The conversation was really stimulating, and wound in and out of perspectives about social interaction design (sxd). At first we were discussing Google Wave’s demise and Google’s inherent lack of social understanding, and then moved onto Facebook missing the mark with Facebook Questions. My take on this is that Facebook already has users asking and answering each other’s questions every day — and effectively at that — but in their status messages. What Questions appears to accomplish with its wide open format is merely to generate data for some presumed search platform later. I’m not convinced the data will be any better than Yahoo! Answers, and, as users, we’re certainly not compelled to answer (or read) questions by people who aren’t in our friend group. It’s the chicken and egg problem if Facebook wants to grow their database to search on later; so a better strategy, in my mind, would be to target questions to the right friend groups. Context matters.

This brought us to a discussion about fundamental differences in the way Twitter and Facebook are designed. Facebook is a network where relations are the social object; while Twitter is a network where information is the social object (although emotion and play are also social objects at times). Yet, with all of Twitter’s openness, it brings with it a sense of presence of who you’re talking to. It doesn’t feel like you’re tweeting into a void, whereas using Facebook Questions does. We also discussed, here, that relationships that form around content sharing (e.g., Twitter) develop into the sort of network where this openness can be supported. But privacy still reigns in the Facebook networks where the only glue is, in many cases, a former relationship.

Of course, this led to asking whether there are rules for designing effective social interactions. The short of it is no. Twitter created a versatile platform by using only simple rules for engagement. But these rules cannot be carbon copied, replicated elsewhere, and expected to work in another system in quite the same way. Things like context, culture, and personalities (among other sxd considerations) change the way a given feature will be used and adopted by the community.

Instead of developing rules or principles of social interaction, a better approach is to think of the questions we can ask when designing for social. Who are our users? How do they think of themselves? Who do they want to connect to? Who do they want to connect to tomorrow? Why? What’s the point of the network in the first place? Where are they when they’re using the network? What is the outcome of an interaction? What’s the role of strong versus weak ties in the network?

We didn’t have any glorious resolution to our discussion but instead emphasized how we need to keep trying to understand how social interactions play out — which includes doing research into social and developing case studies which illustrate principles that we can take to our clients and product teams.

A few references related to social interaction design include:

• Adrian Chan’s original introduction to Social Interaction Design. And related presentations.
• Paul Adam’s research into Real Life Social Networks.
• A great list of references by Paul for thinking about sxd.
• David Casali’s Social Usability checklist.
• A case study by us fine folks at Bolt | Peters about iPad usability and how social and context play a part.
• Our group blog on social interaction design.
• My article on using remote research to inform social interaction design. And a related talk.

But for now, you can read the article in UX Magazine. Or the brief write-up by ZDNet. Or watch the video we created:

And here’s a look at mobile payment transactions (using Square) on the iPhone versus the iPad:

How do you research how the unemployed find jobs? Surely they use their social networks. How do you research how to financial investors get advice from their community? How do you research consumer coffee drinking culture? How do you research how people shop for clothes? Shopping is one of the most social activities, even if it’s done alone. In fact the most social shoppers are elderly women: they shop with their deceased husbands in mind (“What would he have liked?”) and with their children in mind (“If I buy the cheaper shirt, I’ll have more to pass on to my daughter.”) But shopping for a dress might take several days to weeks before the purchase is actually made. What goes on in that time?

Okay, those are what I was referring to as “social design problems”. But what I care about is how we design for those things? I know very little about financial planners make decisions. I know my coffee drinking habits — but do I know yours? What about your shopping habits? Research is necessary to uncover all the nuances in our social behaviors, and is especially important to do right when working on such social design problems.

But how? Our user research methods have been fine tuned over the past decade so that we know exactly how to recruit the right sample, how to ask the right questions, and how many users to talk to to unveil most usability issues in an interface. I just don’t believe that we have the right methods yet for social interaction design issues.

How do we study a community that spans the online and offline world? How do we capture emotions, feelings, expectations, and privacy issues without biased research prompts. How do we understand social context?

I am not convinced that 5 users is enough for social interaction design issues — or for studying social interfaces. There are too many variations in people’s social behavior to capture everything in small samples. There are too many social contexts in which even the same user would respond differently. How many users is necessary? What is the best way to complement data metrics (quants) with qualitative user behavior?

