Topic Detection and Tracking: a brief introduction

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.


An Automatic Participant Detection Framework for Event Tracking on Twitter: Part 1

On one of my last trips before COVID, I went to Málaga. While there, I bought a ticket to watch a football match between the city’s team and RCD Mallorca. As I arrived at the recently-renovated La Rosaleda Stadium, I found my seat and took in the sight of 30,000 blindingly-blue seats with seagulls circling above. Then, I opened on my phone to figure out who was playing. I was behaving like a machine.


Feature-pivot methods: did something happen?

Cheer! When something happens, people talk differently. We can use that cue to notice that something happened.

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.


Document-pivot methods: what’s happening?

Talk! The way people talk can tell us a lot about what's happening.

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 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.


If machines could watch football

This article was originally published on the Times of Malta and appeared in the Sunday Times of Malta on 10 March, 2019. The article is being reproduced as it appeared originally.

One out of every two people watched part of the FIFA World Cup last year. Yet in spite of the sport’s popularity, there is no robot that could sit next to you on a weekend afternoon, sip on a cold beer, and contemplate your team’s woes and successes.

When you sit down in front of a television to watch a football match, you understand what you are watching, but there are many nuances that we take for granted. What would it take for a machine to do the same thing?


About events

Events have been a big part of my life since 2016. But no, not those kind of events.

My name is Nicholas Mamo and I’m not a party animal nor particularly outgoing—I’m a doctoral student at the University of Malta. 2016 is the year when I started working on my undergraduate dissertation and the subject was events.