Starbucks Corporation (SBUX)

Industry: Restaurants

Social Sentiment & Activity

Daily Sentiment Score & 7 Day Moving Average

Popular Topics & Highlights

... ok. Ordering a venti is ok. Drinking iced coffee in winter is ok. Showing up late with ...

... generations of I-phones, twenty different holiday drink types at Starbucks and exactly zero ...

... Starbucks is playing "Ribs" by Lorde, the day after Christmas, in a direct attempt to ...

#BTS fans are rushing to #Starbucks today for limited-edition food and ...

Starbucks gave employees free subscriptions for a meditation app to ...

... you must... but I heard Monday morning are good time to give @Starbucks away for free

... for them? Enlighten me. You can get a part-time job at Starbucks and make far more ...

... two seconds more for my Starbucks Mobile order. #thebreakdownisreal

... answer your questions about what it's like to work there ☕️

... I say. All I ask is you cite me and send Starbucks gift cards. Fair.


Yesterday, Sunday, January 26, we saw positive social sentiment for Starbucks Corporation (SBUX). We gave it a score of 24. There was a moderate amount of activity, such as likes and shares, on social media.

Over the prior 7 days we calculated an average sentiment score of 10 (positive). Over the prior 14 days our AI scored an average sentiment of -5 (neutral). And for the prior 30 days our social sentiment score for Starbucks Corporation (SBUX) is -3 (neutral).


We believe social network activity can help inform investors of the positive and negative opinions people hold of a company. Social media posts are made both before and after market price fluctuations. We can make no claim of correlation or causation between market prices and social media sentiment. We make no evaluation of stock value and we can make no prediction of future prices. The information gathered on should be only one part of a broader investment strategy.

We've trained our artificial intelligence systems from past social media posts. While tests show our predictions are usually accurate to our models, a human may come to a different conclusion for some posts.