From: Gilad Lotan <[email protected]> Over the summer I've been working with a summer intern to sample and analyze data from Weibo. We've been collecting Weibo posts over the past couple months, sampling the public stream every few seconds, using multiple API keys coming from various IP addresses (yup, they heavily rate limit API access).
Some interesting facts about Weibo's API: - The way we're currently sampling, we're seeing around 4000 posts per minute - Weibo doesn't easily provide the friendship/follower graph like Twitter. It only reveals the last 5k followers for any public account. - Weibo uses an explicit sentiment/emoticons mechanism which is very popular. They link an emoticon to an emotion (spelled out). When a user chooses an icon, it embeds the word that the icon represents, within the user's post. Its possible to start mining this sentiment by looking at Weibo posts (emotions are placed within square brackets). - The API has an up-and-coming feature (according to their docs) which will give us the ability to know how many of the account's followers are online at any given time (VERY COOL). We just published a first analysis from this data, looking at people's reaction to Olympic hurdler Liu Xiang's epic fail. http://blog.socialflow.com/post/7120245585/weibo-chinas-twitter-equivalent-abuzz-with-sentimentover-liu-xiangs-olympic-fail The post shows some of the ways in which we can use Weibo data. We have this growing corpus of Weibo data. I'd love to collaborate with other folks (or their students!) who want to explore the data and help us figure out how we can use it to learn about public sentiment in China. I'm not ready to make a public call yet, as I don't want Weibo to ban us (or our IP addresses) from hitting their servers. Let me know if this sounds interesting, or if there's someone I should talk to! -- Gilad | @gilgul thoughts: http://giladlotan.com/blog activism: http://www.globalvoicesonline.org/author/gilad-lotan/
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