跟踪和量化中国微博网站的审查
Tracking and Quantifying Censorship on a Chinese Microblogging Site
摘要：
我们目前的测量和分析审查微博，在中国流行的微博网站。由于我们下载帖子的速度有限，我们识别出可能参与敏感话题的用户，并递归地跟踪他们的社交联系人。我们还利用新的自然语言处理技术来挑选热门话题，尽管中国社交媒体中使用了新词、命名实体和非正式语言。我们发现，微博通过多层过滤动态适应用户不断变化的兴趣。过滤包括通过关键字或转发链接追溯搜索帖子以删除它们，并在帖子发布时拒绝帖子。敏感话题的趋势是短暂的，这表明审查在阻止敏感问题的“病毒式”传播方面是有效的。我们还提供了证据，敏感的话题在微博上几乎没有传播超出敏感的海报的核心。
英文摘要：
We present measurements and analysis of censorship on Weibo, a popular microblogging site in China. Since we were limited in the rate at which we could download posts, we identified users likely to participate in sensitive topics and recursively followed their social contacts. We also leveraged new natural language processing techniques to pick out trending topics despite the use of neologisms, named entities, and informal language usage in Chinese social media. We found that Weibo dynamically adapts to the changing interests of its users through multiple layers of filtering. The filtering includes both retroactively searching posts by keyword or repost links to delete them, and rejecting posts as they are posted. The trend of sensitive topics is short-lived, suggesting that the censorship is effective in stopping the "viral" spread of sensitive issues. We also give evidence that sensitive topics in Weibo only scarcely propagate beyond a core of sensitive posters.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