I have been talking to several people about this recently and would love to hear from you. What social research methods do you use? How do you use them and what benefits do they provide? If you’re willing to share your methods, I am interested in collaborating with you to create a set of best practices here!

They were building upon (among other things) my work on asking and answering behavior on social networks (“Do your friends make you smarter“) and wanted to know more details about things like: why do people post questions, answer questions, and what motivates people to go the social search route over traditional search.

I want to talk about their conclusion here first: where they discuss the tradeoffs between using social networks and search engines. This was the most interesting part of the paper and is the part that has the most practical take-aways for the UX community.

Basically, for questions requiring trustful and personalized responses like for recommendations or opinions, social networks were strongly preferred over search engines. People occasionally perceived a delay in response time (but sometimes did not!) — and either way, this delay was not a downer since it saved people the effort of making multiple attempts on a search engine before getting the right answer back (if they ever did). Also, subjective questions got faster responses on social networks than objective questions!

Additionally, they talk about how being on social networks is fun for people. It’s too bad that they under-emphasize this point because it’s really important from a social interaction design perspective! People engage on social networks because it’s fun! There’s an emotional tie to the community that keeps bringing them back. When it comes time to ask a question, people turn to their friends for help because it keeps them connected with others, helps them to share information about themselves, and keeps them engaged in their community. Fun is an important element of design — and until Google, Facebook, Yahoo, Microsoft, or other search providers make the information seeking part fun, they will lose. It’s not enough to simply pipe in real-time Twitter results and expect that to be fun or more personalized!

That (above) is the juiciest part of the paper, but I do summarize the whole paper below for other nuggets of inspiration.

To start, the authors note that Q-A on social networks is unique (like unique from Q&A sites like Yahoo Answers) because:

• questions are posted with true identities (rarely anonymously)
• people’s audience is smaller (being only people’s direct contacts, or possibly friends-of-friends)
• status messages are short: so questions are succinct

Then they collected surveys from 624 Microsoft employees (1/4 were female) about their Q-A behavior on Facebook and Twitter mostly. The survey asked about:

Asking questions:

• whether they ever used their status messages to ask questions
• if yes, to share a recent example of a question they asked
• what kind of responses they received
• how often they logged onto social networking sites

And answering questions:

• whether they responded to someone else’s question (from a status update)
• if yes, to share a recent example of a question they answered

50% of people who replied to the survey did indeed use their status messages to ask questions! Sometimes they were silly questions (“Why are men so stupid?”) and sometimes they were serious (“Point and shoot camera just died — need to replace it asap. What should I buy? Think under $200″).

On asking questions

Questions took many shapes and forms. Some were targeted to “Anyone” in the social network; others were general statements put out to the network to interpret. Most questions were asking about recommendations (29%) or opinions (22%). Some were about facts (17%) and some were rhetorical (14%).

Questions also related to everything from technology (29%) to entertainment (17%), places (8%), current events (5%), and ethics and philosophy (2%). People said they’d generally avoid asking their network about topics like health, pornography, religion, and financial issues because those are too personal.

Another finding was that Twitter users were more likely to ask questions about technology, while Facebook users more likely to ask about home and family issues. This isn’t too surprising, but does show that the makeup of people’s networks affects what kinds of questions people will ask.

One looming question in this research is: why do people choose to ask their friends over searching on Google? In this study, people reported having more trust in their friends’ responses or that they thought traditional search wouldn’t work for them with this particular question. Sometimes it was obvious that their friends would know their history, family situation, and other preferences better than a search engine.

People also generally knew the makeup of their networks (meaning they could get targeted responses) and people wanted to advertise their current interests by way of asking questions of their friends.

What about answer speed or answer quality? There were mixed results, but often questions asked on social networks were not urgent so any delay was considered acceptable. It was also easier than sorting through tons of results on search engines and quite often more fun to engage with friends.

On answering questions

Almost everyone has answered a question on one occasion or another. And of the questions offered up in this survey — nearly every one received an answer! That’s kind of amazing considering Q-A sites in general have a much lower response rate, but it’s also likely due to the intimate make up of people’s social networks. Not to be an under-appreciated finding in this paper, however!

About one-quarter of questions got an answer in 30 minutes or less, and 90% were answered within one day. (I’d LOVE to see how Aardvark’s data compares here. I have several questions out to Aardvark that have never been answered; but of the ones that do get answered, it’s typically faster than 30 minutes.)

