Cited By
View all- Kulkov IKulkova JRohrbeck RMenvielle L(2024)Leveraging Podcasts as Academic Resources: A Seven-step Methodological GuideInternational Journal of Qualitative Methods10.1177/1609406924126619723Online publication date: 25-Jul-2024
How Will You Pod? Implications of Creators’ Perspectives for Designing Innovative Podcasting Tools
Article No.: 69, Pages 1 - 25
Abstract
While centred on the medium of audio, podcasts are often a multimedia concern, and one that has become hugely popular in recent years, though relatively little is known about the perspectives of podcast creators and their visions of innovation. This article details the results of an exploratory study conducted to enhance our understanding of potential innovation in the field of podcasting. Sixteen podcast creators were interviewed about their work and what they wanted from next-generation podcasts, in order to understand the requirements and expectations of tools that could be built to create new forms of audio-based programming. Through a combination of qualitative and quantitative analysis, we reveal novel findings, such as the duality between “listener-centric” and “creator-centric” innovations, to improve listener experience but also to unleash new creative possibilities in a streamlined production workflow. We shed light on what podcast creators envision as “next-generation podcasting,” the archetypal podcast production workflow, and creators’ expectations of podcasting tools. Combining these findings, we identify how the workflow could be modified to include new steps that will help to realise podcast creators’ visions. This study crystalises on important information about podcasters—their behavior and perspectives on the future of the medium—which will allow further research, design, and development in the field to be founded upon empirical observations.
1 Introduction
Do you have a podcast? You could be the creator of one of the 473,870 active shows on Apple Podcast in August 2023 [63], or have published one of the 85,047,441 episodes made available there since 2005 [36]. With an exponentially growing library and listenership since the first podcasts in 2003 [111], and 1 out of 10 UK adults planning to start a podcast in 2022 [86], it is clear that podcasting has become a key feature of our media landscape. If the present for podcast creators around the world is a seemingly boundless space, filled with encouraging promises of things to come, the future of this medium is still blurry.
There are multiple new technologies currently in the process of “revolutionising” production methods and listener experience; to list only a few: new transcription solutions using artificial intelligence (AI) to generate subtitles for episodes [71, 106], semantic audio editing [15], spatial audio capabilities in listening devices (like the Apple AirPods Pro) and programs [16, 55], the development of tools allowing for new types of spatialised audio experiences, like Audio Orchestrator (a BBC Makerbox tool responsible for immersive podcasts like Monster [18] and Spectrum Sounds [20]), and the growing interest in object-based media and its potential applications to podcasts, through adaptive podcasting [40] or non-linear programs [102]. These projects are all akin to forms of personalisation, where personalisation serves the overall goal of immersion [56]. However, relatively little is known about podcast creators’ perspectives on these technologies, how they are integrating them into their workflows, and what they consider the technologies’ impact to be on listeners. That is because the data available focusing on podcast creators are often limited to demographic information rather than their opinions on their field.
For other traditional media, like film and radio, perspectives of industry professionals have been thoroughly documented, in dedicated academic publications [26, 27, 69, 110]. Comparatively little is known about the corresponding aspect of podcasting.
As listeners, our enthralment with on-demand audio content can be linked to several facets of the medium. Its versatility of genres and styles widens with every passing year. Shows explore novel formats and transcend expectations, reaching new audiences [72]. The episodic nature of podcasts fosters the loyalty of listeners [84], and boosts engagement, by encouraging them to experience the episodes by, for instance, organising listening parties or releasing complementary content [107]. Motives for listening to podcasts are varied, but the ideas of divertissement and social belonging appear in several studies looking at reasons behind podcast consumption [89].
To media producers, podcasting’s appeal is threefold:
(1)
Podcasts reach over 41% of people over 12 years old in the US every month [41], a percentage that has grown yearly. This wide and increasing audience constitutes an incentive for both larger broadcasting companies (like the BBC, NPR, Megaphone, iHeartRadio) and independent creators to invest resources and time into the production of podcasts.
(2)
(3)
The creative freedom the medium offers allows for projects to find unique spaces in which to develop.
What will innovative, personalised, and immersive podcasts of the future be like? To answer this question, we need to better understand the current practices, behavior, and perspectives of podcast creators. This will enable us to paint a picture of the primary user of these new podcasting tools, and thus provide designers and researchers the opportunity to justify future design decisions on the basis of empirical data.
The question of the future of podcasting could also be addressed by asking other actors within the podcasting industry what they would want and need from podcasts in the future. Becker et al. [21] recommends using an inclusive approach to designing audiovisual software that melds Human-Computer Interaction and Audience Studies into one Audiovisual Design method. This method is based on an analysis of the roles of different actors: audience (for podcasting, the passive listeners), synthesiser (the listeners who curate content for others), modifier (the listeners who reproduce, repackage, or otherwise interact with the content by modifying it), player (engaged listeners, keen to interact), and producer (content creators) of a product. To this, one can add the non-negligible role of advertisers and platforms [100]. Each of these actors will have different expectations from next-generation podcasting, and particularly, different expectations of a tool for producing and delivering these new podcasts [21].
When considering existing work on the experience of these actors and their expectations, we note that literature that details the needs of the listeners is widely available [7, 73]. Advertisers and platforms are disembodied actors, which makes understanding their expectations more complex, and they are not the target users of tools that will be built. Therefore, in this article, we focus on “podcast creator” as a target user, and our premise is that understanding their motivations and expectations could be the missing piece to a tricky puzzle where not only the user experience should be considered, but also the content and end products [21].
1.1 Research Aims
Being able to characterise a target user in design is a critical milestone to reach when designing new tools [60]. The aim of this study is to gather critically relevant information about how creators (a) produce podcasts, and (b) explore the affordances of personalisation in innovative forms of podcasting, with near- rather than long-term innovations in mind. Via interviews, we will piece together a representation of the podcaster as a target user, including their habits and views on next-generation podcasting, so that designers, researchers, and stakeholders interested in the development of new tools for podcasting can consider a legitimate user type and their requirements.
To cover these different aspects of a podcast creator’s perspectives, we will focus on the following research questions:
RQ1.
What do podcast creators envision as “next-generation podcasting”?
RQ2.
What tools do podcast creators use and why?
RQ3.
How would new tools and habits be integrated to podcasters’ established production workflows?
2 Literature Review
2.1 A Shape-Shifting Medium
From the first podcasts to the current podcast landscape, there has been a drastic expansion of what we consider a podcast. Genres have emerged and died, survived, and thrived, and the podcast landscape in 2022 is nothing like the one from 2003 [90]. A current definition of podcast is “a piece of episodical, downloadable or streamable, primarily spoken audio content, distributed via the internet, playable anywhere, at any time, produced by anyone who so wishes” [90, p. 1270].
