Adrian Chan Archive

To extend my thoughts on people vs. content further, let’s consider the opportunities for those in marketing, PR, and advertising who hope yet to realize value by engaging social media. In spite of their differences, one thing these industries have in common is a taste for volume. Their taste for success is a taste for more, and their appetites sated best by high calorie helpings of servings that perform.

That said, we all know that high volume advertising across social media are just *this* far off the bottom of the feed trough. Just ask Scott Rafer of Lookery (here’s Allen Stern’s interview with him, dated but relevant). CPMs are notoriously low on social media because users are disinclined to pay attention to ads whilst they’re busy with friends. But sites like MySpace and Facebook serve up a huge number of pages, and are the equivalent of the outdoor advertising marketplace online.

Richer, more embedded, better targeted (by means of micro-targeting to the user, social graph targeting to the group, or social context targeting to audiences of followers) marketing is a better indicator of the future of online marketing. But as anyone in this space knows, ROI is not yet measurable, as is performance. In order for one-to-one or relationship marketing to make their comeback in the guise of social media marketing, industry and application standards will need to show success. And those successes will need to be evangelized by the social media community as case studies and best practices. The phase of application and service innovation is maturing, and is ready for adoption by those who can see a path to engagement.

And now back to my point on people vs content. It strikes me that there’s a fork in the path to adoption, one that possibly reflects a choice between people or content.

On the People side are those of us heralding the cause of influencers and influencer metrics, supported by social media practices like following and friending. Industry speak on the social graph, on conversation, on feeds, lifestreaming, flow apps, and so on all suggest that marketers should get in with the people doing the talking, by means of course of the talk tools we all use (twitter, friendfeed, etc).

And on the Content side are those of us who champion the visibility and relevance of social media news, supported by social media practices like content rating, digging, aggregation, blogging, posting and commenting. Industry speak on the value add of socializing the web, of user generated content, of conversation around published and wired stories, videos, images, and more all suggest that marketers get in front of the context in which social media content is produced and consumed.

These are possibly just two sides of the same coin. Marketers can approach influencers and through them obtain exposure to more relevant audiences, and by means of more valued and trusted sources. Or marketers can buy exposure in the sites, on the pages, and possibly in the feeds that get the most traction, thereby and presumably reaching those most influential and attentive.

I’ve seen more discussion around influencers and the need for a measure of social impact than I have around their content. This could be that content is covered by web analytics and page rank, search, etc already. Or it could be that social content still awaits robust and reliable sentiment and semantic tools (yes, there are some but social talk is notoriously lacking in the context and meta data that content analysis needs for accuracy).

So I don’t know if the distinction I’m making is material in the end. Current marketing and advertising practices continue to emphasize exposure: messages are placed alongside audiences and their activity. But merely being contiguous to the social isn’t good enough. One wants to be in and of the social. So perhaps the industry still needs its paradigm shift. From being in front of the audience to being in the audience, and from being associated with the consumer to talking with the consumer, attentive both to who she is and what she says.

Adrian Chan is a social media experience expert and analyst. You can follow him on twitter at gravity7.

I don’t know if this bespeaks a major trend, but I’ve noticed that of the slew of news and friend aggregators, services seem built on a choice between aggregation of content around people (as sources) or aggregation of people around content (as sources).

The distinction between contributors and contributions is at the core of social media in general. Design limitations, including allocation of screen real estate, navigation schemes, actions and features/functions, and the resulting social content and practices these limitations produce, would seem to suggest that any aggregation tool will stake a preference on either the person or his/her content.

I don’t know if this suggests that there’s a corresponding division among user preferences and interests: to prefer people over content, or content over people. As users, do we fall into two camps? Are there two types of social media users — those drawn to the social face and those drawn to the media face? Those who relate to people first, and those who relate to content first? Those who pay attention to the person, and whose trust and interest aligns with personality, relationship, authority, etc? Versus those whose interests connect with content, statements, news, and talk — over and above the people posting and doing the talking?

