Social Sentiment & Activity
Daily Sentiment Score & 7 Day Moving Average
Popular Topics & Highlights
Oracle wins cloud computing deal with Zoom as video calls ...
Happy #MothersDay from all of us at NetSuite!
The Giants told roughly 350 full-time workers at Oracle Park that they will ...
... ng all #Chainlink and #DeFi developers. Learn how to start building decentralized ...
... multi-region table feature in the @Oracle NoSQL Database version 20.1. #NoSQL #database
AWS Cloud is now bigger than Oracle ! AWS Last Quarter Revenues : $9.954Bn Oracle last Q: $9.8Bn
... Analysts, Partners. We're bringing Oracle Cloud Day to you! Keep an eye on this space as we ...
Good morning everyone. I feel happy today. Small, minuscule, tiny but almighty ...
Cash each company has: Apple: $192.8 billion Microsoft: $137.6 billion Google: $117.2 billion Facebook: $60.3 billion Amazon: $49.3 billion Cisco: $28.6 billion Oracle: $25.9 billion Intel: $24.9 billion IBM: $11.9 billion Total: $648.5 billion
... your #DeFI app pillaged next due to bad data? #BuiltOnEthereum #PoweredByChainlink ...
Yesterday, Saturday, May 30, we saw neutral social sentiment for Oracle Corporation (ORCL). We gave it a score of -1. There was little 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 8 (neutral). And for the prior 30 days our social sentiment score for Oracle Corporation (ORCL) is 7 (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 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.