Tag Archives: big data

Tell Me More danah boyd: an interview with the author of “It’s Complicated: The Social Lives of Networked Teens”


MSR3sm-sq 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”

Ethnography in Communities of Big Data: Contested expectations for data in the 23andme and FDA Controversy


IMG_2834 Brittany Fiore-Silfvast (@brittafiore) is a PhD candidate in Communication at the University of Washington and she holds an MA in sociocultural anthropology from Columbia University. Her research focuses on the relationship of technology and emerging cultural and organizational forms. Her work cited in this article was supported in part by an NSF Doctoral Dissertation Improvement Grant and an Intel grant.

Editor’s note: One of the disciplines big data is most strongly influencing is medicine, and here Brittany Fiore-Silfvast (@brittafiore) applies her expertise to examine the interplay between health and technology to understand the implications of today’s unprecedented levels of patient data collection and analysis (although, notably, seldom including access to the data by those very patients who produced it).

Brittany hits upon a key issue with her post: seeing “big data” as a means of eliminating uncertainty through statistical analysis. While the elimination of uncertainty through statistical analysis is nothing new, the difference today is the scale at which collection and analysis of such data is unfolding and the diversity of the fields in which it is occurring.

Read on to discover the nature of conflict between the main personal genetics testing company 23andme, the importance of and difference between big data, small data, thick data, and DaM data, and the role that “Blue Suede Shoes” play in all of this.

For more posts from this EPIC edition curated by  editor Tricia Wang (who gave the opening keynoted talk at EPIC this year), follow this link.
23andme box

Scott Beale / Laughing Squid laughingsquid.com

Across the field of health and wellness there is a lot of talk about data, from consumer self-tracking and Quantified Self data, to data-driven, personalized health care, to data-intensive, crowd sourced, scientific discovery. But what are these different stakeholders talking about when they talk about data and are they talking about the same thing?

At EPIC, in the “Big Data/Ethnography or Big Data Ethnography” session, I presented on this topic drawing from our ethnography of the impact of consumer big and small data on institutions of healthcare. In this post I use the recent controversy between the FDA and personal genetics testing company, 23andme, to exemplify many of the concepts my co-author, Dr. Gina Neff, and I develop in our EPIC paper “What we talk about when we talk data: Valences and the social performance of multiple metrics in digital health”, rather than simply re-present them.  I also demonstrate how ethnography can be leveraged in the context of so-called “big data” or data intensive transformations in science and practice.Read More… Ethnography in Communities of Big Data: Contested expectations for data in the 23andme and FDA Controversy

I’m Coming Out: Four Awkward Conversations for Commercial Ethnographers


459372_561559630554768_2122767149_o With an approach built on ethnography and design methodologies, Drew Smith (@drewpasmith) delights in bringing consumer and client to the conference table. In the process, he works with them to co-create game-changing products, services and businesses for some of the world’s biggest companies.  Drew shapes culture and strategy at Seren Partners. He blogs occasionally at DownsideUpDesign and posts pictures of cars, mostly side-on, here.

Editor’s Note: I asked Drew Smith (@drewpasmith) to kick off our January EPIC theme because of his background as a designer and a tweet that he had sent. Until Drew attended EPIC 2103, he was hesitant to say that he was an ethnographer in certain professional contexts. But after listening to my opening keynote for EPIC 2013, he tweeted, “Today, I’m coming out. I’m an @ethnographer!” We had an interesting chat afterwards where Drew explained to me why he would even need to “come out of the closet.” It was a fascinating conversation and one that many readers will relate to, especially if you work in a design or strategy agency where you may be the one person with very proficient ethnographic skills.

So I thought it would be interesting to hear how someone with a strong design background experienced EPIC 2013. In Drew’s first guest post on Ethnography Matters, he urges designers and strategists with ethnographic skills be brave: commercial ethnography needs to come out of the closet. Drew provides some conversations that will help us get there.

For more posts from this January EPIC edition curated by contributing editor Tricia Wang, follow this link.

Slide145Over the course of my career I’ve developed an unwavering belief in the transformative power of ethnography. I’ve used its tools and techniques to bring about positive change for my clients, shaping products, services, businesses and brands with the rich, people-centred insight it can bring to bear.

Yet until recently, I’d never called myself an ethnographer; I’ve always been an automotive designer-turned-strategist. This is the story of how that came to change.

