Plotting a course and finding direction for a new podcasting project

Since joining Knight Lab as student fellows in April, Michael Martinez and I have been thinking about podcasting technology and online audio in hopes that a project idea would emerge. We're obviously not alone. The last 12 months have seen the rise of highly popular shows like Serial and advanced mobile or in-car "podcatching" platforms. Just last week, podcasts marked another milestone when President Obama appeared on Marc Maron's WTF podcast. Unfortunately, a handful of problems still plague podcasting; many of those challenges were covered by previous student fellow Neil Holt.

Even after reading widely on issues affecting podcasts, we had quite a bit of trouble trying to determine the most fitting angle of attack. It was difficult to choose a relevant, bite-sized project that we could accomplish and would be useful. We looked into building ID3 editors, developing Chrome extensions, designing new podcatchers, and more. Eventually, we settled on building a platform that primarily helps with the discoverability and categorization of podcasts.

Our (currently nameless) project creates topical podcast feeds comprised of episodes from many other sources. The general goal is to let podcast listeners subscribe to a topic instead of a series and be presented with episodes from series and producers that they may have otherwise overlooked. We accumulate existing podcast feeds and pick out each episode in the feed. Then, the episodes are categorized by topic area and saved into our database of episodes. When the user searches for a topic, we can query the database to construct new podcast feeds containing episodes that are all related to the searched topic. Users should also be able to subscribe to the topical podcast feeds on their mobile podcatchers.

After finding our project direction, we set about choosing some technologies. Michael and I had very little experience with databases and had primarily used Node.js and Express to build web applications in the past. We looked into a few technologies, including Parse, Flask, and others. With some encouragement, we decided to learn Django and use it for this project. It took a while to understand, but with some guidance from other engineers and student fellows at Knight Lab, we were able to start building.

There are still a lot of questions to answer on both the engineering and design sides of the project.

On the engineering side, the biggest area for improvement is in the categorization of the episodes. We are working on how we can best use keyword extraction and other natural language processing concepts to best classify the episodes. Additionally, we would like to test the project with podcast listeners to help build our sense of the most crucial functions of this project. We need a better understanding of how to maximize the value and utility of this project for potential users. We’re a long way from a completed project, but we’ll keep going. Check back in for updates.

About the author

Bomani McClendon

Student Fellow

Latest Posts

  • With the 25th CAR Conference upon us, let’s recall the first oneWhen the Web was young, data journalism pioneers gathered in Raleigh

    For a few days in October 1993, if you were interested in journalism and technology, Raleigh, North Carolina was the place you had to be. The first Computer-Assisted Reporting Conference offered by Investigative Reporters & Editors brought more than 400 journalists to Raleigh for 3½ days of panels, demos and hands-on lessons in how to use computers to find stories in data. That seminal event will be commemorated this week at the 25th CAR Conference, which...

    Continue Reading

  • Prototyping Augmented Reality

    Something that really frustrates me is that, while I’m excited about the potential AR has for storytelling, I don’t feel like I have really great AR experiences that I can point people to. We know that AR is great for taking a selfie with a Pikachu and it’s pretty good at measuring spaces (as long as your room is really well lit and your phone is fully charged) but beyond that, we’re really still figuring...

    Continue Reading

  • Capturing the Soundfield: Recording Ambisonics for VR

    When building experiences in virtual reality we’re confronted with the challenge of mimicking how sounds hit us in the real world from all directions. One useful tool for us to attempt this mimicry is called a soundfield microphone. We tested one of these microphones to explore how audio plays into building immersive experiences for virtual reality. Approaching ambisonics with the soundfield microphone has become popular in development for VR particularly for 360 videos. With it,...

    Continue Reading

  • Prototyping Spatial Audio for Movement Art

    One of Oscillations’ technical goals for this quarter’s Knight Lab Studio class was an exploration of spatial audio. Spatial audio is sound that exists in three dimensions. It is a perfect complement to 360 video, because sound sources can be localized to certain parts of the video. Oscillations is especially interested in using spatial audio to enhance the neuroscientific principles of audiovisual synchrony that they aim to emphasize in their productions. Existing work in spatial......

    Continue Reading

  • Oscillations Audience Engagement Research Findings

    During the Winter 2018 quarter, the Oscillations Knight Lab team was tasked in exploring the question: what constitutes an engaging live movement arts performance for audiences? Oscillations’ Chief Technology Officer, Ilya Fomin, told the team at quarter’s start that the startup aims to create performing arts experiences that are “better than reality.” In response, our team spent the quarter seeking to understand what is reality with qualitative research. Three members of the team interviewed more......

    Continue Reading

  • How to translate live-spoken human words into computer “truth”

    Our Knight Lab team spent three months in Winter 2018 exploring how to combine various technologies to capture, interpret, and fact check live broadcasts from television news stations, using Amazon’s Alexa personal assistant device as a low-friction way to initiate the process. The ultimate goal was to build an Alexa skill that could be its own form of live, automated fact-checking: cross-referencing a statement from a politician or otherwise newsworthy figure against previously fact-checked statements......

    Continue Reading

Storytelling Tools

We build easy-to-use tools that can help you tell better stories.

View More