We present an approach for cyberbullying detection based on state-of-the-art text classification and a common sense knowledge base, which permits recognition over a broad spectrum of topics in everyday life. We analyze a more narrow range of particular subject matter associated with bullying and construct BullySpace, a common sense knowledge base that encodes particular knowledge about bullying situations. We then perform joint reasoning with common sense knowledge about a wide range of everyday life topics. We analyze messages using our novel AnalogySpace common sense reasoning technique. We also take into account social network analysis and other factors.

The symptoms of angina--the pain that occurs in coronary artery disease--do not differ substantially between men and women, according to the results of an unusual new clinical trial led by MIT researchers. The findings could help overturn the prevailing notion that men and women experience angina differently, with men experiencing "typical angina"--pain-type sensations in the chest, for instance--and women experiencing "atypical angina" symptoms such as shortness of breath and pain-type sensations in the non-chest areas such as the arms, back, and shoulders. Instead, it appears that men and women's symptoms are largely the same, say Karthik Dinakar, a research scientist at the MIT Media Lab, and Catherine Kreatsoulas of the Harvard T.H. Chan School of Public Health. Dinakar and his colleagues presented the results of their HERMES angina trial at the European Society of Cardiology's annual congress in September. Their research is one of the first clinical trials accepted at the prestigious conference to use machine learning techniques, which were used to characterize the full range of symptoms experienced by individual patients and to capture nuances in how they described their symptoms in a natural language exchange. The trial included 637 patients in the United States and Canada who had been referred for their first coronary angiogram, the gold-standard test to diagnose coronary artery disease.

Artificial intelligence technologies could reshape economies and societies, but more powerful algorithms do not automatically yield improved business or societal outcomes. Human-centered design thinking can help organizations get the most out of cognitive technologies. Today's artificial intelligence (AI) revolution has been made possible by the big data revolution. The machine learning algorithms researchers have been developing for decades, when cleverly applied to today's web-scale data sets, can yield surprisingly good forms of intelligence. For instance, the United States Postal Service has long used neural network models to automatically read handwritten zip code digits.