How to read and understand your tweets

The latest in the “why” of Twitter, which has struggled to maintain its lead over the rest of the industry since the company re-launched the service back in 2015.

But it’s important to understand that the vast majority of tweets are just noise. 

What’s more, if you look at the Twitter database, you’ll find that the average Twitter user only reads about 1% of their tweets. 

In fact, the average tweets per day are about 20 times lower than the average tweet.

So the next time you hear a “why,” look at your tweet and see if you can find a pattern that’s consistent across the vast number of tweets that are generated every day. 

If you don’t, it’s probably because you’re just wasting your time.

Twitter uses machine learning to identify patterns in tweets to predict the next day’s tweets.

The technology allows for a huge amount of data to be stored in the system, and this data is then used to build an overall picture of your tweet, whether you’re writing about a company, a celebrity, or a local event.

So how does Twitter measure its tweets? 

As mentioned, the company uses machine-learning to identify the patterns in a user’s tweets, and the results can be displayed in a table. 

Twitter uses this table to provide insight into how many times each tweet has been read, how long it’s been since it was last tweeted, and how many people have tweeted that day.

The data also allows the company to calculate the number of times each user has tweeted each day.

For example, if a user is tweeting a lot about a particular event, they may be able to estimate that they have tweeted a lot in the past month.

The Twitter company then aggregates this data into a table called the Tweets Per Minute.

This data is a much more granular dataset that Twitter uses to build its predictions.

Here’s an example of the Tweests Per Minute, which shows how many tweets are sent per minute by a user, and what they mean:As you can see, there’s a huge spike around the 5-minute mark, when tweets are almost 50% more frequent.

However, the overall trend in this data shows that the company is consistently able to accurately predict tweets within a given timeframe.

Twitter also uses this dataset to predict whether or not a tweet is likely to be retweeted.

As a result, it is able to predict which of the 140 million tweets sent each day are likely to receive a retweet.