Due to the low barrier of entry to production, the minimal amount of skills necessary to publish a program, and to the push of major broadcasters to include and champion more diverse productions [17, 77, 78], new voices are constantly appearing in the “podverse.” According to the framework established by Nelson and Ii [76], which judges a composition on five aspects (Expertise and Credentials, Accuracy, Quality of Information, Production Quality, and Currency), the quality of podcasts can be said to have improved, due in part to technological advancements, and in part to the promotion of diverse, expert voices.
Meanwhile, some elements once believed essential to podcasting are now less common. At their inception, podcasts relied fundamentally on RSS feeds to be distributed to listeners [70]. This idea of “downloadability” remains prominent with many podcast purists. However, looking at the consumption habits of listeners, most podcasts are now streamed, rather than downloaded [103]. Similarly, the episodic nature of podcasts is something that has been highlighted by many researchers [51, 72, 96, 107], yet, content is now being released as “one-offs,” emulating movies, lectures, or concerts [101]. Furthermore, for a primarily audio-based medium, there have been a number of multimedia efforts, where, for instance, podcasters choose to record videos to go alongside their programs [24, 57], or where companies offer “enhanced” podcasts, with visual elements to help navigate and clarify their content.1
Although deemed a very intimate medium [91], podcasting is rooted as a one-way format. Unlike radio, which offers call-ins, polls, and direct social media engagement as a way to impact the programs, the pre-recorded nature of podcasts makes it impossible to imitate these social properties. In recent years, there have been several attempts to make podcasts more interactive. In 2020, Spotify introduced a poll feature [98], which allows users to influence upcoming episodes of series they follow. In 2019, the app “Stereo” was released,2 where users could send in voice notes to podcasters while a show was being recorded, so that their comments could be included in the actual program. Other forms of interactivity are being explored, such as non-linearity [19, 102] and adaptivity [40].
With these innovations come inevitable crossovers with other forms of media. If a podcast is accompanied by a video, is it still a podcast? If a podcast is an interactive experience, with clear stakes and rewards, is it now a game instead [94]? And if a podcast is only broadcast at certain times, does it become radio? These blurred boundaries highlight the shape-shifting nature of podcasting, and although conserving its essence should be at the forefront of reflection when innovating for the medium [89], the endless possibilities it offers for creators and audiences alike should also be emphasised.
2.2 New Technologies for Podcasting
Historically, podcasts have been linked to new technology. In 2003, the idea to distribute audio files via RSS feed was novel. The MP3 file format itself was only a decade old [114], and being tech-savvy was a requirement for any upcoming podcaster. Since then, there have been many improvements to the systems behind podcasting, including new audio codecs (e.g., M4A and OGG), and the automatisation of RSS feeds offered by third-party providers such as Podbean, Buzzsprout, and Anchor.fm.
As 3D animation requires modelling software, so next-generation podcasting will require bespoke tools to produce new types of podcasts. This study is concerned primarily with finding out what innovative podcasts creators wish to make so that appropriate tools can be designed. There are hundreds of novel concepts that could be applied to the podcast format, either to facilitate production or to create new experiences for the listener. This study will be concerned with the latter—creating new listener experiences—as other companies and researchers [75] are already rethinking the way we edit and produce audio.
2.3 Producing Innovative Media
Other media’s production methods are highly documented. There are detailed accounts, from industry professionals and academics alike, of music [27], TV [26, 53], cinema [1, 10, 69], and radio production processes [14, 110]. This allows for complex innovative tools and processes to be easily integrated into existing habits, such as new storyboarding tools [13, 42], interactive TV narrative software [108, 109], 3D cinema production tools [11], virtual videography or intelligent video direction [52, 81], and semantic audio editing.3
Baume [14] lays the theoretical foundation necessary for using semantic audio tools in radio production, by detailing traditional workflow patterns in different areas of radio production. This thorough investigation enables researchers to understand the motives and habits of producers, and ensures that any new creative tool would fit the expectations of professionals in the field. This is in line with the findings of Ward et al. [112, p. 5] around the key principles for building new media tools: “Designing tools requires an understanding of what the desired functionality is, what workflows the tool will be integrated into and what value production staff see in the tool.”
Detailing the specific nature of designing audiovisual tools, Becker et al. [21] puts together a spectrum of actors that influence a product, from the passive listener (audience) to the content creator (producer). At the extrema are listener-centric and creator-centric approaches to designing innovative audiovisual tools. By “listener-centric” we mean audience-focused reflections based around the listener’s needs, meanwhile “creator-centric” pertains to features relevant to the production and delivery of podcasts. In the former, listeners could be queried on what direction they would like the medium to take, and their answers would be influenced by their individual preferences. Researchers drawing conclusions from any such study would therefore need a large number of participants to paint an accurate picture of the expectations of the audience, and to accept that non-professionals’ answers would not be rooted in knowledge of the technical ramifications and possible burdens of their expectations. In the latter, creators could steer innovation towards products they would be interested in using and that inform their design from practices already in place. Combining these approaches would require a better understanding of creators’ perspectives, to match the breadth of information available on listeners.
2.4 Listener-Focused Literature
The emergence of podcasting has inspired researchers to conduct very thorough user-based studies in the past. Academics have painted a detailed, nuanced picture of the technical, social, and cultural landscape that has led to the emergence of podcasts [23, 71, 88].
The listener experience of a podcast audience is very specific to the particularities of the medium. Although Armstrong and Glancy presents podcasts as a “private experience” [9, p. 68], podcasts sometimes verge on what the authors describe as a “collective audience” [9, p. 62], where the audience joins in on the creation of an event, without influencing the narrative directly [107]. Generally, podcast listeners are seen as an “intimate audience” [9, p. 62], which is an audience expected to bond with the content directly [66].
Overall, this experience is one that is based on human interactions and the idea of social belonging [90]. This is felt not only in the content, but also in the way listeners access, browse through, and curate libraries of podcasts for themselves. The proliferation of podcasts has made navigating distribution platforms increasingly more complex. Efforts for personalising the listener’s experience on a platform level are often considered necessary [64].
The focus of podcasting as a cultural phenomenon [39, 43, 51, 70, 96] seems to have obscured an equally important aspect of the medium: its production. Indeed, if O’Donoghue et al. [80] and Strickland et al. [99] address how to produce podcasts for educational purposes, the creators’ production methods, workflows, habits, and preferences [89] have not been detailed beyond the many “DIY guides” published so far [29, 30].
