The term fakenews is used very often for different groups of people to judge about opinions. What fakenews is in reality is more peaceful and was illustrated in the image. The Scigen nonsense generator is producing the content, a commercial repository is storing the paper, a bot creates a curated playlist of the fake papers which is submitted to the social network wikinews. And at the end a human will release the story.
This chain of content generation and peer review in a social network can be fully automated. In contrast to human generated fake news and human written peer reviews the overall pipline will produce a much larger amount of information. We are talking not about one or two papers which are biased, but about 100 million and more.
From the software side the needed amount of python scripting is not that big. uploading a paper with an automated script to a website is something which is teached in most computer courses in the first lesson to the newbies. Combining the steps into a larger workflow will result into an interesting problem. How can we decide if the paper is right, how should social network be controlled if bots are the main part of it? Have the human the control or the machines?