For the last years, the use of social media services like Twitter, Google+, and Facebook by all kinds of people, including representatives of public and private organizations and also by governments has been increasing. The ability to get real-time information has enabled people to follow events live, to discover breaking news, to find out about trending topics, and to help on natural disasters, just to mention a few examples.
This social use of the web stimulates researchers and developers to look for the huge information flow created through exchange between people. As the people on social networks inform one another about what is going on in their lives and their cities, that data can be utilized to detect trends and patterns in human behavior and, maybe even, with great precision. This real-time analysis can reveal relevant information about our society.
Companies are already using this intelligence to reshape their businesses and some experts suggest that data-mining is the next frontier for social media marketing. In the web industry, advertising is the area that has a lot to benefit from these kinds of research. The goal for everyone seeking real-time analysis is to have their services act immediately — and intelligently — on information as it streams into the system.
Click on the image and watch the video below to know more about real-time analysis 
http://www.youtube.com/watch?v=POJCV28UYe4
At the workshop Real-Time Analysis and Mining of Social Streams – RAMSS 2013, the keynote speaker Dr. Ramesh Rangarajan Sarukkai (Senior Management, Google Inc.) will talk about ways to monitor the user’s actions while he or she is on Youtube - the site where Sarukkai works. The system presented by the researcher, the DAL, leverages real-time user signals for dynamic ad loads, and is designed to improve the overall user experience on YouTube. This system uses machine learning to optimize user activity during a visit to the website and helps decide dynamically on real-time advertising policies. This is vital for anyone who is looking to monetize a website.
The other keynote speaker is Gianmarco De Francisci Morales, who will talk about SAMOA, an upcoming platform for mining big data streams. This platform will soon be released as open source software to foster collaboration and research on big data stream mining. Morales is a postdoctoral researcher at Yahoo! Research Barcelona. He received his Ph.D. in Computer Science and Engineering from the IMT Institute for Advanced Studies of Lucca in 2012. His research focuses on large scale data mining and big data, with a particular emphasis on web mining and Data Intensive Scalable Computing systems.
Check the full workshop schedule :
Keynote talk by Dr. Ramesh Rangarajan Sarukkai
Towards Real-time Collaborative Filtering for Big Fast Data. Ernesto Diaz-Aviles, Wolfgang Nejdl, Lucas Drumond and Lars Schmidt-Thieme
Detecting Real-time Burst Topics in Microblog Streams: How Sentiment can Help. Lumin Zhang, Yan Jia, Yi Han and Binxing Fang.
Real-time Discussion Retrieval from Twitter. Dmitrijs Milajevs and Gosse Bouma.
MediaFinder: Collect, Enrich and Visualize Media Memes Shared by the Crowd. Raphäel Troncy, Vuk Milicic, Giuseppe Rizzo and José Luis Redondo García.
MJ no more: Using Concurrent Wikipedia Edit Spikes with Social Network Plausibility Checks for Breaking News Detection. Thomas Steiner, Seth Van Hooland and Ed Summers.
Sub-Event Detection during Natural Hazards Using Features of Social Media Data. Abhik Dhekar and Durga Toshniwal.
Read more about Real-time Analyzing and Mining of Social Streams Workshop here: http://www.ramss.ws/2013/program/
