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Julian Siddle, a BBC science journalist and the producer for BBC World Service and BBC Radio, has given a series of talks at Central Exhibition Hall Manege and ITMO University as part of the UK-Russia Year of Science and Education 2017. Speaking to the audience, he discussed the ways to explain gravity waves to children, why major discoveries often begin with the simplest questions and whether scientific content can compete with the social media’s top vloggers.
A research team comprised of scientists from ITMO University and the National University of Singapore developed a new system that recommends sights and venues after analyzing data from social media. The system is based on complex models that use different types of data from three social networks: Instagram, Twitter and Foursquare. What's more, the researchers analyze both the behavior of single users and information in clusters - from communities of people that share common interests. These models allow to improve the existing recommendation systems, note the authors. The results of the research were published in an article for the International ACM SIGIR Conference on Research and Development in Information Retrieval organized by the SIGIR association that celebrated its 40th anniversary this year.
What do urban planning experts learn from photos in Instagram? How does data derived from social networks help bring people together? These and other questions are researched by Damiano Cerrone, the co-founder and content-manager of Spin Unit - a transnational research team that works at the confluence of such fields as Urban Science and Art&Science. Last weekend, he gave a lecture for ITMO University's section at the popular science conference Parsec-2017. In an interview for ITMO.NEWS, Mr. Cerrone explained how scientists derive large amounts of data from social networks, why one can't fully trust information from Instagram and what is there to learn from studying St. Petersburg's metamorphology.
The eight-week MIT Global Startup Labs program, organized by the Massachusetts Institute of Technology, was launched in June at ITMO University’s business incubator. 29 students and graduates from St. Petersburg, Moscow and Irkutsk, supervised by mentors from MIT and Sloan School of Management, are given two months to assemble a team, present a prototype of a new mobile application and to develop its marketing strategy. In August the participants will present final prototypes to potential investors. ITMO.NEWS describes the apps that very soon might be a part of your mobile experience.
On July 1 to 8, the Web Science Summer School 2017 was held in St. Petersburg. It was organized by Laboratory of Internet Studies at Higher School of Economics and ITMO University’s International Laboratory “Computer Technologies”. The School’s mentors presented the projects in data set analysis. ITMO.NEWS has examined some of the social network data analysis projects developed by specialists from ITMO’s eScience Research Institute.
In future, social networks could make advertisers’ work much easier. Big Data analysis algorithms can already figure out the ins and outs of a customer’s personality. They can be used to track negative reviews, determine the customers’ desires, identify their psychological type and tailor advertisements according to each customer’s data. A group of Master’s Degree students from the Computer Technologies Department have studied this topic at the National University of Singapore. They have told us about their research and the pros and cons of living in a city state.
On April 9 the ITMO VKontakte Olympiad came to an end. It was the first time that 2,000 participants from Russia, Kazakhstan and Ukraine solved tasks using the social network. Some 375 finalists competed to gain an extra 10 points for the results of the Unified State Exam, prizes branded with ITMO’s logo and passes for the VK Fest.
Mathematicians from ITMO University in Saint Petersburg, Russia, and National University of Singapore created an algorithm that predicts user marital status with 86% precision using data from three social networks (Twitter, Foursquare and Instagram) instead of one.
Ksenya Buraya and her colleagues created an algorithm that can define an internet user's marital status with a 86% accuracy by using data from three social networks. The scientists believe that such programs will once be used to create psychological profiles. Ms. Buraya will present her report on the research at one of the most important events in this field — the AAAI Conference on artificial intelligence which will be held in San-Francisco in the beginning of February.