- Mar 19, 2010
I really do appreciate everyone's participation in this thread today. While you guys on the left may have not have learned anything from interacting with me, I try to always learn from the time I spend observing liberal echo chambers.
The kind of reactions that I just got actually fascinate me, and I've observed the same phenomenon everywhere from Twitter discussions to people talking in YouTube live chat.
If anyone who criticizes the left, ever reveals anything which could make them seem credible to those who appeal to authority, the native liberals feel compelled to try to discredit the person with personal attacks and other childish antics which equate to schoolyard bullying, in order to sow doubt about the source of information that threatens their ideology. I'm sure it also makes them feel better about themselves.
The behaviour of left is remarkably predictable once you have observed their group-think in enough different environments.
I think the reason it fascinates me, is because I couldn't ever imagine pretending to know something I don't, or pretend to have credentials which I cannot back up. I suppose it makes sense if you bull$#1t your way through life, ignore reality and can just claim false victories, like I see from liberals daily.
Nah, mostly people are on a massive pisstake after having to swallow the bile spewed by Trumpites for the past 4 years
Where does your funding come from - dem tools and AWS compute time don't come cheap for the amount of data you're talking aboutDid you read the long post I made where I took the time to explain some things that are easy to understand? I specifically mentioned things which are commonly observed by people and do not require any kind of data analysis to prove. Most of what I outlined can be studied and confirmed by anyone, without any special knowledge, data, or algorithms. I even listed some examples of observations that you can make yourself to confirm different kinds of censorship and manipulations, which are things that most Twitter users see daily, even if they don't realize it.
Our team uses a proprietary stack developed in-house by people who are smarter than me. It runs crawling and data collection workers on a AWS compute cluster, pushes data to processing nodes via Kafka, before ingesting into one of our sharded ClickHouse database clusters. Further analysis is done using a variety of methods, ranging from simple aggregated metrics that run in the cloud, to machine learning models which use pytorch on dedicated GPU hardware which we have at the office. Team members can also use their own tools for discovery and local analysis.