Data Sampling, Tracking, and Tracing

This section discusses more details of the data I sampled and the methodologies I used to analyze them.

The main set of data that I analyzed as part of my PhD research consists of content posted on and tied to the mommy vlogging channels of seven mommy vloggers. Poly-storying practices and the identities born out of these activities are multisemiotic: participants can make use of, and combine in various ways, the affordances of audio and visual media. They can also hyperlink social media content, participants, and sites.¹ Hence, strategies used by mommy vloggers to construct influencer identities on their channels are multimodal. To gain a comprehensive understanding of them, it is necessary to analyze how they use and combine various media and associated semiotic resources (e.g., spoken and written language, sound, and moving and still images). The key self-presentational affordances on YouTube pages I explored in my analysis are:

• mommy vlogs (including captions, thumbnail images, description boxes, and comment sections)
• channel names
• channel art
• channel icons
• channel About pages.

YouTube channel names, art, icons, and About pages are centrally laid out to encourage people to make explicit, visually accompanied claims about how they want themselves to be understood.

Social media profile generation invites users to define themselves as what Bamberg would refer to and study as positioning level 3,² which denotes tellers’ claims to identities that go beyond a particular communicative event. boyd pointed this out in 2006, when she argued that by crafting a profile, social media users attempt to write a certain self “into being,” guiding profile visitors’ impressions of them.³ To identify narrative strategies used by mommy vloggers to present themselves as mommy vlogger influencers, it hence is essential to gain a comprehensive understanding of how they use these sites.

A YouTube channel’s channel art banner is the customizable banner image that makes up the header of all the YouTube pages in that panel. Channel icons are YouTube’s equivalent of a profile photo, that is, the thumbnail image that along with the channel name represents a given channel across YouTube. This image also is displayed in the lower right corner of the channel art banner.

Channel About pages are one of six pages of a YouTube Channel. As detailed below, I sampled the seven mommy vloggers’ YouTube channel About pages on March 22, 2017. At this time, they consisted of four optional modules:

1. Description module: YouTube’s version of an About section. The Description module by default lists channel subscriber count, total view count, and the date that the channel was opened.
2. Details module: an optional module in which channel owners could provide an email address “for business inquiries” and select a country of residence.
3. Links module: this appears at the bottom of the About channel page and displays clickable icons which link to the channel owners’ other social media profiles and website(s).
4. Related Channels module: this displays a list of suggested channels, generated by YouTube's recommendation algorithm and thus are beyond the agency of the channel owner. The Related Channels feature can be disabled. However, channels that do so will not be promoted in the Related Channels module on other channels.

Channel owners can also add a Featured Channels module to their channel: a customized list that a channel owner opts in to promote on their channel. This module appears on the channel Home and About pages, and the recommended channels are also listed in the Channels page, which displays the other channels the account holder has subscribed to.

In addition to analyzing the above choices, I also explore how mommy vloggers present themselves as mommy vlogger influencers in their mommy vlogs. To do this, I sampled 557 mommy vlogs and tracked and traced activities on their channels across time and across social media sites between November 1, 2016, and June 1, 2019, choosing the fifty most recent and thirty most popular videos (i.e., those with the highest view count) for content analysis.

The Videos page of a YouTube channel provides an archive of public video uploads to that channel. The default view of this archive is reverse chronological order (i.e., “Date added (newest first)”). However, in the drop-down bar in the top right corner of the Videos page, audiences can set videos to be arranged according to their view count, with the most popular at the top, or in chronological order (i.e. “Date added (oldest first)”). Three of the fifty most recent videos (one by Umbumgo Family Vlogs and two by bitsandClips/mariethatsme) are also among the respective vloggers’ thirty “most popular.” These videos were only coded once, which is why the total number of coded videos is 557 instead of 560.

