- [ ] Analyse sentiments ### Explanation Understand the most prioritized topics and sentiments ### Input - posts - comments - keywords ### Output - sentiments (positive, negative, neutral, etc.) - sentiments subjects - risks evaluation ### 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/ ### Types {{ business | technical | behavioural }} ### See also - {{internal links to similar techniques}} ### Weakness [[SOWEL-5. Exposing The Fact Of Activity]]