Digital ethnography is a relatively new field of study which promises, when done well, to deepen the relationship between communicators and their audiences by developing and understanding context. In this series, we’ll examine digital ethnography – a field of study pioneered by our colleagues at NATIONAL Public Relations. We’ll explore why it’s important, what it is, major frameworks and limitations, and how digital ethnography will be practiced by PR practitioners.
Why Frameworks Matter
To deliver powerful insights about the people, organizations, and cultures we’re studying with digital ethnography, we need a framework to ensure we don’t miss vital pieces of the narrative. Anyone can download a bunch of semi-random tweets or Instagram photos using a hashtag and cobble together a slideshow. What separates true, disciplined ethnography from random noise is the foundational framework we use to organize our study.
The ethnography framework is like the blueprint for the house. A few master carpenters with decades of experience could build a house entirely from memory, intuition, and experience. The vast majority of construction professionals still prefer a blueprint to ensure a successful outcome.
Spradley: The Parent Framework
While many ethnographic frameworks exist, the parent framework in ethnography is James P. Spradley’s 9 Dimensions of Descriptive Observation, a method of collection intended for qualitative interviewing.
Dr. Spradley developed his framework to help ethnographers and anthropologists standardize what observations they made; in his 1979 book, he noted that ethnography was one of the few methods which required data collection, analysis, and narrative construction simultaneously. Ethnographers often missed details because of the heavy cognitive load of conducting real-time research, and his framework helps ensure we collect everything relevant. Subsequent frameworks often map back to Spradley’s original 9 dimensions.
The 9 Dimensions in Spradley’s works include:
- Space: the physical setting, such as rooms, places, locations, etc.
- Actors: the people involved in the study.
- Activities: the activities conducted by the actors.
- Objects: the physical elements involved in the activities and space, used by the actors.
- Acts: the individual actions taken by actors.
- Events: context of the acts, actors, and space, such as a meeting or a dinner.
- Time: the sequence of events from beginning to end.
- Goals: what the actors seek to accomplish in their acts.
- Feelings: what emotions the actors express in the events.
Translating Spradley’s 9 Dimensions to Digital
One of the challenges of digital ethnography is that while we have a strong historical record of what actors say, we don’t necessarily have non-verbal data, nor do we have acts and actions taken that our actors didn’t publish.
However, as mobile applications, particularly Facebook, become more pervasive – and arguably invasive – more of Spradley’s dimensions are revealed by users. Consider how much of Spradley’s dimensions are now provided in today’s smartphone-enabled, always-on world:
- Space: we ascertain physical setting through check-in data of locations as well as photography
- Actors: Facebook’s image recognition software automatically tags and suggests other users in photos
- Activities: often described by the actors or depicted in photos
- Objects: provided by photographic data, sometimes described by actors
- Acts: often described by the actors
- Events: provided by photos, geo-location data, and description, as well as meta-data (such as a conference or cultural occurrence using a hashtag, especially on Instagram and Twitter)
- Time: automatically provided by social network data
- Goals: solely provided by actors
- Feelings: solely provided by actors, but encouraged by apps such as Facebook’s Reactions and Snapchat filters
Best of Both Worlds
We’ve established previously that what actors publish on social media may be less subject to the Hawthorne effect. However, as we see from Spradley’s framework above, digital ethnography has its own limitations, its own data gaps.
Assuming time and resources permit, we will ascertain the most comprehensive picture of our actors, our audience through a combination of digital and classical ethnographic research. To ensure a thorough study, we need the non-verbal, contextual data which comes only through firsthand observation. We also need the unobserved, unsolicited data from digital ethnography to fill in gaps where researchers may not get honest feedback or outside of study hours/contexts.
In the next post in this series, we will examine some examples of digital ethnography and the most powerful tools of the trade we have available to us today.
Christopher S. Penn
Vice President, Marketing Technology