Examples of Big Data Language and How Newsrooms can Maximise their Application
AI tips and ideas Small Newsrooms can incorporate into their digital products, service and content production.
Big data are often classified into three parts: Structured, Unstructured, and Semi Structured Data.
AI field come out of tech companies. Companies like Amazon, Google, Meta, and Microsoft are leaders in AI research.
Example of Journalism Use and application of AI is in Improving reader retention by recommending more relevant articles.
Other Journalism Use if AI
According to AI Journalism Discovery: to illustrate the different categories of journalistic use, our colleagues at the Associated Press divide AI uses into three main categories. We’ve adopted this and often classify AI journalism projects by the phase of news development they fall under:
❖ News gathering: Your newsroom regularly sorts through data to find specific events, transcribes audio/video or engages in fact-checking.
❖ News production: Your newsroom regularly creates stories from structured data, localises articles or wants to convert text to audio.
❖ News distribution: Your company wants to make better article recommendations, more relevant ads or personalised landing pages.
But, like any categorisation system, it isn’t perfect. There’s a lot of nuance within each category and edge cases that don’t fit nicely into each. Is engagement reporting distribution or gathering? Where does comment moderation fit?
Knowing which category a problem falls into is less important than knowing if it’s possible to solve it with AI.
The ten most commonly used programming language in big data projects are Python, JAVA, R, C++, Scala, Julia, JAVA script, SQL, MATLAB, Go (Golang). Find out how each programming language is different or interrelated here.
Examples of machine learning algorithm driven big data languages are:
- BARD from Google
- CHATGPT
- Large Language Models, LLM
- BERT
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