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Sunday, March 26, 2017

Can artificial intelligence make you a better tweeter? | Recode

Follow on Twitter as @KurtWagner8
Kurt Wagner, business and tech journalist since 2012 says, "An AI startup called Post Intelligence hopes it can."

Photo: Shutterstock / Willyam Bradberry

I‘ve tweeted nearly 5,000 times in my life, which certainly feels like a lot.

But last week I did something on Twitter I’ve never done before: I used artificial intelligence to help me decide what to tweet. More specifically, I used a service called Post Intelligence, which recommended links and photos to post, suggested the time of day I should post to get the best engagement, and even estimated the popularity of my tweets before I sent them based on the language I used in the tweet.

To do this, Post Intelligence, which used to be called MyLikes and has raised $11 million from Khosla Ventures, uses algorithms similar to those Twitter and Facebook use to determine what you see in your feed.

The company analyzed my Twitter account to determine the topics I tweet about most and calculated which of those topics also perform well with my followers. Then the AI went out and found tweets about those topics that were performing well on Twitter and suggested I share them, too.

The results: The AI-suggested tweets performed better than my normal ones. Kinda. 

I sent 24 tweets over a span of 9 days, 12 that included media suggested to me by Post Intelligence and 12 that including content I found on my own. (This excludes a lot of replies to tweets that I sent, and the three times I tweeted my own stories from Recode.)

The AI-powered tweets received an average of 7.2 favorites and 2.2 retweets apiece. My “original” tweets received 5.0 faves and 1.5 retweets, on average. On the surface, the AI appeared to be a noticeable help.

I also added 70 new followers in the 9-day stretch; I had averaged just 118 new followers per month in the six months prior.

But the engagement data is skewed: The AI suggestions led to my most popular tweet of the period, this gem about BBC girl and how she would be a badass reporter (or badass anything, from the looks of it), which generated a whopping 33 favorites and 11 retweets. 

Without that outlier, my AI-suggested tweets averaged 4.8 faves and 1.4 retweets, on average, almost exactly the same as the tweets I sourced on my own...

Kurt Wagner ends his article with the following: "I want to keep using Post Intelligence to see if a larger sample size changes my performance (or my mind). You can try it here as well. If I learn anything fun, I’ll be back to share it with you all." 

Source: Recode