But between friendfeed, digg, stumbleupon, socialmedian, twitter, facebook, and scores of others now in the business of assembling audiences around social content, it does seem that some are more conversational (twitter and feed aggregators like FF) and some more topical (digg, socialmedian, the new strands).

Perhaps, indeed, some of us are more attentive (in general) to who’s talking, and some to what’s being said.

Adrian Chan is a social media experience expert and analyst. You can follow him on twitter at gravity7.

These screenshots are taken from Radian6, social media monitoring application that I’ve been using for the past couple of days.

This screen shows topical clouds taken from twitter accounts of several social media influencers. Shown here are Tara Hunt (missrogue), Chris Brogan, Adrian Chan (gravity7 — the parser apparently doesn’t like alphanumerical names), Dave Winer, Stowe Boyd, Michael Arrington, Chris Heuer, Jeremiah Owyang, and Brian Solis.

(note I worked myself in there? crafty eh? I’m not really an influencer, of course, so I put myself in there as a proxy control group.)

You’ll need to hit each of these and pop them to full size to be able to read them. If you do, you’ll probably wonder as I did what, if anything, this tells us. These are cloud views, and could be provided by tweetclouds, but I found it handy to be able to lay them side by side, and to be able to flip each window over and change parameters (eg. date range). And they’re updated in real time, so they refresh every few minutes or so.

The value proposition here is that influencers influence while talking, and for those of us on twitter, this means talking in 140 character posts. I had to stare at these for half an hour before I began to see things. (my screensaver kicks in at 30 mins. just kidding). You can click the words to read the posts that included them. I started counting how many were in each (this has to be done manually, so it would be great to see a post number on rollover.)

First of all, the tags include any post from the user as well as posts to or in which the user is @named — so while Dave Winer showed 124 posts for comcast, not all were from him. Likewise, I noticed that Arrington was the only one "reading" — but it turned out that the term was used in posts in which other twitter users said they were reading techchrunch (not in fact that they were reading arrington’s tweets, but techcrunch articles).

With the influencer value proposition still in mind, I tried to read between the lines, or through the gaps, and what struck me first was that in the combination of words shown for each twitterer, one could make out three kinds of conversation: every self-referential talk (apropo the invitation that still begs participation on twitter.com: "What are you doing?"); exchanges with other twitterers; and references to companies, activities, sites (urls).

From stylistic differences in terms that convey everyday experience, you can make out some of the personality of each twitterer. This is even more clear in the 1 and 3 day views than in the 30 day views (yes, that’s thirty days — more than other twitter search clients). These influencers vary in their personability, enthusiasm, self-disclosure, and vary also in how personal or impersonal they come across. Tara comes across as friendly, Jeremiah as professional, arrington as a journalist, brogan as interested. While I follow these folks daily, I purposely did not read their twitter archives — so that I’d be reading as much from terms shown as possible.

As you close down the time frame, terms that are surfaced shift to the present. No surprise there. Interestingly, heuer maintains a more regular repertoire (see how his terms are fewer and larger). Most influencer show a fairly flat conversation space — that is, few words really stand out during the 3 day snapshot view. Solis gets credit for "thanks", which stands out and makes sense given what he does — PR. Solis gives and gets a lot of gratitude. Tara uses the most expressive and emotive terms, suggesting that she tweets more about how she is feeling. Winer clearly had something up with comcast (the heavy throughput problem), and heuer, solis, jeremiah and myself reference "social media" quite a bit — if one were pushing social media, we’d be good targets as we speak it already.

Down at the one day level, it’s easy to see who addresses other twitterers, and is in (public) conversation with them, and who doesn’t. One also gets a sense of the day’s topics. Solis’ topics change significantly between the one and 3 day view. Heuer’s remain for the most part the same — however, he might not have twittered much during the one day time period, and I didn’t check.

In moving now from everyday conversation to topical conversation, we can look again for influence. Influencer, influencer on the wall, who’s the most influential of them all? These cloud views don’t account for reputation score, or use a conversational index (such as suggested by stowe). They account for numbers of follows/followers, and because there’s no metric for page view in twitter, don’t account for impact.

