FOLD adds new dimensions to your stories

What is FOLD?
FOLD is an open publishing platform where users can find and create modular stories, i.e., articles where text is supported by multimedia and interactive cards. The platform was developed in 2015 in the MIT Center for Civic Media and has been growing organically, with hundreds of users in many countries and languages.

Fold's homepage


  • Every story in FOLD can be built using two kind of cards:
  1. The narrative cards are the anchoring narrative, they help you to communicate the message in a traditional way: Just text and hyperlinks. Imagine them like paragraphs.
  2. The context cards are linked to words or sentences in the narrative cards, and display multimedia content (e.g. gifs, videos, audio, photographs) to have a better understanding of the central narrative without losing focus of it.
  • Users can take any contextual card of any story and use it to build their own articles; I hadn’t seen this interactivity with small multimedia pieces of information in other platforms. “We want to make it really easy to reuse pieces of a story, and also to trace back where they came from, so you can find related content easily,” said to me Alexis Hope, co-founder of FOLD.
  • As in other publishing sites, you can follow users, filter the stories, and create lists of favorites.
  • Right now the interactivity between users is pretty much limited. You can’t comment or annotate stories, nor send messages to the authors.
  • Storybench posted a detailed explainer of how easy is to create a new story on FOLD.

What makes Fold different?
I see FOLD as the Ikea of the publishing platforms: It gives you the small pieces of information that you need to build your own object of knowledge. Oh, and as in Ikea, FOLD’s design is beautiful.

FOLD is one of the closest approaches I’ve known to a non-linear narrative. Even though it uses words as a nucleus, the design of the platform and the interactivity with the contextual cards allow a new approach to the text. As Matt Carroll said in a recent article about FOLD: “It’s a really clever idea that lets you add context on the side without impacting the flow of the story.”

How is it being used?
In less than a year, FOLD has become a place of amazing explainers, from complex topics as Molecular Biotechnology or Reaction-Diffusion systems, to lessons that we can learn from Zombies or alternatives to solve Inequality.

The platform is used by students, scholars, journalists and scientists who are willing to share their knowledge with a general public. “Things that tell you how to do something, or how to understand something, that’s the type of content people is using the platform for”, says Alexis Hope, “We’re really trying to create a network of explainers.”

I asked Alexis Hope about the referents of FOLD, she mentioned some of them:
Rap Genius


  • As the content must be in the platform, it can be hard to grow the user base. Should there be a way to embed the modular stories in other websites?
  • How to monetize the idea? Native advertising? Membership?
  • The current mobile version works, but not as good as in a desktop browser. Does FOLD need an app?

FOLD and the Future of News


Actual navigation map in FOLD

In this moment FOLD is a great tool for journalists and storytellers who want to add a layer of multimedia context to their work: It makes things easier to understand, and is easy to use. But in this section I want to suggest another possibility of FOLD.

I like the metaphor behind the platform’s name. When you’re using a desktop browser to read a story on FOLD, you can see a content map in the lower right corner of the screen. That map looks just like an unfolded polyhedron, like an origami piece ready to assemble:  you just have to organize the cards, fold them, and then you will have a unique body of knowledge, a three-dimensional idea, something that you couldn’t imagine with the alphabet and the printing press.


Modular cards could build three dimensional ideas to explore in VR.

Continuing with the metaphor, you could adapt the unfolded ‘3D ideas’ (that is, the stories that we can publish in the current platform) to VR technologies. Every modular card would become a face of a three dimensional ‘body of information’ with which other users could interact.

VR News

We could inhabit an idea made of  pieces of information.

FOLD’s concept opens new ways of imagining news and stories, and the story of the platform is just beginning.


Background: Kevin Hu & Travis Rich built a site called GIFGIF, which aims to crowd tag animated gifs with various emotions. From GIFGIF’s website: “An animated gif is a magical thing. It contains the power to convey emotion, empathy, and context in a subtle way that text or emoticons simply can’t. GIFGIF is a project to capture that magic with quantitative methods. Our goal is to create a tool that lets people explore the world of gifs by the emotions they evoke, rather than by manually entered tags.” As we know, animated gifs are also a popular storytelling mechanism for social news and entertainment websites.

The cultural phenomenon of using animated gifs to express emotions has been the subject of numerous journalistic inquiries:

Fresh From the Internet’s Attic – NYTimes

Christina Hendricks on an Endless Loop: The Glorious GIF Renaissance –

GIF hearts Tumblr: a fairytale for the Internet age –

Visualization project for this week: Kevin, Travis, and I built a map tool so people can explore GIFGIF’s current dataset to see which gifs are most representative of certain emotions across different countries. Out of 1.8 million votes, 1.4 million votes had IP data which links the votes to the location of the voter. GIFGIFmap can be found here.

Screen Shot 2014-04-02 at 1.03.12 AM

In a future version, we would like to show the top gifs per emotion that countries have in common with each other, and what are unique top gifs for each country (along the lines of What We Watch). However, there are limitations to the GIFGIF data set in terms of global coverage. For example, the top 21 countries account for 92% of the votes. Additionally, we excluded countries that had less than 10,000 total votes across all categories, so as to avoid making generalizations based on limited data. We chose to include the number of votes per country (per emotion) to make the data set more transparent in terms of representation.

We think the tool we are building could complement existing stories about the phenomenon of using animated gifs to communicate (stories like the ones we linked to above).

These are some potential questions that we hope journalists could explore using a map interface to the GIFGIF dataset:

1) Do people from different countries interpret the emotional content of gifs differently?

2) If there are variances in interpretation, are there clusters of countries that have more similar interpretations? Do these match up with proximity, or immigration patterns?

3) What top gifs per emotion are unique to a given country?


Note: GIFGIF’s data will soon be made publicly available through an API.