Data journalism is a modality of digital news production that uses large databases to produce pieces of content focused on informational correlations, as well as using graphical and interactive resources to make the User viewing experience of news consumer.
“Journalism is dying.” “Newspapers of extensive tradition and recognition are closing their doors in various parts of the world.” “No one else reads news.”
Phrases like these have been frequently heard and said recently and have a part of reason. In fact, it is no longer common to see people opening the leaves of a newspaper in the Bank of the square to know the news of the country.
At the same time, streaming services and audiovisual platforms are conquering a good part of the usual spectators of television news.
However, the authors of the above phrases may be misinformed about the latest good news: The digital transformation achieved journalism and here to stay.
The main exponent of this movement is data journalism, which has been promoting important changes in the process of information production and consumption by users on the news sites.
The resources and tools of large volumes of data and analytics people are being incorporated into the newsrooms of newspapers, allowing access to more valuable, reliable, complete and adapted to the dynamism of digital reading.
Next, we will present the main novelties of the scenario of data journalism in and out and the impact of them on our way of seeing the world.
If you do not want to be outdated on the subject, read the content until the end is your best decision.
- 1 What is data journalism?
- 2 How did the concept of data journalism emerge?
What is data journalism?
In essence, data journalism is a method of producing news oriented to the use of information elements and numerical value, with the objective of producing correlations to reach precise and relevant conclusions on topics of interest to the Public.
The disruptive nature of this professional mode is shown in breaking the routine of the conventional journalist, consisting of field work streets of the manually crafted Agenda, in person or telephone interviews and the creation of a news content up to the End.
With data journalism, logic is reversed. Instead of proposing a research topic and then departing for the active search of information, editors and reporters immerse themselves in the collections of collected data and identify gaps or connection points that are worth exploring more deeply.
Therefore, it is the data analysis that starts the news production process, gaining a much more meaningful role.
How did the concept of data journalism emerge?
The term “Data-driven journalism ” began to be used in 2009 to designate news production initiatives from structured data in the United States, adapting to different languages in the following years.
The development of a concept for the activity responded to the need to give form and impulse to the new journalistic model, facilitating its diffusion by the professional community and guiding the academic and independent research on the subject.
Many communicators in the field have included even working with the data of their professional profiles to adapt to the requirements of hiring vehicles and companies that are living the transition to the production data driven.
When journalism started working with data?
The question seems even strange, doesn’t it? In the end, journalism always had as a pillar the veracity of the information transmitted in the reports of all formats.
In fact, the long history of journalism has seen initiatives and actions focused on statistical data, which supported the interpretation of the reader in the subject matter.
The first example of the news comes from the American daily The New York Tribune that in 1849 published on the cover a complete and visually friendly graphic about the cholera epidemic that reached the city that year.
Although the medicine had not advanced enough to understand the causes of the disease, the matter of the newspaper alerted the population to its lethal capacity and the need to mobilize efforts to prevent a massive number of deaths.
The graph showed the proportion of deaths from cholera in relation to the total number of deaths in the city, showing a municipal problem of great public interest.
Why can data help journalism?
Understand now what are the main advantages of associating data to journalism:
Are not influenced by particular interests
The journalistic credibility of the traditional media has been put in check with great force in recent years, especially with the emergence of false news on social networks.
Bearing in mind that quality information is the main raw material of journalistic research, it is essential that it comes from reliable sources that are not influenced by commercial or ideological interests. And who can be better than the numbers to guarantee an exempt origin for the facts?
The main premise of data journalism is to easily present and clean the numerical information related to the topic of content, which allows the reader’s evaluation could be based on statistics and not on assumptions or personal versions, That are often distorted by conventional sources of interviews.
Increase the quality of the productions
Data analysis allows to connect limited pieces of information about complex and diverse problems and situations, which favors the content is more complete and proposes a more complete and efficient assistance for the evaluation of the reader.
In addition, the multiplicity of data visualization formats provides the user with a more complete and interactive experience, as he can navigate the graphics and pictures in the order of his preference.
The main data visualization features currently used in the news sites are:
Interactive charts and tables.
Geographic heat maps.
What resources and tools allow data journalism to perform?
At this point you may be wondering: But how are journalists working so well with numbers, even though they are human?
Despite the need for a reasonable analytical capacity to produce data-oriented news, the success response lies in the series of digital tools and resources that communication companies have been able to leverage to guide their initiatives.
The tools allow the large data structure the volume of large databases, which allows the realization of filters and common parameters that separate the information generated according to the interest of the journalist and the category of topics he will explore in A story.
At the same time, the dashboards designed in a responsive and pleasant way create the ideal conditions for a complete data analysis and a better direction of the existing connection points between the available information.
Existing stoning data structures in place with the technical enhancement tools of the news production process and offers user immersion in the final content in which it is affected with visual fluctuations on the page and elements in various Formats (videos, images, GIF files, infographics).
The user is the protagonist of the digital world, which is evident in the existence of SEO strategies, position search and a website or blog on Google. How does this concept apply to data journalism?
Semantic analysis tools are a set of keywords distributed over the Internet, both representing the search for information in search engines as the expression of comments on social networks or forums. Plus a large volume of data, right?
Support for semantic intelligence applications, journalists can decipher the intent of the user and the topics of greatest interest among the fragments of the audience, the combination of keywords to generate ideas of content.
Building on the principle of collaboration in the digital environment, journalists from various media and channels have used the Github to find application development and data structuring references.
The platform is used by programmers and developers to disseminate experiences and new creations, generating an open source software network that communication companies can use to create their own news applications, Optimized for user experience and responsive visualization of dice.
Among all the types of programming language of the projects available in the community, Python is the most suitable for journalists.
The language is quite affordable and comprehensive, providing the development of automatic learning tools, news applications or the use of automatic data collection resources.
Public Data Bases
The collections of official data and research such as the demographic census are absurdly large and interpret them manually is not the most attractive activity for a journalist.
In order for all this information to be lost and wasted, data engineering tools have been applied by reporters and producers to more efficiently filter and organize the volume of figures and statistics produced by public bodies .