Ethnography Matters

danah boyd (@zephoria) is a Principal Researcher at Microsoft Research, a Research Assistant Professor in Media, Culture, and Communication at New York University, and a Fellow at Harvard’s Berkman Center. In 2009 Fast Company named boyd one of the most influential women in technology. Also in 2010, Fortune named her the smartest academic in the technology field and “the reigning expert on how young people use the Internet.” Foreign Policy named boyd one of its 2012 Top 100 Global Thinkers “for showing us that Big Data isn’t necessarily better data”. danah just published, It’s Complicated: The Social Lives of Networked Teens.  

There’s this idea that hard-core techies are code geeks. But hard-core techies also look like ethnographers. A tech ethnographer not only has to understand cultural code, but the mechanisms for how software design links back up to tech practices. I sat down with one of the most well known tech ethnographers of our time, danah boyd (@zephoria). 

Over breakfast at The Ace Hotel’s Breslin, danah and I talked about her career. This fascinating and personal interview reveals danah’s journey through industry and academia.

We’re also excited to have danah’s interview launch Ethnography Matter’s second column, Tell Me More,  featuring interviews with people who are pushing the boundaries of ethnography in unconventional and exciting ways. We conduct the first interview and then post a follow up interview with crowd-sourced questions from the audience. 

Post your follow-up question for danah in the comments or tweet it with the hashtag #askdanah by March 10. danah will select her favorite questions to answer in her second interview!  

Tricia: danah, I’m super excited that we get to talk ethnography over some yummy breakfast food! Earlier last year, you were inducted into the SXSW Hall of Fame.  An ethnographer being validated by geeks! I was beyond excited when I heard this news. How did you feel when you found out?

danah: SXSW has been a very important event to me for a long time. I learned so much about the tech industry through that conference by spending late nights drinking with entrepreneurs and makers. I actually got many a job that way too. It was at SXSW where Ev Williams and I started debating blogging practices. He hired me to work for him that summer.  Oh, and SXSW was where I met my partner.

Tricia: What? Are you serious?

danah: ::laugh:: Ayup!  And now we have a baby who we’re taking back to SXSW this year.

Tricia: Shut up. That is so sweet. Where did you guys meet at SXSW?

danah. At a Sleater-Kinney show.

Tricia: That’s awesome.

danah: It’s just funny to be honored there because I’ve selfishly gotten so much out of the conference.

Tricia: Well I remember very clearly when I read the transcript of the keynote you delivered at SXSW in 2010. It was about Facebook’s issues with privacy. Your talk generated so much discussion. How did you settle on this topic?

danah: I thought, what could I do that would provoke this audience to think? I saw it as a political platform; not big P but small p. I wanted to use this opportunity to challenge norms inside tech industry. I decided to take on the underlying values and beliefs in tech industry regarding privacy because my research was showing that the rhetoric being espoused was naïve. My topic was not surprising for academics, but it was for practitioners.Read More… Tell Me More danah boyd: an interview with the author of “It’s Complicated: The Social Lives of Networked Teens”

Translation

English中文(简体)FrançaisEspañol

by

You can help improve the automatic translation by checking off “Edit Translation” after you select a language. Thanks!

This month’s theme features a series of posts from EPIC 2103  (Ethnographic Praxis In Industry Conference)and is edited by Ethnography Matters co-founder, Tricia Wang (@triciawang), who gave the opening keynote at EPIC, “The Conceit of Oracles: How we ended up in a world in which quantitative data is more valued than qualitative data” (transcript).

Most ethnography conferences are largely academic affairs and have been ongoing for years. The American Anthropological Association is in its 113^th year; the Ethnography in Education Research Forum, its 35^th; the Ethnographic and Qualitative Research Conference, its 26^th; and the Chicago Ethnography Conference, its 16^th. In contrast to conferences that are mostly academic in nature from the speakers to the attendees and content, one relatively new conference focuses on the work ethnographers do within organizations: EPIC (Ethnographic Praxis In Industry Conference), which was held most recently in London from September 15-18, 2013 (draft proceedings of papers & program).

