Zeynep Tufekci's essay analyzing the role that social media played in both the #OccupyGezi and the Arab Spring explores the differences and similarities between different uprisings, and has some very incisive things to say about what social media contributes to political change movements:
It was after the Gezi protesters were met with the usual combination of tear-gas and media silence something interesting started happening. The news of the protests started circulating around social media, especially on Twitter and Facebook. I follow a sizable number of people in Turkey and my Twitter friends include AKP supporters as well as media and academics. Everyone was aghast at the idea that a small number of young people, trying to protect trees, were being treated so brutally. Also, the government, which usually tends to get ahead of such events by having the prime minister address incidents, seemingly decided to ignore this round. They probably thought it was too few, too little, too environmental, too marginal.
On that, it seems they were wrong. Soon after, I started watching hashtags pop-up on Twitter, and established Twitter personas –ranging from media stars to political accounts– start sharing information about solidarity gatherings in other cities, and other neighborhoods in Istanbul. Around 3am, I had pictures from many major neighborhoods in Turkey –Kadıköy, Bakırköy, Beşiktaş, Avcılar, etc– showing thousands of people on the streets, not really knowing what to do, but wanting to do something. There was a lot of banging of pots, flags, and slogans. There were also solidarity protests in Izmit, Adana, Izmir, Ankara, Konya, Afyon, Edirne,Mersin, Trabzon, Antalya, Eskişehir, Aydın and growing.
Is there a Social-Media Fueled Protest Style? An Analysis From #jan25 to #geziparki
The Nightmare Machine is an MIT project to use machine learning image-processing to make imagery for Hallowe’en.
The Stormtrooper Decanter is on back-order, but you can pre-order one from the next batch for £22 — it’s based on Andrew Ainsworth’s original movie helmet moulds from 1976, and will provide endless opportunities to point to lowball glasses and say things like “aren’t you a little short for a Stormtrooper drink?” (via Bonnie Burton)
Yahoo has released a machine-learning model called open_nsfw that is designed to distinguish not-safe-for-work images from worksafe ones. By tweaking the model and combining it with places-CNN, MIT’s scene-recognition model, Gabriel Goh created a bunch of machine-generated scenes that score high for both models — things that aren’t porn, but look porny.
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