Yet people don’t seemed to be bothered by the 1-day response lag. Perhaps this is because replies from trustworthy friends are more valuable than junk search engine or Yahoo Answers responses?

Why did people respond to questions by others? Most often they were just trying to be helpful (37%) or had expertise in the area (32%). Those seem like good reasons to me, and ones that are often overlooked when thinking about how valuable personal social networks can be to people. At other times, people replied because they had a good relationship with the asker, were connected socially, or had some notion of social currency (that answering now may result in a favor later).

When people didn’t respond to questions by others, it was mostly because they didn’t know the answer! That’s pretty neat. But some said they’d prefer a personal request and ignored questions that were asked to the network as a whole. In fact, my research on Q-A in social networks revealed the very same thing — that people gave great responses when asked privately or one-on-one, even when they weren’t very knowledgeable about the topic.

Another interesting, but not very surprising finding, is that people who were more frequent social networks users received quicker responses! Why duh! People who are engaged with their communities have developed rapports and back-and-forths and social capital with folks — what goes around comes around. But it is cool to see this intuition confirmed in real data!

Unfortunately, this paper is weak on design recommendations. My colleagues and I have already suggested the very same ideas (e.g., surface your friends status messages on the results page — what I call “friend-filtered search” — or have a search engine post a question as a status message on your behalf.) Even as I say this, there are serious social interaction design issues with this approach. Expectations about search engine behavior, expectations about social network intrusion, privacy (obviously), interactions with online agents, etc. all come into play. I very much hope that these issues are being considered by the big search engine companies, but somehow I’m afraid they’re not.

Detailed information and registration can be found here: http://socialsear.ch

Why Enterprise Social Search?

Knowledge management and information retrieval in large organizations is a huge problem. A number of orgs are making efforts to address these issues; and leveraging social data — or information that people within the company hold — is one promising route.

Why a design workshop?

Although the premise of our workshop is social search in the enterprise, we won’t be satisfied by just writing or thinking about it. We want to bring together the sharpest minds in the enterprise world and mix them with designers, researchers, and IT professionals to come up with some practical solutions that actually could be implemented.

What next?

After our workshop in San Francisco, we’ll take our findings and carry them onto future workshops in Australia and Washington DC — to build upon our ideas and find ways to develop them even further.

Where can I learn more?

You can read more about who we are and what the workshop will entail over at http://socialsear.ch.

Also don’t miss…

…this presentation that we gave at the Enterprise Search Summit last Fall. This presentation gives a flavor of that topics that will be covered in our Enterprise Social Search Design Workshop in San Francisco.

We hope to see you at the workshop!

Our topic dealt with privacy issues in 2019 when we may, theoretically, have some device hanging behind our ears — or someplace discrete — that reads our thoughts and interfaces with things in the world. Other people could become aware of our thoughts and feelings (although the specific mechanisms of how this would work were left up to the imagination).

Instead, we wanted teams to think up a context and situation where privacy issues would occur and how people in that situation would deal with it. Here is what each of our three groups came up with:

Team #1: “The Street Tigers” — related to privacy while crossing a street:

Bodystorming privacy Group #1 from Brynn Evans on Vimeo.

Team #2: “The Retail Tigers” — related to privacy while shopping online:

Bodystorming privacy Group #2 from Brynn Evans on Vimeo.

Team #2: “The Sick Tiger Puppies” — related to privacy issues in a doctor’s office:

Bodystorming privacy Group #3 from Brynn Evans on Vimeo.

What is social interaction design?

Social interaction design (SxD) is the practice of designing for person-to-person interactions mediated by a computer interface, going beyond pure usability and human-computer interaction. Even fairly solitary experiences like editing a Wikipedia page occur in a social context in which other users’ past interactions influence what new editors contribute.

“It’s the the interactions among users that informs design” (Adrian Chan).

What’s a good example of an SxD problem?

Vark.com is a question-answering service that routes users’ questions to people in their extended networks who may have relevant knowledge of the topic. The original service operates through IM, Twitter, and email; more recently an iPhone app has been developed.

