Citigroup Inc. (C)

Industry: Major Banks

Social Sentiment & Activity

Daily Sentiment Score & 7 Day Moving Average
Activity

Popular Topics & Highlights

... cause climate change. But JPMorgan Chase, Bank of America, Wells Fargo and Citibank ...

Two important things for Credit Card users 1. Credit Card interest rates will kill u if u revolve ...

... America-Bank of America, Citigroup, JPMorgan Chase, and Wells Fargo-are on average 80 ...

Citigroup profit beats as credit card, trading revenue jump

... billion That's enough cash to end world hunger for a year.

... beating Q4 expectations. Citigroup posted earnings of $1.90/share vs. $1.84/share ...

... and recognizing their history. 1) Changed Citi Field address to honor Tom Seaver, & a statue ...

... shares, 20% of $C, 18% of $BAC, 19% of $JPM & 19% of $WFC.

... still depositing with @Chase, @WellsFargo, @BankofAmerica or @Citibank, it's time to move. At ...

When Citi's stock price was $65 a share, I told the CEO ...

Analysis

Yesterday, Sunday, January 26, we saw neutral social sentiment for Citigroup Inc. (C). We gave it a score of -8. There was little activity, such as likes and shares, on social media.

Over the prior 7 days we calculated an average sentiment score of -16 (negative). Over the prior 14 days our AI scored an average sentiment of -16 (negative). And for the prior 30 days our social sentiment score for Citigroup Inc. (C) is -7 (neutral).

Disclaimer

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 SocialSentiment.io 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.