Guidelines for podcast production exist for particular genres, like education [79] or news [44, 66], but there is scant evidence of commonalities in the production workflows, habits, and goals across genres and production networks. These are gaps that are paramount to fill in order for researchers to develop the tools that will usher in this new podcasting era.
2.5 Personalised Podcasts
Burns et al. [28, p. 2] sees two facets of personalisation that work hand in hand to facilitate usage and improve the quality of smartphone-based help-on-demand services: “personalisation and adaptation of both content and user interface.” Similarly, Frias-Martinez et al. [45] hypothesises that services provided by personalised digital libraries can be categorised into three groups: “mechanisms for the personalisation of content,” “mechanisms to help in the process of navigation,” and “information filtering and information retrieval mechanisms.” Corresponding themes emerge in literature focused on personalisation, particularly web-based [47, 74] or smartphone-based technology [33, 105].
Along this line of thought, both podcast content and user interfaces for experiencing them could be personalised. Currently, podcast interfaces are visual, accessed primarily through a smartphone screen [41]. This leaves many possibilities for new listener-audio interactions, perhaps through voice [65, 106], sound [59, 61], gesture [58, 62], motion recognition [54], or using implicit preferences and habits through user metadata [5, 92, 93].4
The benefits of exploring different interfaces would lie in two aspects: immersion and accessibility. By allowing producers to integrate new modes of interaction with their programs, they could ensure that the interface would suit the listener’s habits, navigate the content with more ease, or simply enable their audience to better concentrate on the programme. Alternative methods of interaction could be an achievable solution not only for people listening to podcasts while engaging in another activity, when touching a screen is not practical, but also for those with visual or motor disabilities.
The fixed nature of the typical podcast’s content is a consequence of the immutable nature of the MP3 format. Other “fixed” media, like TV, are becoming more flexible, with accessible soundscapes [82], or non-linear content (Bandersnatch, You vs. wild), and yet still rely on the traditional “fixed” video formats. Therefore, although file format should be considered when developing ways to personalise content, it should not be seen as a barrier to innovation, as exemplified by the growing interest in enhanced podcasts, chapters, and adaptive podcasting, which uses a markup language to bring together personalised content for its users [40].
Besides non-linear narratives and soundscapes made more accessible via levels control, other modifications of content could be applied to podcasting, such as responsive spatialisation [67, 85], voice [22] and sound synthesis [83], reverse engineering tracks to stems [37], and server communication supporting saving of user-generated data and near-real-time collaboration [32].
2.6 Semi-structured Interviews for Requirements Gathering
This literature review has highlighted the necessity to gather more information on podcasters and their outlook on the future of podcasting. This knowledge is instrumental to developing new software, tools, and, more generally, products for podcasting. Knowing a target user is paramount to many facets of User-Centred Design (UCD [4]). Within UCD, many methods, like Iterative Software Development (ISD) and Agile Software Development (ASD) depend on Requirements Gathering (RG), a technique through which the needs of target users are analysed to inform design decisions [35, p. 34, l. 19].
There are various methods for interacting with target users and gathering requirements, including ethnographic anecdotes, expert verification, usability testing, and semi-structured interviews [95]. Semi-structured interviews are particularly useful when attempting to investigate large concepts and topics, allowing participants to elaborate on initial answers and contribute beyond the scope of the question set [48]. Questions in semi-structured interviews can be established by drafting an “interview guide” [6, p. 496].
3 Methods
3.1 Participants
Sixteen creators (independent and BBC podcast creators) took part in an exploratory study. They were recruited through a combination of word-of-mouth, BBC internal communication channels, and media publication advertisements. A gender balance was not achieved, with only 3/16 (= 19%) participants identifying as female. This distribution is supported by a recent study from Sounds Profitable and Edison Research looking at 617 active podcast creators in the US, finding that only 29% of podcasters identified as female, and 2% as Non-Binary or Other [38]. Sixty-two percent of participants were independent creators, while the remainder were affiliated with the BBC. Twelve percent were 25–35 years old, 7/16 (= 44%) are 26–50, and 5/16 (= 31%) are 51–65. 12/16 (= 75%) had over 5 years of experience in the field, with a few reporting having been involved with podcasting since the early days of the medium (2005–2010).
“Producer” was the most common occupation (with 12/16 (= 75%) of participants describing producing as one of their main roles when making a podcast). The term “jack of all trades” was mentioned freely, without cue, in 5/16 (= 31%) interviews. 4/16 (= 25%) described themselves as “hosts,” 4/16 (= 25%) as “sound engineers,” 3/16 (= 19%) as “advisors,” 3/16 (= 19%) as “developing innovative podcasts,” 3/16 (= 19%) as “executive producers,” and 2/16 (= 13%) as “researchers.” This justifies our usage of the word “creators,” as the roles of a podcaster can be varied, even when working for a large media organisation.
The genres of podcasts in which participants were involved were varied, according to Spotify’s genre classification in 2022 [97], with recent work in “Lifestyle” (6/16 (= 38%)), “Stories” (4/16 (= 25%)), “Business and Technology” (3/16 (= 19%)), “Educational” (3/16 (= 19%)), “True Crime” (2/16 (= 13%)), “News and Politics” (2/16 (= 13%)), Sport (1/16 (= 6%)), “Comedy” (1/16 (= 6%)), and “Music” (1/16 (= 6%)) reported.
3.2 Procedure
Due to the nature of the research questions, an exploratory study was designed, taking the form of approximately 45-minute, semi-structured interviews [6, 48], conducted over Zoom with individual participants. The interviews covered participants’ views on their current work and the future of podcasting. The participants were contacted 1 week following the interview with a questionnaire to gather additional thoughts that might have formed after the interview. This study was conducted with ethical approval from the University of York’s Arts and Humanities Ethics Committee.
Participants were first asked a series of questions about their work and creative process. These questions were designed to detail the inner workings of podcast production, and were set by a focus group of researchers and podcast producers from the BBC. A subsection of these questions have been analysed in a prior publication [89], focusing on how podcasts are produced (workflows and production habits). Rime et al. [89] delves into more detail about the archetypal production workflow, which, while being relevant to the current article, is only a small portion of the information necessary to address our research aim.
Participants were then asked to react to 12 short videos presenting new technologies that could be applied to podcasting (Table 1), divided into two categories to maintain focus and coherence in the discussion. They were asked to rate how interested they would be in using them on a scale of 1 (strongly disinterested) to 5 (strongly interested) and prompted for more information on particularly high or particularly low scores.
