02-Based on kuber socialbadge

Source: Internet
Author: User

Zheng Zhe 201005 is affiliated with section 02. Technical pre-Research

[Note: The old document last year has been written. Previous article titled 01-a good example of learning kuber's socialbadge | 02. Pre-developed technology | social

Kuber's socialbadge can be obtained based on the given email address, Twitter user Homepage Address, and Google user profile address:

    • This person's Google Reader shared items URL (if any );
    • Who the person follows (followings in Twitter and Google Reader ).

 

Test connection:

1. My Google Profile link: http://kuber.appspot.com/social/search? Q = www.google.com % 2 fprofiles % 2 fzhengyun

2. My Twitter link: http://kuber.appspot.com/social/search? Q = Twitter.com % 2 fzhengyun

 

On this basis, I hope:

1. a Twitter account or Google profile address is given to a number of high-weight users of social media. This user set is called:Targetusers.

2. Obtain the attention list of each user (which nodes are followed by this user) respectively. This user set is called:Followingnodes. After the merge operation is repeated, a total node set is obtained, which is called:Watchlist.

3. Traverse each node in the Watchlist:

Check whether the corresponding web service is supported. We currently tentatively support Google Reader shared items, Twitter, and delicious (all of which have links or short messages ). Determine whether the data is accessible. If the other party does not have the permission (the access will get a 403 Status Code), ignore it.

Asynchronously collect the data of the node. Every article shared by googlereader is collected.Article. If it is Twitter, it will collect RT messages and messages with HTTP links. If it is delicious, collect its favorite links.

4. For every user of targetusers, calculate the world of interest (followingnodes) one by one:

    • Share the most articles or links.Algorithm;
    • The most frequently-forwarded Twitter messages follow the receng's algorithm.

 

Purpose:

    • Check whether personalized computing can meet the reading requirements in the current social media use in China.
    • Observe whether the popularity and popularity of the world they are concerned about are valuable for the heavily collected social media users, for average users.

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