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微博客PCU数据集  数据集被用于探索微博中的垃圾邮件发送者

微博客PCU数据集 数据集被用于探索微博中的垃圾邮件发送者



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Data Preview ? 5.8M

    Data Structure ?


    Jun Liu(liukeen '@', Hao Chen(lechenhao '@' , Mengting Zhan, Jianhong Mi,Yanzhang Lv
    MOEKLINNS Lab, Department of Computer Science ,Xi'an Jiaotong University, China

    Data Set Information:

    Our dataset is used by us to explore spammers in microblog and you can access our demo system at
    [Web link]

    Please add :8080 after the domain name as port. The repository webpage fails to parse the weblink when it's added in the source. (under inspection)

    Attribute Information:

    weibo_user.csv has the following attributes:
    -user_id: account ID in sina weibo;
    -user_name: account nickname???
    -gender:account registration gender including male??? female and other???
    -class:account level given by sina weibo;
    -message:account registration location or other personal information;
    -post_num: the number of posts of this account up to now;
    -follower_num: the number of followers of this account;
    -followee_num: the number of followee of this account;
    -follow ratio: followee_num/follower_num;
    -is_spammer: manually annotated label, 1 means spammer and -1 means non-spammer;
    user_post.csv has the following attributes:
    -post_id:user post ID given by sina weibo;
    -post_time:the time when a post is posted;
    -poster_id: the user ID who posted this post;
    -repost_num:the number of retweet by others;
    -commnet_num: the number of comment by others;
    followe-followee.csv has the following attributes:
    -follower: the nickname of follower;
    -follower_id: the user ID of follower;
    -followee: the nickname of followee;
    -followee_id: the user ID of followee;
    post.csv is almost the as user_post.csv and the post in it are retrievalled by a certain key word related to a topic;

    -content: the post text(mostly in Chinese, please set your Microsoft Office to make it readable)

    Relevant Papers:


    Citation Request:

    Thanks to MOEKLINNS Lab[[Web link]] especially Spammer Detection Group for opening its data