Table 1.
| Type of Personalistion | Concept | Example Technology Used For Demonstration |
|---|---|---|
| Interface | Gesture Recognition | MediaPipe (JS) |
| Touch/Tilt Recognition | NexusUI (JS) | |
| Voice Recognition | Descript | |
| Sound Recognition | Audioset Tagging CNN | |
| Metadata | Not Applicable | |
| Content | Non-linear Narratives | StoryKit |
| Reverse Engineering Music | Moises | |
| Sound Synthesis | Nemesindo | |
| Voice Synthesis | Lyrebird | |
| Server Communication | Node (JS) | |
| Responsive Spatialisation | Resonance Audio SDK (JS) |
Table 1. Table Summarising the Video Demonstrations Presented to the Participants of this Study
No particular technology was presented for Metadata, as it is a wide topic that should be addressed differently depending on the desired outcome.
In the follow-up questionnaire designed conjointly with the interview guide, the same videos were used as prompts once again to gather any additional thoughts. The participants were also asked what most interested them in the study and given a space to provide feedback.
3.3 Materials
The interview guide was designed with a focus group of BBC Research & Development staff and BBC producers. The interview questions (italics) and rationale for asking the questions (non-italics) are as follows:
(1)
If anything was possible, what’s a podcast you would like to make or hear that would transcend the current format? To get the conversation going, creators are asked to project themselves into a boundless future, where any podcast project can be carried out.
(2)
What tools are necessary for your work? Knowing what equipment or software producers rely on will allow us to determine how to make a new tool compatible with their current setups.
(3)
What attributes make for good podcasting tools? Participants are asked to provide some adjectives that justified their choice of software so we could infer some requirements for a podcast production tool.
(4)
Do you have a particular workflow when creating a podcast? Workflow process or schemas are defined as “specify[ing] which tasks need to be executed and in what order” [3, p. 267]. Here, we mean the sequence of events that begins with the idea for a programme and ends with a final product available to audiences. Understanding the production habits of practitioners will enable any new podcasting tool to find its right place within an established process.
(5)
Do you have any experience with coding? And would the need for coding deter you from using a tool? New media tools can sometimes require users to code in order to achieve a particular feature. This question seeks to evaluate whether this requirement is reasonable from podcast creators’ perspectives.
(6)
What do your listeners seek in your programs? This question is answered primarily from a producer’s perspective, therefore interpreted as “Why do you want your listeners to tune in?,” rather than “Why do they listen to your programs?” Knowing the motives of producers can help contextualise their answers and understand how to help them achieve their goals.
Following these questions, we wanted to gather the creators’ points of view on some concepts that were deemed particularly relevant by (1) the focus group used to bring together the interview questions; and (2) the review of literature and technological capabilities conducted upstream of the interviews. These concepts are detailed in Table 1. For each concept presented, a technology, existing tool, or software was showcased, to demonstrate the possible applications of the concept to podcasting. These technologies were selected not necessarily because they were the best in their respective fields, but because they were easily deployed and showcased the features in focus adequately.
So that all the participants would respond to the same stimuli, a series of 40-second video presentations was put together to explain these concepts. Applications were not described in detail, so that the participants did not feel compelled to restrict their imagination to particular potential uses.5
3.4 Data Analysis
Interviews were transcribed using Descript, and a thematic analysis was conducted per interview question using NVivo. The rationale for conducting the analysis per question was to obtain clear individual answers, while still being able to situate them within the context of each interview. To make sure no theme was overlooked by this particular method, the transcripts were investigated in their totality following the question-by-question analysis, to make sure all thematic occurrences had been noted. The method for thematic analysis followed the “phases of thematic analysis” as described by Braun and Clarke [25], that is, familiarizing yourself with the data; generating initial codes; searching for themes; reviewing themes; defining and naming themes; producing the report. In this report, we particularly look at the percentage of participants mentioning specific themes in their answers. Quantitative data were gathered also, via a Likert scale, and analysed using non-parametric, inferential statistics. A Friedman test was performed to determine differences between concept ratings, followed by a Wilcoxon signed-rank test to compare the ratings of each concept to one another. We performed a Friedman test rather than a Kruskal–Wallis test because we took a repeated measures design for each topic. This quantitative analysis complements the qualitative analysis, and offers insight into whether some opinions are widely shared among participants. This enables us to construct a global overview of the creators’ opinions on a wide range of subject matters.
4 Results
4.1 Interview Responses
For the sake of transparency, and to demonstrate how the thematic analysis is performed throughout this study, the complete table of codes is provided in Table 2. The first column corresponds to the codes recorded from the transcripts at first examination (step 2 in the phases of thematic analysis according to [25]). The ratio of participants mentioning this code, \(q\), is noted in the second column. After going through the first instances of codes, these were grouped by theme, as indicated in the third column. The ratio of participants mentioning such a group, with each participant only counted once in each group of codes, is presented in the fourth column, again labelled \(q\).
Table 2.
| Codes recorded from transcripts | \(q\) | Thematic groups | \(q\) |
|---|---|---|---|
| Connected audience | 5/16 (= 31%) | Listener engagement | 7/16 (= 44%) |
| Learning more about audiences | 1/16 (= 6%) | ||
| Reaching a global audience | 1/16 (= 6%) | ||
| Universal story | 3/16 (= 19%) | ||
| Accessibility | 1/16 (= 6%) | Personalised podcasts | 6/16 (= 38%) |
| Adaptive podcasts | 2/16 (= 13%) | ||
| Flexibility within personalisation | 1/16 (= 6%) | ||
| Interactivity | 3/16 (= 19%) | ||
| Chose your own adventure podcasts | 2/16 (= 13%) | ||
| Easier interaction | 1/16 (= 6%) | ||
| Non-fixed podcast | 1/16 (= 6%) | ||
| Celebrity interviews | 1/16 (= 6%) | Pushing or exploring other genres | 6/16 (= 38%) |
| Reality podcasts | 1/16 (= 6%) | ||
| Pushing fiction podcasts further | 3/16 (= 19%) | ||
| Pushing storytelling further | 2/16 (= 13%) | ||
| Immersion | 5/16 (= 31%) | Immersion | 5/16 (= 31%) |
| Passivity | 1/16 (= 6%) | ||
| Spatial audio | 2/16 (= 13%) | ||
| Better audio quality | 1/16 (= 6%) | Technical ameliorations | 5/16 (= 31%) |
| Recording easier, in better quality | 3/16 (= 19%) | ||
| Lower entry to production | 1/16 (= 6%) | ||
| More efficient editing | 1/16 (= 6%) | ||
| Questions the form of podcast | 2/16 (= 13%) | Questions the form of podcast | 2/16 (= 13%) |
| No changes necessary | 1/16 (= 6%) | No changes necessary | 1/16 (= 6%) |
| Prioritizing audio during production | 1/16 (= 6%) | Prioritizing audio during production | 1/16 (= 6%) |
In response to interview question (1) (p. 8), participants are keen to envision new ways of making or delivering podcasts. 7/16 (= 44%) of participants express an interest in increasing or facilitating listener engagement. Participant A shares their interest in forms of social audio:
The whole area of social audio is really interesting, and I think I would like to do more that combines social listening and on-demand audio\(\ldots\) Probably the next thing for us in terms of innovation, aside from extra insight [on our audience], and aside from producing more and better podcasts, would be to engage more deeply with our audiences. And I think possibly social audio is one way of doing that. That would be quite interesting to explore.
