
if you go to http://wiki-trust.cse.ucsc.edu/index.php/Main_Page and click on *Random Page*, you can explore that Wikipedia demo more. Our trust is function both of the text "age" (how many times it has been revised), but also of the reputation of the revisors.
Let me also point out that our code base has much evolved since then. In particular, the latest release of WikiTrust adds:
- Author tracking. Hover over a word in the "check text" tab, and the author is displayed in a pop-up window. - Origin tracking. Click on a (non-link) word, and you are sent to the diff where the word was introduced. - Vote button. If you are logged in, and you agree with the information displayed in the "check text" tab, you can vote for its correctness, and the revision text will gain trust as a consequence.
We do not have a whole-wikipedia demo of that so far, but you can find various examples linked from http://trust.cse.ucsc.edu/WikiTrust . Some of those examples are mirrors of existing wikis (from dumps), but visit our very own Cookiwiki, which we set up to experiment:
- www.cookiwiki.org
Register, and edit a page, browse around, etc. Yes, there is not a lot of content, but you can experiment with the interface. Come on, everybody knows at least one recipe, and we welcome even one for hard-boiled eggs!
Finally, do you have your own wiki? Then just download our codehttp://trust.cse.ucsc.edu/WikiTrustand give it a try. If you follow the link for a tarballhttp://code.google.com/p/wikitrust/downloads/list, you can download a tarball which contains a statically-linked executable for linux (and the source code for any OS), so installation is easy.
Luca
On Wed, Nov 19, 2008 at 12:12 PM, avani@cs.umn.edu wrote:
Dear All,
My name is Avanidhar Chandrasekaran (http://en.wikipedia.org/wiki/User_talk:Avanidhar).
I work with GroupLens Research at the University of Minnesota, Twin Cities. As part of my research, I am involved in analyzing the usefulness and Necessity of author reputation in Wikipedia.
In lieu of this, I have simulated an Interface to color words in an article based on their Age.
Being experienced contributors to Wikipedia, I invite you to participate in this study, which involves the following.
- Please visit the following Instances of wikipedia and evaluate the
interface components which have been incorporated into each of them. Each of these use their own algorithm to color text.
a) The Wikitrust project
http://wiki-trust.cse.ucsc.edu/index.php/Main_Page
b) The Wiki-reputation project at Grouplens research
http://wiki-reputation.cs.umn.edu/index.php/Main_Page
- Once you have evaluated the two interfaces, kindly complete this survey
on Wikipedia quality
http://www.surveymonkey.com/s.aspx?sm=hagN5S1JZHxH6pF9SmXkkA_3d_3d
We hope to get your valuable feedback on these interfaces and how Wikipedia article quality can be improved.
Thanks for your time
Avanidhar Chandrasekaran,
GroupLens Research, University of Minnesota
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