Personalizing content: Via algorithm, Via social network

First a brief technical explanation: the Personalized Content approach uses a very similar technique to spam detection software. The idea is that everyone has their own pattern of reading. To recognize your pattern, Personalized Content services omit stopwords and extract keywords from the news you read – then use Bayesian Statistical analysis to predict what kind of news you will like or dislike in future….Personalized news has a couple of main attractions. Theoretically, if your news is personalized then it’s not as vulnerable to gaming as the power of masses approach. Plus people are getting busier everyday, so personalized news has a strong appeal as a potential solution for information overload.

Visit the Read/Write Web to explore personalized news, with commentary from Digital Alchemy. Please contribute your knowledge of “Personalized News” as well as “Power of Masses” to the Whats New Media Wiki.

Previously from WNM:
The Politics of the Internet: for better or worse?
Semantic Newscasting
Custom Search
Reporting down, aggregation up. Customization unseats localization.
Rumor Aggregation: Blog buzz and market effects
Just me and my algorithm

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Filed under A democratic medium?, Blogosphere, Connection/Isolation, Search, Social Media, Technology, our Mirror, The Politics of New Media, The Semantic Web, Tools, Ubiquity, Virtual Communities, web 2.0, When New Meets Old

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