This is the first example we encounter of creators focusing on “listener-centric” innovations—ways to improve or change the listener experience. In a similar mindset, 6/16 (= 38%) of participants express an interest in personalised podcasting. Participant B brings up the concept of “hyper-personalisation,” meaning content is modified based on elements of the listener’s environment or context.
Hyper personalisation, that could be discretely slipped into shows to make things really interesting. The easiest example I have of what’s available right now is you can have a show and then the host is like: “It’s 6:59 PM,” and if you look at your clock, 6:59 PM too! If you were to listen again, it would [say]: “It’s three in the afternoon.” All these types of things can really make for an engaging experience. Something as simple as when you start the show, it says, “good morning” if it’s in the morning and “good afternoon” in the afternoon.
This is echoed throughout the interviews by five participants, who are keen to be able to integrate these “hyper-personalised” features into their productions.
6/16 (= 38%) are interested in expanding their own work via exploring new genres. One participant thinks podcasts do not need to be changed, but amended his answer later during the interview, talking about immersive audio and accessibility for disabled and international audiences. Overall, the idea expressed by Participant G was shared by most:
I think that we’re at such an early stage in the podcast industry, we’ve barely scratched the surface.
In response to interview question (2) (p. 8), participants focus on several aspects of their work. Table 3 represents the grouped codes emerging from participants’ answers regarding editing software. Although Adobe Audition is used by 7/16 (= 44%) of participants, 14 other types of editing software are mentioned. Participants also detail their preference in recording tools: Zoom is used as a recording tool by 5/16 (= 31%) participants, but 6 other pieces of software (like Riverside or Zencaster) are mentioned also.
Table 3.
| Editing Software | \(q\) |
|---|---|
| Adobe Audition | 7/16 (= 44%) |
| Protools | 4/16 (= 25%) |
| Sadie | 3/16 (= 19%) |
| Hindenburg | 2/16 (= 13%) |
| Logic | 2/16 (= 13%) |
| Audacity | 2/16 (= 13%) |
| Powair | 1/16 (= 6%) |
| Ableton | 1/16 (= 6%) |
| Descript | 1/16 (= 6%) |
| Reaper | 1/16 (= 6%) |
| Wavelab | 1/16 (= 6%) |
| RX Advanced | 1/16 (= 6%) |
| Garage Band | 1/16 (= 6%) |
| Sony Vegas | 1/16 (= 6%) |
| Levelator | 1/16 (= 6%) |
In response to interview question (3) (p. 8), efficiency is mentioned by 10/16 (= 63%) of participants, and so is compatibility (with software, but also with team workers). Utility is brought up in 7/16 (= 44%) of interviews, while a tool being comfortable is important to 5/16 (= 31%) of participants. 2/16 (= 13%) of creators want their tools to be good value for money. Participant K went into detail regarding their choice of software and why the most important features of podcasting software were the ability to easily collaborate on projects and follow industry conventions:
[I use] Pro Tools because the clients I work with are using it, and it really comes down to collaboration. I think that if a format were to come around that would improve on the AAF (Advanced Authoring Format) for the OMF (Open Media Framework) file exchange formats, you might see people being a little more agnostic when it comes to their audio editors. But because the predominant number of projects I use are in Pro Tools and it’s very, very hard to get information out of one audio editor and into another in a seamless way, so I’m going to use what everyone else is. If I woke up tomorrow morning and everyone was in Logic for some reason, or Reaper, I’ll learn that and use that, but that’s not the case.
The idea of setting an industry standard for podcasts to facilitate work across teams and platforms is a diverging evolution from the independent and free nature of podcast production, but as the medium evolves and attracts larger more mainstream stakeholders, the need for uniformity in format develops too.
In response to interview question (4) (p. 8), the terms used by the participants are represented in the flow diagram in Figure 1, with arrows denoting the common path from one production step to the next. Depending on the type of podcast produced, certain steps might be skipped or repeated as needed. If a process is mentioned by one participant, its background is green, whereas if it is mentioned by all 16 participants, its background is red. This particular aspect of the study was explored in more depth in a separate paper [89]. A similar workflow example can be seen in [14, Figure 3.2.3.3.1. Operational sequence diagram of radio documentary production, partitioned by role and location].
Fig. 1.
In response to interview question (5) (p. 8), an equal number of participants 8/16 (= 50%) than not say they would be deterred from using a tool if it required some coding. People who do not programme but still say they would not be bothered by the necessity of programming mentioned “ease” and “value” as key conditions to their decision.
In response to interview question (6) (p. 8), Participant D explains:
[We want the audience] to be tuning in because it’s really great content, because [the listeners] are really interested in what we’re saying, and that we’re helping them understand the world in a particular way or giving them a new view or perspective on it.
Concurrently, 11/16 (= 69%) participants mention forms of edutainment, 9/16 (= 56%) mention connecting with the content, 4/16 (= 25%) say reasons could vary depending on the programme or listener, and 3/16 (= 19%) talk about quality. This seems to highlight the desire from creators to create unique, valued programs, that can compete with other forms of media. Participant E explicitly mentions this in their answer:
We’re not just competing against audio, right. We’re not competing or just looking at the audio landscape in isolation; we are competing with incredibly immersive experiences such as gaming and social media.
4.2 Review of Demonstrations
Personalisation of Interface.
The graph in Figure 2 represents the interest of participants for different ways to interact with audio content. Participants are asked to rate on a scale 1–5 how interested they are in concepts of Touch/Tilt Recognition (\(\text{Median} = 3\), \(\text{IQR} = 1.25)\), Gesture Recognition (\(\text{Median} = 2\), \(\text{IQR} = 2\)), Metadata (\(\text{Median} = 5\), \(\text{IQR} = 1\)), Sound Recognition (\(\text{Median} = 4\), \(\text{IQR} = 2\)), and Voice Recognition (\(\text{Median} = 4\), \(\text{IQR} = 2\)). They are represented as a diverging stacked bar chart, where each bar is divided into stacked segments around a baseline, of length proportional to the percentage of participants having given each rating on the Likert scale.
