How Twitter Can Improve Trending Topics


Photo: derya

Two months back, I wrote about an emerging new topic entitled trend curation. The article highlighted some strategies Twitter had implemented to make its trends more relevant so that they provide better value for the user.When you take a look at Twitter’s trending topics today, they span several different categories. Famous people often make their way into the trending topics when they are involved in a highly publicized event or controversy. Sports teams and athletes will show up as trending during a big game.

Cities will show up as trending when there is an event or even a disaster taking place within the city. When a new movie comes out, it will be trending, and the more popular it is, the longer it stays trending.  Psychological thriller Inception, for example, was trending for weeks after it launched nationwide.

You will also often see trends with a high-tech focus. When the Google homepage turned into Pacman it dominated the trending topics. When Facebook launched Places, it was trending all over the Twitter homepage.

These trends are useful, but the issue with Twitter’s trending topics is that they are always jumbled up together, so it is difficult to extract value from them. For trends to evolve, we need to see them broken out by category. For instance, when will we be able to see the most trending movie of the past week? And why can’t we quickly see which athletes or sports team are trending right now? The data is all there — it just needs to be categorized and organised….

My site Sency launched Places trends months back to show which locations are popular right now.  We then had them curated, to remove non-relevant places such as airports and Starbucks. The next step involved categorising the places by type. For instance, in New York we now show which restaurants, hotels, night clubs, and entertainment centres are popular lately. By separating out our places trends based on the type of the place, we make them more useful for the user.

Twitter is the best example of the real-time Web. Within seconds of an event, there are people commenting about it on Twitter. This raw data has become an outstanding resource for us all. In fact, the ability to quickly identify, in an automated way, breaking news and trends has been one of the best things to come out
of the real-time Web. Now, it’s time for the data be segmented, categorized, and organised so that we all can extract more out of it.

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