Growing technology leaves an impact on every industry. As people want to upgrade, they allow the integration of computation in their fields. The current trends in journalism are no different from any other. There is an intersection between computation and journalism, which we will widely discuss here.
AI is expediting the process of analyzing data and synthesizing them into stories. For example, automatic story writing involves Natural Language Understanding and Processing for synthesizing reports. AI also helps generate images and videos for data journalism.
Why do journalists need to learn data analytics?
There is a shift in the digitalization of media publications, and companies who couldn't bring the change collapsed. Simultaneously, the ones that could are now exploring data and computation tools to make journalism more economical.
The process of computational journalism is using analytical tools for reporting. Data journalism is much different from traditional journalism, and journalists need to keep up with the trends. If you plan to work in media, you will also need to gather knowledge from a data analytics course to work more efficiently.
The job of a journalist is to take unstructured data and creating a structure. They have to be convincing enough to catch people's attention. Structured data is not always informed about different people or events. It can also include factual numbers like tracking money, the effects of an election, and so on.
One of the most prominent examples of how data journalism worked is the exposition of the Panama Papers. Global journalists came together and exposed famous names, which led to resignations and legal trials.
Among all media companies reporting, a German newspaper, Süddeutsche Zeitung, revealed the most extensive dataset. The company had an anonymous source report of 11 million documents to them. The company then teamed up with 370 journalists across 76 countries and carried out a year-long investigation to expose influential people.
Without the help of analytics, it is impossible to have evidence regarding such matters of corruption.
Data journalism makes way for democratic storytelling
People who join the data analytics career work with the science of analyzing raw data for drawing conclusions. When you add this to journalism, it creates a more straightforward approach for the media as well.
Nowadays, computer-assisted reporting is standard, and technology helps us gather information, analyze, and create stories. Thus, open data is democratic, factual, and engaging.
Every industry is taking efforts to make data more available to people. For example, data regarding the government, census, demography are all on the internet. Thus, it helps journalists who like to dig deeper into their research and come up with fact-based reports.
One such example will be the Stanford Open Policing Project. The university's journalism department allowed its students to register freedom of information act requests. All the states were asked to report the electronic version of the stop data of State Police. In two years, they garnered records from 31 states with 130 million records.
The data helped students understand what makes a policeman pull over someone.
The university opened the data for any media house or local reporter to download this information. The revelation helped people understand the state police better. It also highlighted how the police take actions across racial demographics and a pattern to understand how they work.
Visualization is vital for journalism
Data visualization is an essential part of journalism as it engages people. Journalists take complex data and convert them into exciting visuals. People don't have much time to read lengthy content nowadays. Attractive visuals with short content are more engaging.
Visualization is another aspect of why journalists need to know how to use tools to create them. There are many such tools available to create compelling visuals with complex datasets. It goes onto show the varied skillset a journalist needs to have for surviving in this field.
