Research Article
Mining Community-Level Influence in Microblogging Network: A Case Study on Sina Weibo
(1) Input: , , , , , , | (2) Output: | (3) Select the users who are the last 10% of the login frequency and whose login | time interval is greater than 7 days, into the set | (4) Put the users with the top 10% of the diffusing advertisement frequency into | the set | (5) Select the users who are the last 10% of the number of user’ theme | information into the set | (6) Put the users with the top 10% of the attention users into the set | (7) Put the users with the number of fans between 10–200 into the set | (8) | (9) Update and | (10) return , |
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