Twitter is dead. Technically, it is still alive—barely—but for scientific research, it is as good as dead. Twitter’s demise did not start with the saturation of blue ticks, nor with the nonsensical limits on daily views. It started and ended with cordoning off access to the Twitter API; now, it costs $5,000 per month for 1,000,000 tweets—a tenth of what academics previously got for free. I started researching on Twitter in 2016....
In my previous post, I took a look at document-pivot methods in Topic Detection and Tracking. Document-pivot approaches use clustering to find out what people are talking about, but that’s not the only solution. In this post, I take a look at feature-pivot methods, the second type of Topic Detection and Tracking methods. Instead of looking at what people are talking about, these approaches look at how people are talking to detect that something happened....
Topic Detection and Tracking has been around for more than 20 years, but during this time, there has been a lot of research. When researchers started creating systems, they went off in a few different directions. Earlier, I took a brief look at Topic Detection and Tracking. In this post I take a look at one of the two main approaches to solving the problem: document-pivot methods. Picture this: you’re out and about when you hear someone say the phrase “free hamburger....
Topic Detection and Tracking is not an old research area. It was ‘only’ established in the late 90’s and it didn’t really pick up until a few years later. However, a lot has happened since then and today’s research is almost unrecognizable from back then. In this post, I take a brief look at what Topic Detection and Tracking is and at its history. What’s Topic Detection and Tracking? First things first: what is Topic Detection and Tracking or, less formally, event tracking?...