Visual media is also offline and historical.
I’m interested in sharing, linking, connections, etc on social media. I’m a big fan, and I always insist that those who remove themselves from social media–at the individual or organizational levels are missing out.
Based on recent trends, I’m curious about the visual aspect. I want to focus on the visual aspect of content sharing. This trend toward the visual is also influenced by the shifting habits of technology users. As more people engage with social media via Smartphones.
As a Fast Company article stated last year, “blog posts became Facebook updates and Tumblr posts, which shrunk to Tweets and finally to Instagram or Pinterest and now smart brands are navigating the new visual social-media era.”
Convergence of platforms–instagram being the best example. On my Facebook, I often see interesting collages, from things like Footlocker having a sneaker contest. These visual trace data is a rich arena for companies to advertise, but also yet another way for organizations to engage in commercial surveillance.
OK, pictures? Cool. So what?
What is interesting is not just the images themselves, but the communicative intent behind the sharing of an image. You could have a similar discussion about other media forms, such as in Dana Boyd’s awesome treatement of retweets on twitter.
I mean if I just told you to keep calm and keep reading this blog, would that mean anything? Well if you’re on facebook, of course you know that’s a Meme.
Just go ahead and google “Kanye” and “swift” or “interruption” etc.
Whether it’s political bloggers fascination with cats, or Willy Wonka ridiculing Kony activists, internet memes can evolve and spread extremely rapidly, sometimes reaching world-wide popularity within a few days. Internet memes usually are formed from some social interaction, pop culture reference, or situations people often find themselves in. For researchers, students and organizations, memes are potentially an illustrive type of trace data, as they can be longitudal–changing over time. I would add that they are also generally be event-based.
Another subcategory to study here would be matching up demographics and platforms. I have written before about Pinterest and whether it is a gender driven type of social media. Now that photo is just a joke, don’t take it to seriously. Pinterest would be an interesting platform to study to see what images are being shared (repinned), what type of comments are they getting, and what type of comment.
Fandoms & online subcultures
In looking this up, I was fascinated by Lawrence Lessig, professor of Law at Stanford Law School and founder of the School’s Center for Internet society. In 2008 he wrote a book called remix culture, in which he viewed culture as Read only culture, with which a small professional group produces all the culture that is consumed by the masses, like a read only CD. In remix culture, it is read/write. The public is free to add, change, influence, and interact with their culture so one can combine or edit existing material to produce a new product. Basically, there is a constant revision to what is being created, which is done on both a professional and amateur scale.
This is a very fascinating issue that also gets into music (mash-ups) and YouTube (AMVs). Here’s Lessig explaining it:
Limitations of interpreting social visual data
I see several stumbling blocks as to why at this time, it might still be hard to do large scale empirical studies based primarily on visual data. I say this with a few caveats–I may be wrong on some of my assumptions, please correct me if some of the limitations I list are not limitations any more. Also, I tend to lean to the policy and social aspect of this discussion, I am not a programmer, so there might be ways around these limitations from the IT or computer science fields. Limitations:
- Separating what is digital trace data from what is archival data. For example a gallery album with photos digital trace data? Does it depend on whether it is shared?
- Meaning-the image itself still might need some textual context–with current technology a picture itself has no meaning beyond descriptive characteristics
- New tools. Social network analysis and other robotic or automated data collection methodologies are starting to become widely available for researches–and not just for quantitative research, but for qualitative analysis as well. But that is generally for text-based media. Is there anything comparable for images yet? I know that image recognition technology is available on Picasa for example but not sure there’s a research tool. The US military probably has something, but obviously I wouldn’t know for sure (but I suspect they always have the cool tech 10-15 years before everyone else is even aware of it!).
- Privacy issues, especially if image sharing becomes personal. If you’re doing a research paper, if the source data includes images of real non-public personalities, you have a different set of ethical issues to contend with.
- Lastly, is the ever controversial and senstitive issue of Intellectual Property Rights (remember SOPA and the HUGE explosion it caused?). This is something Lessig is worried about, when he advocates for remix culture. Usually casual sharing of memes or whatever on facebook is not enforced by the powers-that-be, but once you get into mass distribution–commercial or non commercial such as for research or academic purposes, there’s the possibility that you may run into some issues if you are working with visual data.