A few weeks ago, Chinese in Shanghai rescued over 600 cats from being skinned through crowd-sourcing techniques using the micro-blogging website Weibo. Animal rescue groups and volunteers were called to intercept the truck after a message was spread through Weibo. The cats were ultimately saved and the police became involved after the truck that was carrying the cats was stopped by the concerned citizens.
I wanted to share this story because it bares some resemblance to the netizens vs. animal rights violations instances of Human Flesh Searches from the past.
A research blog dedicated to the Human Flesh Search Engine (人肉搜索), a contemporary Chinese internet phenomenon in which netizens use the internet and web forums to target notorious online personalities to discern their real identity. The purpose of this blog is to keep up to date with new instances and advancements of the search engine at work, as well as collate my past and ongoing research into the subject matter.
Showing posts with label crowd sourcing. Show all posts
Showing posts with label crowd sourcing. Show all posts
Saturday, December 14, 2013
Monday, November 11, 2013
Boston Marathon Bombing HFS
It's been quite a while since my last update and I apologize for this blog becoming so sparsely updated. I haven't had as much time as I'd like to peruse trends on the Chinese Internet and so a lot of stories have been slipping under my radar.
However, I would like to share this one story that hits very close to home.
A few weeks ago, a 22-year-old girl named Alicia Ann Lynch from Michigan tweeted and shared a photo of herself dressed up as a Boston Marathon bombing victim for Halloween. All judgement and poor-taste aside, what interests me about the story is the backlash she received and the exact similarities it holds against HFS cases in China.
As with HFS searches in China, American netizens used her social networking accounts to gather information about the young girl. Having discovered a photo of her driver's license, netizens were able to discern her address. Within days netizens found nude photos of her and shared all of that around the internet.
Netizens then took to the comments section of an article about the girl's poor decision to share her address and the names of her employer. The girl closed all of her social media accounts in an effort to evade netizens, but that was in vain. She reopened her account briefly to tell that she had lost her job.
As with cases of HFS in China, while most netizens spoke out against Lynch, there were many who also advocated against the wave of cyber-bullying and shaming that shook the story.
However, I would like to share this one story that hits very close to home.
A few weeks ago, a 22-year-old girl named Alicia Ann Lynch from Michigan tweeted and shared a photo of herself dressed up as a Boston Marathon bombing victim for Halloween. All judgement and poor-taste aside, what interests me about the story is the backlash she received and the exact similarities it holds against HFS cases in China.
As with HFS searches in China, American netizens used her social networking accounts to gather information about the young girl. Having discovered a photo of her driver's license, netizens were able to discern her address. Within days netizens found nude photos of her and shared all of that around the internet.
Netizens then took to the comments section of an article about the girl's poor decision to share her address and the names of her employer. The girl closed all of her social media accounts in an effort to evade netizens, but that was in vain. She reopened her account briefly to tell that she had lost her job.
As with cases of HFS in China, while most netizens spoke out against Lynch, there were many who also advocated against the wave of cyber-bullying and shaming that shook the story.
What this shows is that while the internet in America is significantly smaller than that of China, human flesh searches, or crowd-sourcing movements as they're more commonly referred to in the US, can be just as dangerous and common.
Monday, May 7, 2012
Crowd Sourcing and Disease Recognition
I came across BioGames, a product of UCLA's Ozcan Research Group, that uses a web game that players can play that helps doctors find malaria-infected red blood cells. The group has shown that "by utilizing the innate visual recognition and learning capabilities of human crowds it is possible to conduct reliable microscopic analysis of biomedical samples and make diagnostics decisions based on crowd-sourcing of microscopic data through intelligently designed and entertaining games that are interfaced with artificial learning and processing back-ends."
Why it works: "So far we have shown that this platform is capable of achieving high accuracies in diagnosing red blood cells that are potentially infected with malaria. We have shown this on a small scale with up to 30 gamers. We need your help to scale this up into a truly massively crowd-sourced platform. When you play a game, your responses are collected and combined with those of other individuals to produce an accurate overall diagnosis. Our goal is to achieve the same accuracy level of a medical professional. Having shown that the crowd's accuracy increases with the size of the crowd, we are interested in finding the most optimal number of individuals needed for accurate diagnosis."
Even more overwhelming is the fact that "using non-professional gamers we report diagnosis of malaria infected red-blood-cells with an accuracy that is within 1.25% of the diagnostic decisions made by a trained professional." Therefore, it is possible to aid third world nations that don't have the resources or trained professionals to examine microscopic data.
A great example of the power of crowd-sourcing and online collaboration put to good use; the same power that also controls the more negative aspects of human flesh search.
Why it works: "So far we have shown that this platform is capable of achieving high accuracies in diagnosing red blood cells that are potentially infected with malaria. We have shown this on a small scale with up to 30 gamers. We need your help to scale this up into a truly massively crowd-sourced platform. When you play a game, your responses are collected and combined with those of other individuals to produce an accurate overall diagnosis. Our goal is to achieve the same accuracy level of a medical professional. Having shown that the crowd's accuracy increases with the size of the crowd, we are interested in finding the most optimal number of individuals needed for accurate diagnosis."
Even more overwhelming is the fact that "using non-professional gamers we report diagnosis of malaria infected red-blood-cells with an accuracy that is within 1.25% of the diagnostic decisions made by a trained professional." Therefore, it is possible to aid third world nations that don't have the resources or trained professionals to examine microscopic data.
A great example of the power of crowd-sourcing and online collaboration put to good use; the same power that also controls the more negative aspects of human flesh search.
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