Ethnography by Another Name

During my student years, I’d come to know a London co-creation agency called Sense Worldwide. They had a mission to “make things better, by making better things”, a concept that was deeply appealing to an idealistic young designer.

We built trust and I allowed them to explore how I was using social networks (the early days of Facebook, the mid-life crisis of Gaydar) and why I was dreaming of upgrading my Sony Ericsson K750 to a Nokia N95. Together, we came up with ideas to make my world of mobile technology better. I loved the experience so much that I wanted to work for them.

Desperate, keen and with none of the ethnography or anthropology qualifications that usually accompanied their recruits, Sense Worldwide nevertheless took a chance. Without realising it, I became an ethnographer by the back door.

During my time there, I witnessed the profound impact that ethnographic research could have. The stories and insight pulled back from the field transformed not only  the way new products and services were developed, but also how companies were led and run.

I noticed, however, that getting ethnography on the table with prospective clients was a challenge. It was often perceived as expensive and more than a little quirky. To ease the sales process, we adopted a series of jazz-handed 1-liners that got ethnography sold, perhaps overly so. Yes, we conducted ethnographic research, but sometimes our practice failed to live up to the over-the-top expectations set by language designed to hide our commercial awkwardness.Read More… I’m Coming Out: Four Awkward Conversations for Commercial Ethnographers

Big Data Needs Thick Data


Tricia Wang

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.

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image from Mark Smiciklas at Intersection Consulting

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

Reaching Those Beyond Big Data


Editor’s Note: Opening up the Stories to Action edition is Panthea Lee’s @panthealee moving story about a human trafficking outreach campaign that her company, Reboot, designed for Safe Horizon.  In David Brook’s recent NYT column, What Data Can’t Do, he lists several things that big data is unable to accomplish. After reading the notes to Panthea’s talk below, we’d all agree that big data also leaves out people who live”off the grid.”

As Panthea tells her story about Fatou (pseudonym), a person who has been trafficked, we learn that many of the services we use to make our lives easier, like Google Maps or Hop Stop, are also used by human traffickers to maintain dominance and power over people they are controlling. Panthea shares the early prototypes in Reboot’s design and how they decided to create a campaign that would take place at cash checking shops. 

Below, Panthea shares her notes to the talk that she gave at Microsoft’s annual Social Computing Symposium organized by Lily Cheng at NYU’s ITP. You can also view the video version of her talk

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We’ve made great strides in data-driven policymaking, open government, and civic technology –– many of the folks in this room have made significant contributions in these domains. But, as we know, many people, even here in New York City, still live “off the grid”––and the issues of access go beyond “digital divide”.

As a designer working on governance and development issues––fields where economists regularly eat anthropologists for lunch––this is something I think a lot about.

In the era of Big Data, as we become increasingly reliant on capital-d Data, I wonder what might exist in the negative space? Who are we not capturing in our datasets? And how might we reach them?

Slide02

A few months ago, I met a young woman from Benin who I will call Fatou (not her real name). Fatou had been adopted by an American preacher on mission in Benin, and brought to the United States. She and her family were overjoyed at her good fortune.

Fatou was pleased, she felt taken care of with her new “mother” and “father” in Queens. They started her on English lessons to help her adjust to the US and to allow her to enroll in school, a longtime dream.

But even from the outset, some things seemed strange to her.

Whenever they left the house, “to keep her safe”, her mother always held her by the wrist, keeping a firm grip. She wasn’t allowed any possessions beyond clothing. Her belongings were regularly searched for any material she kept, particularly information (pamphlets, papers). If found, they were confiscated. She worked long hours at a school the family owned. She was never herself enrolled in school, as promised, and when she inquired about her education, she was told to stop being ungrateful.

At first, Fatou thought these were just US customs. But then things got worse.Read More… Reaching Those Beyond Big Data

In between is the place where you have to understand people: Social science, stigma, and data big or small


Judd and Tamar

Editor’s Note: Judd Antin @juddantin is a social psychologist and user experience researcher who studies motivations for online participation. In 2011, he was named an MIT Technology Review Innovator Under 35. Prior to joining Facebook, he worked with Yahoo Research.  His educational background includes Applied Anthropology, Information Science, and training at the French Culinary Institute. One of my favorite papers of his is Readers are Not Free Riders: Reading as a form of participation on Wikpedia (pdf) [1].