Let’s consider the difference between the mobile and desktop experiences of Vark.com. Both asking and answering activities work rather well in desktop email and IM. In contrast, responding on-the-go is awkward—more often than not, we’re distracted, hurried, or unable to type a coherent answer without bumping into a fire hydrant.

There’s also an assumption that the answer resides solely in our heads, when in reality, providing an answer often requires sharing links or performing a quick search—that is, we may not have the answer immediately on hand, but we know where to look.

Furthermore, successful answers often manifest as conversations on the desktop (example above), in which messages are exchanged in a back and forth manner so that the questioner can clarify her question and the answerer can refine her response. This type of sustained interaction is much harder to establish with on-the-go users.

Finally, iPhone prompts (below) often lack enough information about the nature of the question or your relationship to the questioner. One reason for Vark’s success is that it seeks out answers from people within an extended, personal network, naturally building trust and accountability into the system. But without knowing how you know the questioner, the iPhone app experience feels instead intrusive and disruptive, and lacks any strong social motivator to respond.

Why is remote research useful for SxD?

Traditionally, user-centered designers conducted field studies or shadowed someone to learn more about their practices. The digital space complicates matters—not only is it difficult to shadow someone, but people’s actions are so fluid and varied that it’s hard to isolate specific behaviors in order to study them.

Remote research has emerged as a great way to do needs-finding for SxD, for three reasons:

First, it’s hard to recreate interactions between two or more people in a lab setting. Last year when I was studying user interactions during social search tasks, I realized that I needed to talk to multiple people: both the user who posed the question as well as the people who provided replies. I started by observing the questioning process: how the question was phrased, which communities or individuals were questioned, the historical relationships between the parties. Then I explored the answering process: answerers’ perception of the request, why they chose to reply, if they had a history of interacting like this.

What’s interesting is that answers provided over social networking sites (like Twitter and Facebook) were mostly jokes or “nudges” to attract the user’s attention (“Hey, remember me?”). But answerers in private channels (email, IM, phone) were more serious and thoughtful because people were contacted directly and had longstanding relationships with the user (“She asked me personally, and she’s helped me in the past”).

Second, social interactions unfold over time, and their repercussions aren’t always apparent in a hour-long lab study. I recall one user in my social search study who asked a question on ping.fm. He received a prompt reply which “seemed right”, so he reported it as his “final answer”. I followed up two days later to see if he had received any other replies. In fact, the conversation thread on ping.fm had progressed, and the community had collectively concluded that the earlier reply was incorrect. This observation was only made possible by the passage of time.

Third, social interactions are best understood within the context where they occured. Not just physical location, but also past history (between the people interacting) and reasons for having the interaction. For example, my sister tweets about her new startup, but I’m not familiar with her a field and don’t have a professional relationship with her, so I seldom reply to her tweets. However, when she emails, calls, or writes on my Facebook wall, I reply instantly—even on an unfamiliar topic. If you were only studying my Twitter use, you might wrongly conclude that I’m an ingrateful sister, but this interpretation would be taken out of the full context of my relationship with her.

Thus, whether you’re designing for healthcare, fitness, games, dating, or online privacy, it’s critical to gain insight into where, when, and why people to act the way they do. Community engagement through social media will differ substantially depending on people’s personalities, reputation, location, local culture and rules, nature of their relationships, and history of the community. Remote research methods—like experience sampling, remote observations, and critical incident surveys—are great tools for understanding the many facets of social behavior, and suggest productive avenues for pursuing SxD.

Additional resources:
Social interaction design salon (group blog)
Digital ethnography for social interaction design (slide show)

[Guest author: Brynn Evans is a digital anthropologist, design researcher, and author who studies social interaction design and social search. She extends a thousand thanks and a bear hug to Tony Tulathimutte for help in editing this post!]

I really hope other Overlappers will share the output of their vision boarding sessions! For me, mine became a reminder of what social interaction design is — what factors influence social dynamics in a community, and what kinds of questions you have to ask when studying or designing for a community. What appears to be a crack or crevice in the middle of the conversation (in the middle of the board) is supposed to represent this design opportunity. But there is no “one size fits all.” The quote beneath reminds us of that: “I don’t really know what ‘community’ means.” Is that like Facebook? Question mark?