Fig. 2.
A Friedman test is conducted to determine whether interest levels differ across the types of interface personalisation. The results show a significant difference (\(\chi ^2 = 21.99\), \(p \lt 0.001)\). Post-hoc tests using a Wilcoxon signed-rank test with a Bonferroni-adjusted \(\alpha\)-level of 0.05 suggests that Metadata is preferred overall to Touch/Tilt Recognition and Gesture Recognition.
In a follow-up questionnaire, participants are asked to choose their “favourite” demonstration. Out of 11 respondents and 12 demonstrations, Metadata is the preferred answer of 5/11 (= 45%) participants. Although great interest was shown for this concept, a majority of participants were adamant that all data from listeners should be gathered ethically and stored safely, such as Participant F, who rated the concept a 4 on the Likert scale (4: interested), on the condition the data were collected “within the bounds of privacy, and not making people feel like they were surveilled.”
Overall, creators imagined ways to use metadata to personalise the listener’s experience on several levels: on a platform level, Participant G noted how understanding and knowing your “niche audience” could help you “find the right audience” and “connect” with more listeners; on a business level, Participant A highlighted the importance of getting more “robust commercial models”; and on a content level, Participant H shared this specific example of how they would use the technology:
Football fans have an extremely high level of interest in the team that they follow and a negligible interest in every single other team. If we know who someone supports—or if not that kind of metadata, then at least where they are in the world—we might be able to infer what the local stories are that are of interest to them. I would use that kind of metadata in my programme now to give people in Manchester stories about Manchester clubs and players.
This is an example of how the technologies demonstrated are envisioned by participants as tools that could help adapt podcasts to a listener’s context. We see other examples of listener-centric innovations when Participant B describes how they would use Voice Recognition in their program: “You can see that it’s 11:00 PM at night, that person sounds like they’re tired, maybe you put up a different audio where the host is actually speaking a lot more relaxed and quietly, and maybe the theme song, all the guitars and drums doesn’t play,” thus bridging the concept of adapting to data contained in the listener’s voice and other contextual information.
Although the listener experience is prioritised in the phrasing of the interview questions, creators mention ways they see these technologies facilitating their workflows and production processes. For example, Participants A and C see a clear value in using sound recognition to isolate and delete unwanted sounds from recordings, while Participant I would like to see voice recognition technology evolve to include tone of voice to supplement their podcast’s transcripts.
Personalisation of Content.
Figure 3 represents the scores participants gave on a Likert scale to different types of audio content personalisation for podcasting: Voice Synthesis (\(\text{Median} = 3\), \(\text{IQR} = 2.5\)), Sound Synthesis (\(\text{Median} = 4\), \(\text{IQR} = 1.5\)), Responsive Spatialisation (\(\text{Median} = 3.5\), \(\text{IQR} = 3\)), Non-linear Narratives (\(\text{Median} = 5\), \(\text{IQR} = 1\)), Reverse-engineering Music (\(\text{Median} = 3.5\), \(\text{IQR} = 3\)), Server Communication (\(\text{Median} = 4\), \(\text{IQR} = 2\)), Levels Control (\(\text{Median} = 4\), \(\text{IQR} = 2.25\)).
Fig. 3.
A Friedman test is conducted to determine whether interest levels differ across the types of content personalisation. The results show no significant difference (\(\chi ^2 = 7.25\), \(p = 0.290\)), indicating there is no particular variance within levels of interest for these concepts. 12/16 (= 75%) of respondents rated Non-linear narratives as a “5: strongly interested.” When talking about possible applications for the concept, the idea of enabling the user to easily jump around chapters was predominant. Participants J and H expand on this:
I like this idea of being able to jump around inside of a podcast, especially the way that I do mine: discussion, interview, interview, however many interviews, and then discussion again\(\ldots\) I know some people don’t give a s— about the discussion, they just want to hear the interviews. So if they were able to jump around that way or tailor the interviews to themselves, or rearrange things based on that\(\ldots\) I think that would be kind of a neat thing.
With sports then think having that kind of branching narrative would be really useful to let the audience decide essentially the duration of the content. The podcast that I produce is short form—it’s under 10 minutes long, but there’s no reason for it to be that way.
On the topic of chapters, participants share the opinion that the current system for chapter tagging and navigating is impractical and imperfect. Overall, offering podcasts adapting to a listener’s environment is a favoured idea, being talked about unprompted by four different participants.
Although Voice Synthesis’ median interest on the Likert scale was 3, 10/16 (= 63%) participants have reservations relating to ethics, and it is rated most uninteresting by participants. Participant K details their concerns surrounding this technology:
This is really concerning technology. I’m very worried about this technology hitting the newsroom. What’s going to happen when that first debate sparks about? “Well, all we needed was an ‘S’ so I just synthesised an ‘S’ to make the noun plural”—there’s some real, real implications there.
Six participants express concerns surrounding authenticity and quality of Sound Synthesis, and 6/16 (= 38%) participants have overall reservations about Reverse-eEngineering Music. Sound Synthesis and Reverse-engineering Music are envisioned as production tools by a majority of participants (9/16 (= 56%)). The enhanced accessibility offered by Levels Control was noted by most participants, with Participant L saying:
I had this problem with my son the other day. He was trying to listen to his podcast on a long car journey. He is trying to listen to speech content and he can’t hear any dialogue because the hum of the car is too much. And you know, sometimes we might try and mix a podcast [taking these situations into account], to make sure that you can get that clarity, but not always. So an adaptive feature that makes listening more accessible is interesting.
Participant L underlines the importance of not falling into over-personalisation, or baseless personalisation, saying:
It has to have a payoff\(\ldots\) The producers have to pay the audience back for that engagement rather than just be about contact for the sake of it.
The reasoning behind personalisation is something considered by most of the interviewees. Although it is widely accepted that personalisation will play a part in how we make and consume podcasts in the near future, creators are aware of the caveats of producing personalised content for personalisation’s sake.
5 Discussion
How podcast creators envision innovation and then explore and produce with innovative techniques are matters that will affect the experience of millions of listeners worldwide. This article describes interviews that were undertaken with 16 podcast creators, in order to shed light on creators’ perceptions of next-generation podcasts, indicate how innovation might be incorporated into production workflows, and formulate some requirements and expectations of tools built to create new forms of audio-centric programming. In this final section of the article, we summarise and interpret the results of our qualitative and quantitative analyses, draw some conclusions, and finish by identifying some limitations and ideas for future work, laying down the foundations necessary to make advances in the world of podcasting, particularly in terms of production tools and listener experience.
