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Notes:

Computational journalism is the application of computational methods, such as data analysis, machine learning, and natural language processing, to support and enhance the work of journalists. This field combines the traditional skills of journalism, such as researching, reporting and storytelling with the tools and techniques of computer science to uncover patterns and insights in large amounts of data. The goal of computational journalism is to help journalists make sense of complex information, find new stories, and create more engaging and informative content. This field also includes the use of automated tools to generate news stories, such as financial reports, sports updates, and weather forecasts. Additionally, computational journalism also involves the use of data visualization and interactive media to present information in a more engaging and accessible way to the audience.

Computational journalism and automated journalism are related fields that both involve the use of computational methods, such as data analysis, machine learning, and natural language processing, to support and enhance the work of journalists. However, there is a key difference between the two.

Computational journalism is a broader field that involves the use of these methods to support various aspects of journalism, such as research, reporting, and storytelling. It also includes the use of data visualization and interactive media to present information in a more engaging and accessible way to the audience.

Automated journalism, also known as “robot journalism” or “computer-generated journalism”, is a specific application of computational journalism that involves the use of automated tools to generate news stories, such as financial reports, sports updates, and weather forecasts. The goal of automated journalism is to create news stories quickly and efficiently, without human intervention. It uses natural language generation (NLG) to automatically produce news articles from structured data, such as financial reports, sports updates, and weather forecasts.

News extraction, also known as information extraction, is the process of automatically extracting structured information from unstructured text. It is often used to extract specific pieces of information, such as named entities (people, organizations, locations), events, and relationships between entities, from news articles or other text sources. It uses natural language processing (NLP) to analyze the text and extract structured information.

Automated journalism uses the output of the news extraction process as an input, to generate the news stories.