Paper Reading #30- Life "modes" in social media

Title: Life "modes" in social media
Reference Information:
Fatih Ozenc and Shelly Farnham, "Life "modes" in social media". CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems. ACM New York, NY, USA. ©2011. ISBN: 978-1-4503-0228-9.
Author Bios:
Fatih Ozenc- I have just completed my Ph.D. studies on interaction design, at Carnegie Mellon's School of Design.
Shelly Farnham- Shelly is a researcher in the FUSE labs at Microsoft. She has worked for Yahoo in the Communications and Communities Department.
Summary:

• Hypothesis: If the authors can effectively manage a user's social media interactions across different "modes" of their lives (family, work, friends, college, sports, etc), then the experiences and services of the social media interactions will be maximized.
• Methods: The authors performed in-depth, two-hour interviews to explore how people naturally mentally model different areas of their lives, how they incorporate communication technologies to support them, and how we might improve their online experiences of managing their social media streams. The authors created a UI that can aggregate all social media information sharing into a single mechanism that can further create information "boundaries" between facets of an individual's life as well as create transitionary models between "modes". The authors then conducted a study on separate individuals scoring highly on extroversion and having multi-faceted lives so that their feedback would be effective toward creating "division" mechanisms.
• Results: Participants either sketched out their lives as "social memes" (resembling network graphs- having nodes and edges representing parts of life such as activities, groups, work, etc instead of individual interactions) or as "timeline memes" (such as a basic rundown on their daily routine or their activities as time has incremented. These resembled collages.).  "Family", "Friends", and "Work" were the three most dominantly present facets of life in the participant sketches. Users were found to have chosen different communication means with each "facet" of their lives based on the intimacy and closeness of the relationships in the different spaces (For example, someone would use their e-mail as a primary contact method for work as opposed to a cell phone for their family). Participants also described their transition "modes" as a sort of "ritual" or physical movement (i.e. "transitioning" from work to home involved a car ride). The participants favored having an organized and focused information sharing mechanism for their multi-faceted lifestyles.
• Content: The authors wanted to create a way to have information boundaries for different "modes" of life for the user. Their results indicate that people with higher levels of faceted identity have the problem of organizing, sharing and consuming online, especially while managing and transitioning between family, work, and social life modes. They strategically use communication technologies to manage intimacy levels within these modes, and levels of permeability across the boundaries between these modes. For future efforts designing social media products, we recommend designers and researchers think about the user’s communication ecology holistically, consider life ‘modes’ as one of the organizing principles, prioritize focused sharing and the mobile medium, and incorporate cues and signals when designing for transitions.

Discussion:
I really enjoyed the ideas and concepts of this paper. I believe most people will actually enjoy using this sort of division mechanism. I myself don't care for it really. I'm not a private, "multi-personality" person at all. I don't mind who sees what about me. Mainly because I want people to know all about me. I enjoy letting people into my life and getting into other people's lives. Like I said, this is definitely a good idea, though. I also like HOW they went about their study. The only good way, in my opinion, that they were ever going to get the design part right is to place it in front of actual sample users that would be (potentially) benefitting from the proposed technology. I believe the authors achieved their goals and didn't simultaneously. They came up with good metrics to use for future designs, but proposed no good ways to go about doing it literally (in code or algorithms, i.e.). This paper was neat.