Before attending an ethnographic conference, there is a critical question that must be answered: Why go to an ethnography conference? This is not a trick question. It is something that I have asked myself a number of times. In fact, I had honestly been unsure of the value of such conferences. That is, until I attended EPIC 2013. Let me elaborate…

Consider the hypothetical in which you are a superhero. You would likely want to hang out with a team with different super powers(a la X-Men or Justice League), not a team comprised of clones of yourself. So for most of my career, I didn’t prioritize going to ethnographic industry events. That said, I have attended my fair share of academic conferences such as HCI, CHI, CSCW, and ASA. By and large, I haven’t been overly impressed; the academic rigor of presentations wasn’t always coupled with inspiration and the events could be incredibly sleep-inducing (except for the fun meet ups afterwards where everyone becomes human!). I generally prefer conferences that challenge me to think about the unfamiliar, which shouldn’t be surprising to hear from an ethnographer.

But I can now testify that I have attended my first ethnography industry gathering and I found it very inspirational, indeed!

In September 2013, I traveled to London to attend and speak at EPIC 2013. It was an honor to deliver the conference-opening keynote lecture entitled “The Conceit of Oracles: How we ended up in a world in which quantitative data is more valued than qualitative data” (transcript). While there was some variability in the quality of the presentations, the ones that were high quality were beyond inspirational. Equally brain-exploding were the fantastic hallway conversations with other accomplished ethnographers.

EPIC is a gathering where academic ethnographers and corporate ethnographers mingle as equals. In its sixth year, EPIC “promotes the use of ethnographic investigations and principles in the study of human behavior as they are applied in business settings.” EPIC started out with folks who were working at large tech companies such as IBM, Xerox Parc, Intel, and Microsoft, but it has now evolved into a conference that welcomes attendees working in boutique research firms, design studios, and consulting agencies.

There is no other conference in our field that is so interdisciplinary in attendance and ideas. I met attendees who deal with ethnography in every context, including marketing, strategy, design, research, and academia. Simply put, this is the conference to go to if you wish to learn how to make products, services, and organizations that truly serve people.

To capture the memorable presentations, interesting conversations, and useful workshops from EPIC 2013, Ethnography Matters will present a series of guest posts from presenters and attendees of the conference.Read More… Why go to an ethnography conference?: Notes from the EPIC 2013 Conference

Translation

English中文(简体)FrançaisEspañol

by

You can help improve the automatic translation by checking off “Edit Translation” after you select a language. Thanks!

Tricia Wang

Editor’s Note: Tricia provides an excellent segue between last month’s “Ethnomining” Special Edition and this month’s on “Talking to Companies about Ethnography.” She offers further thoughts building on our collective discussion (perhaps bordering on obsession?) with the big data trend. With nuance she tackles and reinvents some of the terminology circulating in the various industries that wish to make use of social research. In the wake of big data, ethnographers, she suggests, can offer thick data. In the face of derisive mention of “anecdotes” we ought to stand up to defend the value of stories.

__________________________________________________

image from Mark Smiciklas at Intersection Consulting

Big Data can have enormous appeal. Who wants to be thought of as a small thinker when there is an opportunity to go BIG?

The positivistic bias in favor of Big Data (a term often used to describe the quantitative data that is produced through analysis of enormous datasets) as an objective way to understand our world presents challenges for ethnographers. What are ethnographers to do when our research is seen as insignificant or invaluable? Can we simply ignore Big Data as too muddled in hype to be useful?

No. Ethnographers must engage with Big Data. Otherwise our work can be all too easily shoved into another department, minimized as a small line item on a budget, and relegated to the small data corner. But how can our kind of research be seen as an equally important to algorithmically processed data? What is the ethnographer’s 10 second elevator pitch to a room of data scientists?

…and GO!

Big Data produces so much information that it needs something more to bridge and/or reveal knowledge gaps. That’s why ethnographic work holds such enormous value in the era of Big Data.

Lacking the conceptual words to quickly position the value of ethnographic work in the context of Big Data, I have begun, over the last year, to employ the term Thick Data (with a nod to Clifford Geertz!) to advocate for integrative approaches to research. Thick Data uncovers the meaning behind Big Data visualization and analysis.

Thick Data: ethnographic approaches that uncover the meaning behind Big Data visualization and analysis.

