The amount of data generated on Twitter
is huge and handling this amount of data along with making sure that all users get tweets of respective importance is a challenge for the data engineers.
Twitter has made many adjustments to their ML Algorithms for optimising UX. For people in the field of data science, this article will show how the algorithms are implemented. Rest of the audience will get an understanding of what’s going behind their screens and why certain tweets show up on their timeline.
Understanding The Algorithm Behind Twitter’s Timeline Ranking
All the tweets since the user’s last visit are gathered and shown in reverse chronological order. Every tweet is given a relevance score by a model. This score indicates the likelihood of the user finding a certain tweet interesting.
So, a collection of tweets with higher scores will show up, increasing their visibility. If the number of relevant tweets is high, there again needs to be an order which is now ranked based on the time of posting.
The following factors are considered to make predictions:
- The presence of image or video in the tweet and number of likes
- The user’s past interactions with the one who tweeted
- User’s history of likes and retweets and the time spent on Twitter
A typical user also has a habit of refreshing the feed every minute or two. So, this also adds up to the already complex scoring model. The model calculates the scores and show the tweets in real-time.