Predicting Trending Topics

Twitter users will be familiar with the term “Trending Topics”. The site displays phrases or hashtags that are being used in a high number of posts. While many may think that trending topics appear quickly, and often disappear just as quickly, this many not be the case. At the Interdisciplinary Workshop on Information and Decision in Social Networks at MIT in November, Associate Professor Devavrat Shah and his student, Stanislav Nikolov plan to present an algorithm that predict topics that will trend. Not only is this algorithm 95% accurate, it can also make predictions an average of one and a half hours before the topics trend – and sometimes up to five. 

The algorithm starts by being “trained” – combing through sets of data in an attempt to find meaningful patterns. It then compares changes in the number of tweets about topics in the data set. The algorithm is built to split up it’s execution over several servers to adapt to the modern computational framework, so while the sample data sets have been small, it can easily be scaled up to examine more data. 

While this algorithm could help Twitter charge more for targeted ads that revolve around trending topics, its potential use in other categories – ticket sales, or maybe even stock prices, is much more interesting. 

What do you think this algorithm could be used to accurately predict?

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2 Responses to Predicting Trending Topics

  1. cbaughma says:

    I think this algorithm is particularly interesting because it incorporates time into the model. It looks at tweet content and notes the increasing frequency of tweet content to predict what will trend and what will not trend. With the Holidays approaching, I think this algorithm could be useful to producers and retailers in predicting quantities of products to purchase and sell based on popularity. There’s always those few “golden” items that seem to run scarce over the Holidays because of such high demand, and I think implementing algorithms like this could help prevent that scarcity.

  2. kmcmeek says:

    Having a background in computer science I would be extremely interested to see how this algorithm works, although it is very likely I would be in over my head. However it is very cool and would be extremely useful. After the recent hurricane I am curious to see if this algorithm could somehow be used to increase warnings to certain areas or perhaps generate more accurate warnings.

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