5.1 What do Podcast Creators Envision as “Next-generation Podcasting”?
Creators interviewed in this study expressed two separate goals that appear to contradict each other. The first is to improve listener experience, through a combination of new formats, higher quality audio, or finding ways for content to be more engaging for audiences; the second is to simplify and streamline their production process, by using faster, smarter, more efficient tools. However, practices that could simplify the creator’s work, like synthesising voices, sound effects, or un-mixing music to separate tracks, could have the adverse effect of worsening the listener experience overall. Conversely, adding features to podcasts in order to improve listener experience could greatly complicate an already-convoluted workflow.
By looking at RQ1, “What do podcast creators envision as next-generation podcasting?,” we bring to light this duality in expectations. Participants agree that next-generation podcasting should involve a form of improvement of the listener experience (a “listener-centric” vision of next-generation podcasting), but they also show an interest in using the technologies presented as tools to simplify production and reduce their workload (a “creator-centric” reaction to our demonstrations). Aligning these two approaches to podcast innovations could be paramount to improving both the listener’s and the creator’s experience of podcasting. For all interviewees but one cautious independent producer, this combined improvement is synonymous with “next-generation” podcasting. Regardless of its application (listener- or creator-centric), purpose-driven innovation prevailed in participants’ reasoning, with the aim of easily producing better quality, more entertaining, informative, engaging and immersive content at the centre of “next-generation podcasting.”
In turn, this allows us to narrow down the research field for “next-generation podcasting,” by looking at the technologies that would best suit this scenario. The nuance our qualitative analysis brings to our quantitative results helps us decipher our participants’ answers and bring into focus technologies that appear plausible candidates for “next-generation podcasting,” while discarding more problematic ideas. For instance, we can discard motion-based recognition, as both Touch/Tilt and Gesture Recognition raised concerns over accessibility and disability, and generally went against the idea of podcasts being a “hands-free” medium. Reverse-engineering music to separate stems and synthesising sound effects or voices could very well be an asset for creators, but participants interviewed expressed reservations concerning ethics, authenticity, and quality, which could potentially hinder the listener experience more than the creator’s process would benefit from the implementation of these tools.
It is also important to remark that the technologies presented in the video demonstrations evoked similar ideas in participants. Four creators were interested in creating podcasts that adapted to the listener’s environment; three were keen to explore location-based personalisation; two wanted to create podcasts that varied depending on the listener’s time of day. Participant K said:
I am really looking forward to the day when a mobile device can respond to the environment that the listener was in, and automatically change the dynamics of the content, or change the loudness of the content presented to the listeners, so if you’re on a subway and it’s very loud, it will decrease the dynamic range of the content and perhaps turn it up just a little bit for you to make it easier to listen to.
These notions of adaptivity and reactivity to attributes on the user side are consistent with the concept of “perceptive media” (media that perceives one’s actions and then adapts to them), as coined by Ian Forrester, and his goal to create podcasts that adapt to the listeners [40].
Across the board, participants have stressed that they do not want to overwhelm the listeners with decisions, like Participant D who explained: “Trying to get listeners to interact or do anything\(\ldots\) It’s non-existent.” Any interactivity should therefore work in a non-intrusive fashion, hand in hand with immersion, as a means to achieve it rather than as a distraction from it, and have a clear purpose.
5.2 What Tools do Podcast Creators Use and Why?
Podcast creators value easy-to-use, highly compatible, “no-code” software. Due to the lack of standardisation within podcast production practices, both independent and BBC-affiliated creators use a variety of tools to record, edit, and distribute their podcasts. But, within this multitude, the corollaries of what is usually a collaborative process prevail, with creators favouring highly compatible, simple-to-use tools. Via RQ2, “What tools do podcast creators use and why?,” we attempt to shed light on the habits and expectations of practitioners pertaining to their software and equipment, which could give us insights into the requirements a podcasting tool should aim to fulfil.
According to answers to interview question (3) (What attributes make for good podcasting tools?), a podcasting tool should be efficient, compatible, useful, comfortable, and good value for the money (in order of importance, from most important to least important to the group of participants). This should be read in the context of participants’ current practices. For instance, the six BBC creators agreed that their choice of software was influenced by the habits of people they worked with, yet, they mention using four different DAWs (question (2): What tools are necessary for your work?). Although compatibility seems high on their list of priorities, personal preferences and background appear to play a bigger role in their choice of editing software, which speaks to the conflicting expectations of seeking universality, but lacking conformity.
This lack of conformity, but need for universality, means any new podcasting tool should aim to offer widespread support across different work tools. The need for simplicity and lack of coding expertise from the participants (question (5): Do you have any experience with coding? And would the need for coding deter you from using a tool?) informs us that any podcasting software should be very easy to use and not require any programming skills.
Understanding the desired functionalities and attributes of a new media tool is fundamental to its development [112], and, by studying the requirements and expectations of podcast producers, we present a solid foundation on which innovative podcasting tools could be built.
5.3 How Would New Tools and Habits be Integrated to Podcasters’ Established Production Workflows?
Integration of innovation will come in pre- or post-production phases. Podcast production is a complicated process, which, for the sake of producers, should be simplified rather than complexified further. Some apps such as Anchor.fm6 take this approach of drastically simplifying the podcast production process, with all the steps required for basic podcast production (Figure 1) contained within one single web app. But, if the purpose of these new tools is to add features or improve substantially on existing ones, it can be expected that a minimal modification to the archetypal workflow presented would need to occur.
In order to answer RQ3 (“Where and how would new tools and habits be integrated into their established production workflows?”), we ask about the specifics of each participant’s workflow (interview question (4): Do you have a particular workflow when creating a podcast?). Thanks to the archetypal production workflow detailed in Figure 1, we can begin to imagine where new software would fit best. We found that podcast production was a highly iterative process, and that therefore, we should respect the loops already in place (like writing \(\leftrightarrow\) recording \(\leftrightarrow\) editing), or take precautions to preserve them, but also not shy away from introducing another step that a creator could loop into their existing workflow. This analysis suggests a new step could be embedded as part of the pre-production phase, before or in tandem to booking, or in the post-production phase, after editing but before distribution.