Thick Data analysis primarily relies on human brain power to process a small “N” while big data analysis requires computational power (of course with humans writing the algorithms) to process a large “N”. Big Data reveals insights with a particular range of data points, while Thick Data reveals the social context of and connections between data points. Big Data delivers numbers; thick data delivers stories. Big data relies on machine learning; thick data relies on human learning.

Read More… Big Data Needs Thick Data

Translation

English中文(简体)FrançaisEspañol

by

You can help improve the automatic translation by checking off “Edit Translation” after you select a language. Thanks!

Rant this way ~ Photo by Nesster, CC BY-SA

Heather pointed out these comments by Bob Garfield from a recent broadcast of On the Media (“Sentiment Analysis Reveals How the World is Feeling“):

I’ve been arguing for years that qualitative research, focus groups and the like, are not research at all. They don’t generate data. It’s statistically insignificant, easily manipulated, and from my perspective just as likely to be exactly wrong as exactly right.

Garfield then adds:

But it seems to me that what you’re dealing with is something that deals with all of my objections, because you’ve got the world’s largest focus group.

Sigh. This is wrong on so many levels, and anyone who is interested in ethnography already knows why, but just to touch on some of the problems:

• Qualitative research can generate data. The tweets used in Johann Bollen‘s [1] sentiment analysis (the subject of this OTM episode), interview transcripts, field notes, photos, audiorecordings, visual recordings: all data. Some research within the qualitative tradition also generates numeric data [2] by, for example, calculating measures of intercoder reliability, or in the analysis of card sorting tasks.
  –
• There is a lot more to statistical testing than statistical significance (and some controversy among statisticians about overuse of significance testing). There is also more to quantitative analysis than statistical testing. Bayesian inference, for example, could be thought of as quantitative analysis that is not necessarily statistical testing.
  –
• Similarly, qualitative research cannot be reduced to “focus groups and the like”. The purposes, strengths and weaknesses of focus groups are very different from those of other qualitative methods such as [participant-]observation and one-on-one interviews [3].
  –
• Using statistical testing as a marker for what is or is not research omits work that has formed the backbone of the sciences such as classical experimentation, disconfirmation by example, comparative methods for creating typologies and analyzing artifacts, etc.
  –
• “Easily manipulated”? Yup, research findings in general can be manipulated. Statistical testing is really easy to manipulate.

Garfield’s statement also suggests either ignorance or dismissal of mixed methods research, which, I would argue, is increasingly becoming a gold standard for research in some fields, such as public health.

There’s a hint at why mixed methods have become so important in public health research in Garfield’s comment about “the world’s largest focus group.” Bollen’s use of a large collection of corpora is well-suited to his purposes, but other purposes can require different or additional kinds of work.

Let’s say I do a giant public health survey. If a minority in my sample doesn’t interpret a word or phrase in the same way that the majority interprets it, if some questions make no sense at all from their perspective, if people writing the survey have no idea what minority members’ concerns or experiences even are much less how they’re relevant to health, then the survey results will be meaningless for that social group.

There is no such thing as a survey that is not culturally informed. Without ethnographic work and awareness, surveys, public health information and campaigns, etc., will likely be culturally informed by those who are most powerful and/or in the majority. Qualitative research is indispensable for addressing structural health inequities affecting the less powerful. Should ethnographic work focused on these inequities be patted on the head and assured that it’s nice, but it’s not-really-research? Fortunately, the NIH does not think so.

Sometimes I wonder if people miss how widespread and useful qualitative work is because it can be invisible (see Tricia‘s related post about the ‘Invisibility of Ethnography‘). A couple recent episodes of On the Media may clarify the kind of research that Garfield is dismissing here, while at the same time (perhaps unknowingly?) depending on it.

On Nov. 4th, Garfield spoke with social media researcher danah boyd about “Parents helping kids lie online.” The paper [4] behind this interview presents quantitative summaries of survey data — “real” research, perhaps, to Garfield.  But hmm, how and why was this survey designed?

Read More… Qualitative research is not research at all?

Translation

English中文(简体)FrançaisEspañol

by

You can help improve the automatic translation by checking off “Edit Translation” after you select a language. Thanks!