In 2009, I built the original R-Shief to collect, analyze, and visualize social media content, which harvested over 70 billion posts in 72 languages. R-Shief would become a repository of multiple social movements from Occupy Wall Street to the 2011 Arab Uprisings. In its first years, R-Shief rapidly grew into a complex media system enabling me to collect and analyze data from social networking sites and to innovate machine learning software. Using its immense data repository, I developed one of the earliest detection algorithms that recognized language from the series of characters in a tweet.
In 2015, I launched Kal3a (the Arabic word for castle), an application stack that supports the R-Shief Trends Widget, Search API, the Historical Hashtag Visualizer, and Real-time Visualizer. And in 2015, I launched the Arabic Text Analysis API that displays various occurrences of Arabic words in Wikipedia. These open software programs are available on Github.
Please visit r-shief.org to view the archive, data visualizations, and all the legacy R-Shief platforms (older versions built between 2009-2020).