Tamar Antin is a research scientist who uses mixed and especially qualitative methods to critically examine public health policies and narratives. She has several years of experience in public health research. One of her recent publications is Food Choice As a Multidimensional Experience [2].   Her dissertation [3] combining three papers on food choices and body image is excellent reading for any student of qualitative methods. 

I’ve known Tamar and Judd for several years now, and Tamar has been a mentor to me. Every time Tamar and I talk about research and ethnography, it never seems to last long enough; I just want to ask her more questions. And every time I see Judd, I want to ask him a million questions too. So a post for Ethnography Matters was a great excuse to get together with them for a chat on anthropology, Big Data and Small Data, and other interesting things.  –  Rachelle

P.S. This isn’t a straight transcript of our conversation but a sort of Frankenstein transcript made out of chopped up pieces sewn back together. 

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1. Two Ethnographers
2. What they’re working on
3. Stigma and hacking
4. Qualitative research as art, science and handmaiden
5. Big Data and Small Data

1. Two Ethnographers

What’s your background in anthropology?.

Judd: I have an undergraduate degree in anthro from Johns Hopkins, where I was one of seven anthropology majors I think, like in the whole university. It was a small department. I got interested in anthro primarily because of my adviser, who became our friend, Felicity Northcott. Coincidentally she also married Tamar and I. She was internet ordained and she officiated our wedding. She’s awesome.  She was just a very down to earth, foul-mouthed, passionate anthropologist.

Tamar: And for me, I have an undergraduate degree in anthropology also, from the University of Texas. I was having this conversation with the undergraduate adviser there at the end of my senior year, like okay now I have this degree, but I didn’t really know what to do with it. I went to the career center, and they had a list of all the jobs that you could do with certain majors, and I think the only job that was listed for anthropology majors was travel agent.

Judd: What?

Tamar: Oh yeah. I was thinking, well I don’t want to do that.

Judd: Travel agent?!

Read More… In between is the place where you have to understand people: Social science, stigma, and data big or small

Where does ethnography belong? Thoughts on WikiSym 2012


On the first day of WikiSym last week, as we started preparing for the open space track and the crowd was being petitioned for new sessions over lunch, I suddenly thought that it might be a good idea for researchers who used ethnographic methods to get together to talk about the challenges we were facing and the successes we were having. So I took the mic and asked how many people used ethnographic methods in their research. After a few raised their hands, I announced that lunch would be spent talking about ethnography for those who were interested. Almost a dozen people – many of whom are big data analysts – came to listen and talk at a small Greek restaurant in the center of Linz. I was impressed that so many quantitative researchers came to listen and try to understand how they might integrate ethnographic methods into their research. It made me excited about the potential of ethnographic research methods in this community, but by the end of the conference, I was worried about the assumptions on which much of the research on Wikipedia is based, and at what this means for the way that we understand Wikipedia in the world. 

WikiSym (Wiki Symposium) is the annual meeting of researchers, practitioners and wiki engineers to talk about everything to do with wikis and open collaboration. Founded by the father of the wiki, Ward Cunningham and others, the conference started off as a place where wiki engineers would gather to advance the field. Seven years later, WikiSym is dominated by big data quantitative analyses of English Wikipedia.

Some participants were worried about the movement away from engineering topics (like designing better wiki platforms), while others were worried about the fact that Wikipedia (and its platform, MediaWiki) dominates the proceedings, leaving other equally valuable sites like Wikia and platforms like TikiWiki under-studied.

So, in the spirit of the times, I drew up a few rough analyses of papers presented.

(Wikipedia and its platform, MediaWiki are but one of a host of other wiki communities and platforms which is why I’ve distinguished between Wikipedia and others.)

It would be interesting to look at this for other years to see whether the recent Big Data trend is having an impact on Wikipedia research and whether research related to Wikipedia (rather than other open collaboration communities) is on the rise. One thing I did notice was that the demo track was a lot larger this year than the previous two years. Hopefully that is a good sign for the future because it is here that research is put into practice through the design of alternative tools. A good example is Jodi Schneider’s research on Wikipedia deletions that she then used to conceptualize alternative interfaces  that would simplify the process and help to ensure that each article would be dealt with more fairly.

Talking about ethnography?

