Recent research has confirmed what many motorcycle riders have known for years. “Lane splitting” – or riding in between lanes of traffic – obviously saves riders a lot of time, but it’s also considerably safer than sitting in traffic and acting like a car, as long as it’s done within certain guidelines, and contrary to what many drivers think, it actually speeds up traffic for everyone else on the road. Riders, please pass this information on to the drivers in your lives.
I play video games, but I would never identify myself as a gamer. Even worse, I argue that enough of those who do are turning the identity and adjacent ideology into a dangerous kind of extremism. I spoke with Matt Galloway, host of CBC’s Metro Morning about the subject.
Twitter is used extensively in the United States as well as globally, creating many opportunities to augment decision support systems with Twitter-driven predictive analytics. Twitter is an ideal data source for decision support: its users, who number in the millions, publicly discuss events, emotions, and innumerable other topics; its content is authored and distributed in real time at no charge; and individual messages (also known as tweets) are often tagged with precise spatial and temporal coordinates. This article presents research investigating the use of spatiotemporally tagged tweets for crime prediction. We use Twitter-specific linguistic analysis and statistical topic modeling to automatically identify discussion topics across a major city in the United States. We then incorporate these topics into a crime prediction model and show that, for 19 of the 25 crime types we studied, the addition of Twitter data improves crime prediction performance versus a standard approach based on kernel density estimation. We identify a number of performance bottlenecks that could impact the use of Twitter in an actual decision support system. We also point out important areas of future work for this research, including deeper semantic analysis of message content, temporal modeling, and incorporation of auxiliary data sources. This research has implications specifically for criminal justice decision makers in charge of resource allocation for crime prevention. More generally, this research has implications for decision makers concerned with geographic spaces occupied by Twitter-using individuals.
This story has a simple message: The system that is supposed to maintain the balance between secrets and civil liberties has broken down. Many believed that it already had, but Feinstein, for good reason, had argued that even if changes needed to be made, the essential relationship between her committee and the agencies it oversees was operating within bounds. What she described Tuesday was a total lack of trust on both sides. The level of trust was so low that people may have felt it was necessary to break the law to fulfill their obligations. That’s not just bad for this particular relationship; it throws the balance between the two branches into even greater turmoil than it was already in.
