Sometimes, an idea sweeps Twitter, touching the conversation of millions of people. Many other times, ideas disappear almost as soon as they appear. Researchers at the social computing lab at HP Labs in Palo Alto and Stanford University recently wrote a paper analyzing what makes gives a topic on Twitter lasting popularity.
Twitter tracks these subjects of conversation in a “trending topics” list, and the researchers collected this data every 20 minutes for 40 days. They also collected tweets mentioning these topics every 20 minutes. They put the data together and studied it to draw conclusions about what makes a topic last.
Most trending topics disappear again fairly quickly, the researchers found, fizzling out within 20 to 40 minutes. Some, however, last for days.
The researchers write:
When we considered the impact of the users of the network, we discovered that the number of followers and tweet-rate of users are not the attributes that cause trends. What proves to be more important in determining trends is the retweets by other users, which is more related to the content that is being shared than the attributes of the users.
There are some people whose comments are so influential that they can launch trends almost single-handedly, but the researchers found that these topics actually tended to burn out quickly. Really, the most lasting topics were those that engaged a lot of different people, including comments from a large number of authors. In many of these cases, people were commenting on news items being discussed in traditional media.
According to the researchers:
This illustrates that social media, far from being an alternate source of news, functions more as a ﬁlter and an ampliﬁer for interesting news from traditional media.
The inside story of how ChatGPT was built from the people who made it
Exclusive conversations that take us behind the scenes of a cultural phenomenon.
How Rust went from a side project to the world’s most-loved programming language
For decades, coders wrote critical systems in C and C++. Now they turn to Rust.
ChatGPT is about to revolutionize the economy. We need to decide what that looks like.
New large language models will transform many jobs. Whether they will lead to widespread prosperity or not is up to us.
Design thinking was supposed to fix the world. Where did it go wrong?
An approach that promised to democratize design may have done the opposite.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.