The whole process was a collaborative effort of the team. Many debates about visuals got us thinking about how we should position our concept in relation to Twitter. In addition to working on micro-interactions, I was primarily responsible for the visual design in order to achieve a consistent look and feel.
Recent events show how much influence social media platforms have and which consequences come with it, especially in terms of news consumption. In the era of fake news and information overload, we wondered how we could redesign a social media platform to foster news consumption.
This project is a concept that addresses three core challenges for designing news on the social media platform Twitter. It aims to enhance consciousness when consuming news, as well as to provide value and clearance.
The news page is a complete and structured overview of current news.
Users are enabled to create and follow their own interests.
The user has access to a full coverage of a specific news topic, sorted by the nature of the tweets.
The user can modify the algorithm by changing the parameters, such as expanding the perspectives.
This function provides context on why users are seeing certain tweets.
During early research, we had the opportunity to talk to industry experts, like data experts from The Economist and freelance journalists to learn about how social media changed their way of working. We then conducted surveys and interviewed several people to gain insights into how they consume news.
We have analysed a variety of news publishers on their sites and social media. We also tracked how they report about the same event over months or even years.
We had some guiding principles that we developed after summarizing and validating the user research.
A main problem users face is that it is hard to distinguish between actual news content and a regular tweet. There is no visual distinction among the nature of tweets.
Reducing information overload
From a publisher's site, views and clicks are essential. The algorithm forces them to post the same content several times a day to be visible on the user's timeline. As a result, users see many news tweets about the same topic in their timeline.
The people we interviewed said that they consume their news mainly on Twitter. They look through their timeline and feel informed, but remain in their bubble and lack a complete overview of current important news.
One of the key insights was that users often see news which doesn't interest them, or they want to be notified about specific topics. We want to enable people to learn more about events of their interest.
Reading news on social media only provides a very limited view on a topic. We aim to give users context on a topic and enable them to explore related content.
Control and transparency
The algorithm is a black box. It leaves the user wonderung why certain tweets are visible or not. We want to empower users to manipulate the algorithm to get better insights and control.
As a next step, we got familiar with Twitter's UX and visual design system of both their mobile and desktop apps.
I always make sketches before starting a digital version. I would say pen and paper are my favorite tools.
After loops of feedback, weekly design sprints, and critiques, we learned that we needed to align the look and feel of our design far more tightly with Twitter's design guidelines in order to provide a coherent experience.
We continued to work a lot with potential end-users. Validating our design solutions through user testing in particular helped us gain confidence in our design decisions.
Foster conscious news consumption
• by creating a visual distinction among news content and other tweets.
• by creating a visual distinction among the nature of news tweets (article, breaking, etc.)
• by providing an overview about current happenings.
• by bundling news tweets about the same happening.
• by providing context.
• by enabling the user to explore the news and its related topics.
Provide transparency and personal control
• by enabling the user to manipulate the algorithm.
• by providing insights why certain tweets are displayed.
• by allowing the user to set their own categories based on their interests.
• Trust the process!
• Standing behind your values.
• Applying the right methods and asking the right questions.
• Good documentation is key.