Data science is one of the most important fields of modern computer technology of this century. Millions of sources provide us with billions of data points each day. New industries must be invented to handle the constant influx into our databases. With Python, accessing and processing data becomes accessible to thousands of people around the globe. In this post I'll show some features implemented in the analysis tool in my previous post "The underlying problem of the Fediverse and other decentralised platforms".
ActivityPub and Mastodon brought new incentives into the world of decentralised communication platforms, even so far as I would call it a serious alternative to platforms like Twitter. But all efforts made by hundreds of individuals every day – administrating servers, developing software and moderating communities – have a weak spot which needs to be addressed in the near future: who has control over the underlying computing infrastructure of the Fediverse? And are users aware of the conditions?
Last year, in 2016, the people behind the Telegram messenger opened up a lot of features of their platform for developers. The so called "Bot API" makes it possible to connect to the Telegram servers, receive messages and communicate with the other clients inside the network. I was curious and developed a bot that has some use case if you are visiting our local library.
What headlines run to the top in no time? What titles are changed? What discussions draw the most comments and stay active? In this post I will summarize how a mix of Python and R produces a video showing the HN headlines over a two month period.