That’s exactly the point. What works in Community A might not work in Community B. (As an example: Until recently, you haven’t been able to reply to Facebook messages via email, although this didn’t stop people from logging into Facebook.com and continuing their experience there. This fluid cross-platform interaction hasn’t worked for LinkedIn, however. Receiving a email notification from a LinkedIn group feels more like RSS than social interaction, and when I receive a message, I haven’t been motivated to log onto the site and reply or interact with people.)

And so, as social interaction designers, we have to carefully consider the social dynamics we want to enable and how to go about doing that. Consider this:

First, do you think search engines making use of social networks will improve search results and thus make our daily life a bit easier?

Yes! A lot of fact finding and information discovery already comes from friends, colleagues, and even acquaintances. Online social networks organize our personal relationships in a way that reduces the barriers to information exchange. At the moment, social networking sites aren’t set up for search per se—Facebook and Twitter want to get into search, but with Facebook, they can only reveal what your friends have OK’d to be public, and with Twitter, there’s enough noise, spam, and unknown people making claims that the results can be hard to trust. But, there’s already evidence that people are turning to these online social networking sites to ask their friends questions. On Twitter, these have been dubbed “lazy tweets”:

“Wondering where Bowtie saves it’s themes… Anyone? #LazyTweet” –@iphone360

“Looking for social media trends in the healthcare industry. Anyone out there have resources they can share? #lazytweet #healthcare” –@chrismevans

“Anyone know if there are Brocade SAN and Cisco MDS simulators? #lazytweet #healthcare” –@sloane

The real value for social search is making the search experience more personalized. If search engines can make use of existing ties, relationships, and data coming from social networks, they can use that data to bubble up results that come from a trusted friend network that may be as relevant (if not more relevant due to the trust factor) as traditional search results. The risk, however, is that our personal networks are narrow and not every search we perform may have counterpart results from social networks. This is why search algorithms will continue to play a large role in search, regardless of how “social” it gets.

Another benefit of using social network information in conjunction with search is that a services can begin to “learn” which of your friends have expertise or knowledge about certain topics. Then when you search for those topics, people from your network who may have relevant knowledge could be made available to you. It’s still unknown how visible searchers want other people to be in the search interface. People may only appear as a search result listing, linking to their profile or email address; or they could appear as a direct contact, like through an instant messaging window on the same page as the search results. Either way, the point is that direct person-to-person conversations can greatly supplement an information discovery process (as we pointed out in the “Do your friends make you smarter?” paper).

Another interesting area for social networking support during search is for searches that present difficulties. Anytime you can’t find what you’re looking for on the first try, or you rework your query over and over again — these are use cases that could benefit from asking a friend a question, pinging your social network, or finding a colleague/acquaintance who may have experience with this particular problem.

And second, do you expect these social search engines to become available in any near future?

Yes and no. Yes, in that there are a number of services that provide human answering — but these mostly do not include a search algorithm component, meaning that results are only driven by a direct human contribution. Such services include Aardvark, Cha Cha, Hunch, Quora, and Mahalo…

Another popular class of social search services only makes use of aggregated social data from large networks. I call this “collective social search” since it’s like the wisdom of crowds effect, in that you can see trends from the collective that might be useful in guiding your search. Google Search Suggest is an example of this — it shows you the common search phrases for a given few words. Twitter’s Trending Topics and OneRiot are similar. I think the popularity of this approach is that it’s algorithmic, so you can throw more programmers at it and hopefully improve the results. But it’s quite limiting in its utility since searchers will trust people they know or people who can be vouched for, whereas trends across an entire network have no intrinsic relationship to the searcher. Such results may help in the early stages of search when you’re still trying to formulate an ill-formed query, but won’t be as useful when you want to narrow down to a specific answer to your question.

Thus, the kind of “social” component I want to see in search will require combining both of the approaches I mentioned above. This is not trivial, and there are a lot of unknowns about how people will respond to a service that does this. How will people react if their search results are shared with their social network? Will it be different if we see how valuable it is when our networks’ search results are shared with us (the reverse case)? How will reputation and obligation come into play? How will reactions differ by personalities? By location? By past history? By the political climate?

If Facebook’s Beacon experiment taught us anything, it’s that “social” can’t be solved by an algorithm. We’re still a ways off from really solving social search.

I consider this to be a work-in-progress of methods for studying cultural and social behaviors in online, mediated spaces. Please share the methods that you have used or found to be useful so that we can continue the conversation around best practices.