5.4 A Note on Accessibility
Prince [87] acknowledges that podcasts are “unusually accessible,” referencing ease of use, low cost, and the flexibility that transcriptions offer to deaf or hard-of-hearing listeners. However, this last feature relies on the assumption that most podcasts would use transcripts, and that those would be of good quality. Seven participants discussed accessibility, just under half of the total number of creators interviewed. It seemed widely agreed upon that podcasts are not the most accessible in their current form, often lacking proper transcripts or simplified/audio-described interfaces. Often, transcripts for podcasts are not available, and a complicated feature for creators to include in their programmes. Although some tools already exist that facilitate this process (AI transcription tools, distribution platforms that specifically query for transcripts, etc.), these solutions often come at a cost for the creators. The multitude of distribution options and hosts, each with their own upload platforms and requirements, makes it harder for creators to expect and rely on the same accessibility features from one project to the other. This lack of consistency might in turn discourage some potential listeners. There is a clear reflection on these accessibility shortcomings in the medium as a whole by the aforementioned participants.
5.5 The Podcast Creator as a Target User
These interviews have revealed key facts about podcast creators that can be used to better plan and design tools for next-generation podcasting, as covered by the prior subsections detailing our findings. Overall, we take away that podcast creators (1) are interested in delivering better, more immersive and engaging experiences to their listeners, (2) have an already-complex workflow comprised of a wide range of tasks and skills, (3) are looking for ways to simplify this complex production process, (4) want their production tools to be efficient, compatible, useful, comfortable, a good value for the money, and no-code, (5) are looking for ways to adapt their podcasts to their listeners, (6) are concerned with accessibility and reaching as wide an audience as possible, and (7) are wary of unethical uses of AI in media.
5.6 Limitations
The exploratory nature of this study required choices to be made in preparation for the interviews. For instance, although we have justified the inclusion of the 12 demonstration videos presented, they do not represent an exhaustive list of technologies that could be used for next-generation podcasting, but rather a selection of technologies that could be implemented within a time frame appropriate to our wider research project. The demonstrations presented may therefore be perceived as a subjective collection of potential technologies, with their inclusion (and the exclusion of others) justified by the aim of our research.
Overall, we registered an average interest in the technologies demonstrated that was above the middle of the rating scale. This could be explained by participant self-selection—the recruitment process may have appealed to people who were particularly passionate about the application of new technology to audio and related media.
We chose to consider the participants’ views on technologies for content and interface personalisation independently, because the technologies in these two groups served fundamentally different goals, and were presented with a short break in between. Overall, the content and personalisation categories are rated as interesting as one another, with a median interest in these two groups of technologies of 4 on a 1–5 Likert scale.
Potential bias that some creators may have had due to prior familiarity with certain technologies also needs addressing. This might have led them to have a more favourable impression of the technologies of which they were already aware, and in turn skewed the data towards these concepts, like non-linear narratives, where all participants were familiar with various existing incarnations. It is unclear whether the high interest registered for this concept was due to a general, mainstream knowledge of the technology compared to other demos, or to a real preference.
We did not systematically collect data regarding the size of the teams in which the creators worked. We can, however, comment on our impression that results were consistent regardless of team size or affiliation, and that these two factors did not seem correlated.
Our thematic analysis was led by one investigator but checked by two others. By its very nature, qualitative analysis is subjective, but the researchers have tried to minimise human error by following current best practices [25, 31, 50], through acknowledging bias, and having discussions surrounding the codes and results [34, 68].
This study focuses solely on exploring the creators’ current production habits and outlook on the future of podcasting, in order to bridge a gap noted in the literature regarding the role and expectations of the professional podcaster. Other actors’ points of view, like those of the listeners, advertisers, or platforms, could be explored to better contextualise the research presented in this study.
5.7 Future Work
The design guidelines (Section 5.5) uncovered by the interviews can be applied to research and development projects across the industry that focus on delivering more immersive and personalised programmes to the user. Object-based audio personalisation is one of the many facets of interactivity that could be further explored using the recommendations and insights revealed by this article [113]. Tool designers who want to make it easier to produce innovative podcasts that cross over with other media—like game-ified podcasts [2, 104], or podcasts that exploit the non-linear possibilities of long-form content—could benefit from the conclusions of this article.
The question of standardisation within the podcasting world also comes to mind. With all the emerging possibilities for the medium, are we moving further away from the fixed format we are used to—the one that relies on a single, immutable MP3 file? Forrester [40] argues that an intermediary format that would support more adaptable podcasts is necessary, and proposes this could be achieved through authoring.7 This would enable podcasts to be compiled on the user’s device, relying on a markup language to deliver personalised audio content. This kind of innovative format should be supported not only by adequate production tools but also by bespoke delivery systems.
Beyond the changes in the creators’ outputs that this study could support, the evolution of producers’ and writers’ creative agency and their perception of creative agency within the context of more interactive programmes could be explored. The development of next-generation podcasts and podcasting tools will bring forth new questions surrounding both creator and listener experience, helping us understand our relationship both to audio content and personalised multimedia.
5.8 Conclusion
This study delves into the intricacies of podcast production and the concept of next-generation podcasting. It explores the current practices of podcast producers, revealing their archetypal production workflows and habits, and postulating that these preferences could form the basis for podcasting innovation and research in the future. We investigate the perspectives of independent and mainstream creators on next-generation podcasting, bringing to light their expectations for tools enabling better listener experiences, but also tools that facilitate their work, and their view of how a selection of new technologies could be leveraged within their work. The amalgamation of these findings allows us to hypothesise how a new podcasting tool could be implemented within existing production habits. This work suggests that creators would be receptive to easy-to-use, highly compatible, “no-code” software, which integrates easily within complex pre- or post-production setups, and that they are particularly interested in technologies that could be applied to adapting their content to their audience, whether for editorial or accessibility reasons.
Acknowledgments
Thank you to Catherine Robinson, Chris Pike, and Jon Francombe for their involvement as industry supervisors on this project. And thank you to the reviewers for their insightful comments on previous versions of the manuscript.
Footnotes
4
The term metadata has a wide range of definitions; more precisely, over 46 definitions are recognised by Furner [46]. Here, we mean the information stored about the user and the podcasts, particularly the ones that can help personalisation (preferences, habits, categorisations). All subsequent uses of the term “metadata” refer to this specific definition.
5
The videos are accessible at https://osf.io/nz9t2/
7
“Authoring is the process of designing and implementing an interactive presentation. The author collectively refers to the persons fulfilling roles throughout the authoring process. And authoring tools are the software and hardware tools used by an author to design or implement a presentation” (Bailey and Konstan [12]).
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Published: 23 October 2023
Online AM: 20 September 2023
Accepted: 14 August 2023
Revised: 03 July 2023
Received: 10 February 2023
Published in TOMM Volume 20, Issue 3
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View all- Kulkov IKulkova JRohrbeck RMenvielle L(2024)Leveraging Podcasts as Academic Resources: A Seven-step Methodological GuideInternational Journal of Qualitative Methods10.1177/1609406924126619723Online publication date: 25-Jul-2024
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