Wiki + recommendation engine = Digg

"Digg adopts the user-driven
Driven), which sets a buffer for the news source. The news submitted by the user first enters this buffer, if there are enough readers who agree with the news (Digg uses a way similar to democratic voting
This process is called Digg). It will stand out from the buffer and appear on the Digg page. Otherwise, it will be squeezed out of the news source buffer. Intuitive
That is, Slashdot is controlled by the Administrator, while Digg authorizes the user. These two different news submission mechanisms derive different community cultures. Because of the high user autonomy, and
Effective integration of blogs and websites allows Digg to respond very quickly to the latest network information. For example, a new network service starts to issue invitations, and an important network service is updated,
A new product has been launched. Anyone can submit any interesting information to Digg (Information Input). Anyone can comment or vote on the information (Information Processing). Anyone can
Publish the information to your blog or website through Digg )."
-- Baidu encyclopedia

In the early days, Digg was actually a wiki. All the content was created by users. This is the essence of Digg and the biggest difference between Digg and the old news websites. In my opinion, the voting mechanism is more in order to provide a better user experience, so that users can feel that they are "taking the lead" (in fact, they do not use voting, it is also possible to rank news by clicking rate ).
The current Digg has added a recommendation engine. The recommendation system automatically analyzes users' voting behaviors, uses machine learning algorithms to discover users' preferences and habits, and then automatically recommends news that users may be interested in. In my opinion, this brand-new model is a huge step forward on the basis of Wiki. In the past, Digg or wiki, users are more like volunteers, while Digg is more like users are making transactions with websites. On the one hand, users are voting for news and contributing to this website. On the other hand, users are also able to gain benefits and find content they are interested in more easily. Users can not only benefit from their own behaviors, but also feel better interaction with the website.
In the past, Digg had some shortcomings. 1% to 2% of users could guide the entire social media news website. That is to say, a special group can easily manipulate social media news websites. This problem is easy to understand, because not all users have time to vote and are willing to contribute. However, in the new model, this problem may be mitigated. Because the user can feel that voting will generate value to himself.

Wiki + recommendation engine can be called the extension of Web2.0 or web3.0. However, the name is not important. What matters is that this model represents the future development direction.