> [!info] > Input: [[Social Media Posts|posts]], [[Social Media Content|comments]], [[Social Media Content|keywords]] > Output: sentiments (positive, negative, neutral, etc.), sentiments subjects, risks evaluation > > Types: {{types}} > Weakness: [[SOWEL-5. Exposing the Fact of Activity]] ### Explanation Understand the most prioritized topics and sentiments ### Examples - [Boost OSINT investigations with textual NLP - YouTube](https://sociallinks.io/osint-webinars/boost-osint-investigations-with-textual-nlp) - [Analyzing Tweets with NLP in minutes with Spark, Optimus and Twint](https://towardsdatascience.com/analyzing-tweets-with-nlp-in-minutes-with-spark-optimus-and-twint-a0c96084995f) ### Tools - https://www.twitonomy.com/ ### See also - [[SOTL-5.1. Check Initial Activity]] - [[SOTL-5.3. Detect Close Relations by Interactions]] - [[SOTL-5.5. Study Activity at the Same Time]]