Strong factual storytelling relies on good idea development. In this video, part of a series of video posts made for students on the MA in Data Journalism at Birmingham City University, I explain how to generate good ideas by avoiding common mistakes, applying professional techniques and considering your audience.
The links mentioned in the video include:
Related post: Here’s how we teach creativity in journalism (and why it’s the 5th habit of successful journalists)
Machine learning and Natural Language Processing (NLP) are two forms of artificial intelligence that have been used for years within journalism. In this video, part of a series of video posts made for students on the MA in Data Journalism at Birmingham City University, I explain how both technologies have been used in journalism, the challenges that journalists face in using them, and the various concepts and jargon you will come across in the field.
PS: The MA courses at BCU have an open day this month: you can register here.
The examples mentioned in the video include:
In a guest post for OJB Maria Crosas points out three main takeaways that newsrooms should consider when aiming for a complete chatbot experience.
Over the past year I’ve been frequently invited to share ideas around how bots can help newsrooms to deliver news, and advice on how to build an engaging chatbot experiences. And throughout these classes, I’ve also had challenging questions on how these technologies are pushing the boundaries of ethics, artificial intelligence and storytelling.
I’ve boiled down these experiences into 3 takeaways for newsrooms that want to begin the chatbot journey. Here they are…
January 2012: The National Post’s graphics team analyzes keywords used in State of the Union addresses by presidents Bush and Obama / Image: © Richard Johnson/The National Post
In a guest post for OJB, Barbara Maseda looks at how the media has used text-as-data to cover State of the Union addresses over the last decade.
State of the Union (SOTU) addresses are amply covered by the media —from traditional news reports and full transcripts, to summaries and highlights. But like other events involving speeches, SOTU addresses are also analyzable using natural language processing (NLP) techniques to identify and extract newsworthy patterns.
Every year, a new speech is added to this small collection of texts, which some newsrooms process to add a fresh angle to the avalanche of coverage.
This week I’m rounding off the first semester of classes on the new MA in Data Journalism with a session on artificial intelligence (AI) and machine learning. Machine learning is a subset of AI — and an area which holds enormous potential for journalism, both as a tool and as a subject for journalistic scrutiny.
So I thought I would share part of the class here, showing some examples of how the 3 types of machine learning — supervised, unsupervised, and reinforcement — have already been used for journalistic purposes, and using those to explain what those are along the way. Continue reading
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