I decided against downloading the 557 videos sampled for coding in NVivo. Although doing so would have allowed me to store and better protect my data set from subsequent changes, and would also have limited my impact on my sample (my clicks and watch time played into video and engagement metrics), they add up to approximately 84 hours of video material. This would have demanded a lot of time and storage space to download/store. Instead, I coded the 557 videos while watching them on YouTube, attaching nodes to their corresponding thumbnail images in NVivo (see screenshot). I did, however, download 113 videos along with their comment sections, description boxes, video thumbnails (as shown in YouTube searches), as well as video suggestions in the Watch Next module associated with them and material that was tied to the vlogs that seemed significant.

Due to their different upload schedules, the time span covered by the fifty most recent videos varies.

I decided to focus on the mommy vloggers’ fifty most recent and thirty most clicked videos because I wanted to gain a comprehensive understanding of the mommy vlogs by these seven vloggers that viewers were most likely to watch at the time I was data sampling. While recency and popularity are not their only criteria, suggestion algorithms on YouTube do favor recency and view count. This means that “newest” and “most popular” videos are likely to rank high in YouTube suggestions, such as search results or Watch Next panels. Furthermore, because videos on a channel’s Videos pages are, by default, displayed in reverse chronological order and the view can be set to “most popular,” these criteria regulate which videos audiences are shown when they enter the archive of videos on mommy vloggers’ channels. For these reasons, a sample consisting of the most recent and most popular videos is likely to contain the mommy vlogs by the seven mommy vloggers that at the time of sampling are most likely to draw audiences to, and provide inroads into, their channels and material posted about them.

Importantly, I do not attempt to relate aspects of mommy vlogs’ content or how they are shared to their view count to make inferences about the effects of particular features of vlogs on view count. This would require a comparative analysis, which would have to take into account a broad variety of variables related to YouTube audiences (e.g., personal watch history, search history, subscriptions, subscription settings), content creators (e.g., upload schedule, sponsorship, time of posting), and Google’s corporate interests and agendas (e.g., pushing specific (types of) content or channels). These variables all factor into the paths that algorithms direct audience traffic along by making a certain selection of content visible to audiences.

In addition to sampling 557 mommy vlogs to conduct a content analysis, I also tracked and traced how the forms and practices of mommy vlogging have evolved over time. This entailed:

1. watching back all videos listed in the seven mommy vloggers’ Videos channel page that uploaded before March 22, 2017
2. conducting weekly check-ins of their YouTube activities to follow and document ongoing and unfolding activities on their channel between November 1, 2016, and June 1, 2019.

I also followed and documented intertextual traces created by the seven mommy vloggers, their audiences, and YouTube algorithms that linked mommy vlogging channels to other content, sites, and participants. Material can be tied to mommy vlogs through links and references in mommy vlogs, video titles, thumbnail images, description boxes, or comment sections or through YouTube playlists and video suggestions offered by YouTube in the Watch Next panel on a video Watch page (i.e., when a given video is playing).

A video thumbnail image is the clickable image that represents a given video on YouTube. It is added to videos in what, at the time, was called YouTube Creator Studio, and is now simply YouTube Studio, during the upload process. At this point, the channel owner is also prompted to “Add [a] description” that will appear in the video description box. In addition to constituting clickable icons that serve to visually organize videos on YouTube, the video thumbnail, title, and description box are sites that can be used to contextualize vlogs. By using these sites to reveal, foreground, and conceal certain information, vloggers can alert audiences to what to expect if they play the video. Through this, they can frame how videos are to be understood before they are actually played/watched. Frame here is understood in a Goffmanian sense, as “schemata of interpretation,” established or evoked by people “to locate, perceive, identify, and label events and occurrences.”⁴ Once clicked, a video’s thumbnail is no longer visible, but its description box is, and the text in it and the video title combine to literally frame the running video, adding to the discursive context within which vlogs are interpreted.

At the same time, I was tracking and tracing the flow of personal information circulating in social media about the seven mommy vloggers, taking notes and screenshots to keep track of their follower base(s) across their social media profiles, their exposure in traditional and social media, and changes in YouTube platform features and algorithms.