Twitter: How Data Science Made Twitter What It Is Today

Now that Twitter is trending, Thanks to Elon musk, It is the right time to discuss how data scientists contributed to its success. It is an online news and social networking site where people communicate in short messages called tweets. It’s that simple or is it?

It offers lots of features for its users and continuously improves them. In this blog, we will discuss how data science is used to provide you a better service and many more things.

How Twitter Determines What Makes A Trending Topic

Gilad Lotan (Data Scientist at Twitter) explains that trending topics are determined by sharp spikes rather than a continuous growth of any topic.

Now that’s Trending.

If a topic is continuously growing over a long period of time, it is not a trending topic, hence to make a topic trending it should show a sharp spike over a pretty short period.

According to Twitter, How trends are determined,

Trends are determined by an algorithm and, by default, are tailored for you based on who you follow, your interests, and your location. This algorithm identifies topics that are popular now, rather than topics that have been popular for a while or on a daily basis, to help you discover the hottest emerging topics of discussion on Twitter.

More than 35000 tweets are sent per minute and this is a huge number. So data scientists must also look for any tweets that include Violence, harassment, and other similar types of behavior that discourage people from expressing themselves. So are there rules for trends? Of course, there are, You can go through all rules from here.

Twitter Analytics

92% of companies tweet more than once a day, 42% tweet 1-5 times a day, and 19% tweet 6-10 times a day. It is a large platform for not only expressing yourself but to promoting businesses and branding.

Twitter offers analytics of every Twitter user where they see their growth and insights to better their reach.


There are Two Types of Data Scientists

Type A Data Scientists :

Here A means Analysis. Type A Data Scientists make sense of the data. They deal with data cleaning, methods for dealing with very large data sets, visualization, and so on.

Type B Data Scientists :

Here B means Building. They build models which interact with users, often serving recommendations and products, people you may know, ads, movies, search results, etc.

Conclusion :

Data Science plays a major role in Twitter’s growth. There is a lot of hiring in Twitter for data scientists.


Opportunities are everywhere, To become a data scientist, all you need is to learn skills (python, NumPy, pandas, Apache Spark). Console Flare has successfully placed students and professionals in companies like Accenture, IBM, and Cognizant.


We are offering One to One Interactive session with Corporate Professionals and Data Scientists. Go through our Courses Here and become a Data Scientist in 5 Months. Good Day.

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