I am still intrigued by the fact that so many quantitative analysts wanted to know about ethnography during our open space session. We started the session with those who had done ethnographic work talking about their experiences: Stuart Geiger talked about his ethnographic work on Wikipedia bots, Isis Amelie Hjorth talked about her ethnographic enquiry into Wreckamovie, the collaborative movie outfit from Finland and Paško Bilić discussed how he studied breaking news stories on Wikipedia. Others wanted to know how you even begin to do ethnographic research on Wikipedia when editors are a) anonymous and b) located all around the world. One participant said, “I’m faced with 3 million edits (in my dataset) and I have to say something about them. How do I even begin?”Read More… Where does ethnography belong? Thoughts on WikiSym 2012

The Ethnographer’s Complete Guide to Big Data: Conclusions (part 3 of 3)


Statistics House, Kampala, Uganda

As promised here is the final installment of my short series about ‘big data.’ I started out by declaring myself a ‘small data’ person. My intention was to be a bit provocative by suggesting that forgoing or limiting data collection might sometimes be a legitimate or even laudable choice. That contrast was perhaps overdrawn. It seemed to suggest that ‘big data’ and ethnographic approaches were at the opposing ends of some continuum. ‘How much’ is not necessarily a very interesting or relevant question for an ethnographer, but who among us hasn’t done some counting and declared some quantity (1000s of pages of notes, hundreds of days in the field, hours of audio or video recordings) that is meant to impress, to indicate thoroughness, depth, effort, and seriousness?

So the game of numbers is one we all probably play from time to time.

Now to answer my few remaining questions:

1) How might big data be part of projects that are primarily ethnographic in approach?

My first exposure to ‘big data’ came from a student who managed to gain access to a truly massive collection of CDR (call detail record) data from a phone network in Rwanda. Josh Blumenstock was able to combine CDR data with results from a survey he designed and carried out with a research team in Rwanda to gain insights into the demographics of phone owners, within country migration patterns, and reciprocity and risk management. I was terribly excited by the possibilities of what could be found in that kind of data since I had been examining mobile phone ownership and gifting in nearby Uganda. I wondered how larger patterns in the data might reflect (or raise questions) about what I was coming to see at the micro-level about phone ownership and sharing, especially its gendered dimensions. Indeed Josh’s work showed a strong gender skew in ownership with far more men than women owning phones and women phone owners more affluent and well-educated. My work explained the marital and other family dynamics that put far fewer phones into the hands of women than men.

However, combining these two approaches is more a standard mixed methods approach than anything new. Is something more innovative than that possible?Read More… The Ethnographer’s Complete Guide to Big Data: Conclusions (part 3 of 3)

The Ethnographer’s Complete Guide to Big Data: Answers (part 2 of 3)


Statistics House, Kampala, Uganda

I’ve come away from the DataEdge conferencewith some answers…and some more questions. While I don’t intend to recap the conference itself, I do want to take advantage of time spent with this diverse group of participants and their varied perspectives to try to offer the bigger picture sense I’m starting to develop of the big data/data analytics trend.

The idea that big data might usher in a new era of automatic research and along with it researcher de-skilling or that it would render the scientific method obsolete did not prove to be a popular sentiment (*phew* sigh of relief). The point that data isn’t self-explanatory, that it needs to be interpreted was reasserted many times during the conference coming from people who occupy very different roles in this data science world. No need to panic, let’s move along to some answers to those questions I raised in part I.

What is big data? Ok, this was not a question I raised going into the conference, but I should have. Perhaps unsurprisingly there wasn’t a clear consensus or a consistent definition that carried through the talks. I found myself at certain points wondering, “are we still talking about ‘big data’ or are we just talking about your standard, garden-variety statistics now?” At any rate, this confusion was productive and led me to identify three things that appear to be new in this discussion of data, statistics, and analysis.

Read More… The Ethnographer’s Complete Guide to Big Data: Answers (part 2 of 3)

The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World (part 1 of 3)


Statistics House, Kampala, Uganda

Part I: Questions

Research is hard to do. Much of it is left to the specialists who carry on in school 4-10 more years after completing a first degree to acquire the proper training. It’s not only hard to do, it’s also hard to read and understand and extrapolate from. Mass media coverage of science and social research is rife with misinterpretations – overgeneralizations, glossing over research limitations, failing to adequately consider the characteristics of subject populations. Does more data or “big data” in any way, shape, or form alter this state of affairs? Is it the case, as Wired magazine (provocatively…arrogantly…and ignorantly) suggests that “the data deluge makes the scientific method obsolete” and “with enough data, the numbers speak for themselves?”

Read More… The Ethnographer’s Complete Guide to Big Data: Small Data People in a Big Data World (part 1 of 3)