January 20, 2014 | 17 Comments

Lessons Learned From EPIC’s Mobile Apps & Quantified Self Workshop

Mike Gotta (@Mikegotta) is a Research Vice President for collaboration and social software at Gartner. He has more than 30 years of experience in the IT industry, with 14 of those years spent as an industry analyst advising business and IT strategists on topics related to collaboration, teaming, community-building, and social networking. He has expanded his research to include quantified self trends as well as the business use and organizational value of ethnography. He is currently pursuing a master’s degree in Media Studies at The New School in New York City.

At EPIC 2103, Mike Gotta (@Mikegotta) gave a workshop, Mobile Apps & Sensors: Emerging Opportunities For Ethnographic Research, that examined mobile apps developed for ethnographic research uses. I asked Mike to contribute to the January EPIC theme at Ethnography Matters because his research is always spotlighting some of the most fascinating trends in the tech industry. In this article, Mike provides a wonderful overview of his workshop, but even more interesting is his discussion of all the different ways the dialogue veered away from the original topic of the workshop. Essentially, things didn’t go as Mike had planned. The new direction, however, offered Mike a lot of insights into the future of mobile apps, which led him to reflect on personalized sensors as part of Quantified Self trends and the increasing importance of APIs in future research tools. If you’re a qualitative researcher who wants to know how to make use of the latest mobile apps, this is a must-read article. The second half of Mike’s article can be read on Gartner’s blog.

Mike is currently at Gartner, Inc. (NYSE: IT), which describes itself as the world’s leading information technology research and advisory company. Mike is a familiar face at Ethnography Matters; during his time at Cisco Systems, Mike contributed to Ethnography Matters a piece that has become one of the most often-cited pieces of research on the role of ethnography in Enterprise Social Networks (ESN).

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

You might wonder – what’s a technology industry analyst doing at EPIC and why deliver a workshop on mobile apps and sensors?

The world of the IT industry analyst is becoming much more inter-disciplinary as societal, cultural, economic, media, demographic, and technology trends become more intertwined. These trends, perhaps, were always entangled in some fashion and we are only now becoming more interested in how the patterns of everyday life are mediated by various technologies.

There was a time when industry analysts could cover technology trends and their business relevance as long as they had an IT background. That might still be true in some cases – maybe – but in my opinion, being well-versed in social sciences is becoming a baseline competency for those in my profession.

Which brings me back to EPIC 2013. I had been looking into synergies across design, ethnography, and mobile and was happy to deliver a workshop for EPIC attendees to look at advances in mobile apps that support ethnographic research. As a group, we identified the pro/con’s of mobile apps and discussed how field research could be better supported. The topic was relevant not only to the ethnographic community but also to audiences who interact frequently with industry analysts: digital marketers, innovation teams, design groups, product/service managers, and IT organizations. It struck me that EPIC (as a conference and organization) is in a position to act as a yearly event touch point between those in the social sciences and business/technology strategists interested in the same issues.Read More… Lessons Learned From EPIC’s Mobile Apps & Quantified Self Workshop

December 5, 2012 | 11 Comments

On Digital Ethnography: mapping as a mode of data discovery (2 of 4)

Editor’s Note: Can ethnographers use software programs? Last month’s guest contributor, Wendy Hsu @WendyFHsu, says YES! In Part 1 of On Digital Ethnography, What do computers have to do with ethnography?, Wendy introduced her process of using computer programming software to collect quantitative data in her ethnographic research. She received a lot of great comments and suggestions from readers.

Part 2 of of Wendy’s Digital Ethnography series focuses on the processing and interpreting part. In fascinating detail, Wendy discusses mapping as a mode of discovery. We learn how using a customized spatial “algorithm that balances point density and readability” can reveal patterns that inform the physical spread of musicians’ fans and friends globally. Geo-location data clarified her qualitative data. We are already in great anticipation for Part 3!

Check out past posts from guest bloggers.

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Figure 0: The Hsu-nami’s Myspace friend distribution in Asia

In my last post, I introduced the idea of using webscraping for the purpose of acquiring relevant ethnographic data. In this second post, I will concentrate on the next step of the ethnographic process: data processing and interpreting. Remember The Hsu-nami, the band that I talked in the last post? The image above is a screenshot of their Myspace friend distribution, a map that I created for analyzing the geography of their community. This post is about the value of creating such maps.Read More… On Digital Ethnography: mapping as a mode of data discovery (2 of 4)

October 27, 2012 | 20 Comments

On Digital Ethnography, What do computers have to do with ethnography? (1 of 4)

Editor’s Note: While digital ethnography is an established field within ethnography, we don’t often hear of ethnographers building digital tools to conduct their fieldwork. Wendy Hsu wants to change that. In the first of her three-part guest post series, she shows how ethnographers can use software, and even build their own software, to explore online communities. By drawing on examples from her own research on independent rock musicians, she shares with us how she moved from being an ethnographer of purely physical domains to an ethnographer who built software programs to gather more relevant qualitative data.

Wendy is currently a Mellon Digital Scholarship Postdoctoral Fellow in the Center of Digital Learning + Research at Occidental College. She recently completed a Ph.D. in the Critical and Comparative Studies program in the McIntire Department of Music at the University of Virginia. Her dissertation, an ethnography of Asian American independent rock musicians, deploys the methods of ethnomusicology and digital humanities to explore the complex interrelationships between popular music and geography in transnational contexts. She implemented methods of digital ethnography to map musicians’ social networks. She tweets at @wendyfhsu and blogs at beingwendyhsu.info. She also plays with the vintage Asian garage pop revivalist band Dzian!.

Check out past posts from guest bloggers. Here are some ideas for how you can contribute.

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When Tricia asked me to contribute a series on Ethnography Matters, I thought that I would take this opportunity to bring together the notes on digital ethnography that I have collected over the last couple of years. I would like to push the boundaries of computational usage in ethnographic processes a bit here. I really want to expand the definition of digital ethnography beyond the use of computers, tablets, and smart phones as devices to interact with online communities, or to capture, transfer, and store field media.

In this three-part series, I am going to discuss how working with computational tools could widen the scope of ethnographic work and deepen our practice. I will stay mostly within the domain of data gathering in this first post. In the second post, I will talk about the process of field data interpreting and visualizing; and the last post, I will focus on how the digital may transform ethnographic narrative and argumentation.

In this post, I’d like to foreground computational methodology in thinking about how we as ethnographers may deploy digital tools as we explore communities within and around digital infrastructures. I am particularly interested in how we use these tools to study communities that are digitally organized. How do we use and think about data ethnographically? How does one use computational tools to navigate in digital communities? What are the advantages of leveraging (small) data approaches in doing ethnographic work? While this post is focused on the study of digitally embedded communities, in my later posts, I will speak more broadly about how the digital may extend how we look at communities where face-to-face interactions are central.