So the terms, while shown in the same font size, can’t give us comparative topical influence. They more simply show us what these influencers tend to talk about. Because tinyurls are captured only as words, and not parsed, we’re not able to see what these users have posted links to. But we can see who does post links. Few of the social media company names, applications (facebook and twitter excepted), or buzzwords appear here. That’s not surprising, given that these users maintain their own blogs, belong to a high number of social networks, and are regular face to face contact. Much of what surfaces in the social media space, therefore, might not make it into these conversation clouds verbatim.

(What does surface is often in the tinyurl). However, these are just my interpretations. (For example, stowe, deborahcrooks, and I just had a guitar/singing jam session at my place, but the words "jam" "guitar" "session" etc passed below the radar, or were the subject of direct messages. This begs the question of private and public conversations, and a lot of value is passed through back channels.)

Note that a view of influencers in popular TV, movies, dvd rentals, bands, cars, celebrities, etc, might show very different results. Influencers who don’t make regular face to face contact should produce more explicit topical references in their twitter conversations. In fact a quick survey of Lost fans and Lost tweets showed a great deal of detail right after last week’s (awesome) episode. Lost fans can use a shorthand, insider references to theories, and so on. Highly coded 140 character conversations take an insider’s knowledge to understand. While radian6 did surface "OMG," I’m guessing that some social media analysts might have missed "OMG" as a term of extreme enthusiasm and brand affinity (! — not to mention WTF!!!).

I skipped over my second observation — references to other twitterers — because it’s fairly straightforward. It would be cool if these were denoted in the tag clouds by use of color. Speaking of color, it would be cool also if rolling over one word would highlight the same word in other profiles. Widgets don’t talk to each other, however.

There’s one powerful dimension of this that I’ve not yet brought up, and that’s the real-time updates radian6 provides to each window. I could see using this for clients. In fact by keeping lists of topical or domain influencers, together with their blogs, one could provide a client with intra-day monitoring. Each widget can be exported as a graphic or as xml, and emailed from within the application, with notes. This would be perfect for real-time tracking — say of events, breaking news, product launches, pr, marketing or advertising campaigns.

It would be great to see this with cross references and relationships (a social graph) built in. One might then get a better sense of the overall conversation space. This approach looked at individual influencers — a topic approach requires setting up widgets by keywords, and results vary immensely by the correlation of search terms to tweets. I’m sure I’ve missed quite a lot, but this post is already far too long.

Thanks for your attention!

Just some arbitrarily chosen terms, with number of tweets returned for each (written to, by, or citing that user):

user: techcrunch

yes 10
reading 12

user: chrisbrogan

thanks 22
talking 9

user: missrogue

book 9
awesome 10
whuffie 5

user: davewiner

comcast 124 times
thanks 8

user: jowyang

thanks 6
agree 6

user: briansolis

thanks 6

user: stoweboyd

dinner 5
wine 3
tuning 3
interesting 3

I’ve been having a fascinating time reading through papers on NextStage Evolution, a company in the business of metrics and online media analysis. And I’m compelled to write briefly on some core methodological principles, primarily because the methodology behind social analytics warrants careful consideration. All of us in this space want to know what the user wants, does, and might likely do. That would be valuable information, and having it would allow us to anticipate and deliver, and engage, with users. Unfortunately, user’s don’t declare their motives or intentions, and so it is up to analysis to model user interests from user behavior.

I sincerely believe that social media analysis needs to account not only for the user’s proximate activities, those being his or her online behavior and actions as trackable by analytical tools (be they within a walled garden social network, on and around blogs, in conversation tools like twitter, or even through social applications and widgets), but also deeper and less available interests. These are the interests that underlie interpersonal interactions, communication, and relationships. And no matter how near or far interactions, communication, or relationships may appear through social media applications, they form the basis of user agency.

Agency is a sociological concept, and it underlies user actions and activities. Agency, to me, involves intentionality and motive, as well as content (information), and is interested (identifies or attaches to an object or subject). User experience is about agency. Interaction design is about agency. And inaction can be about agency, too. Fundamental to the concept of agency is that of self-reflexivity — that we know what we are doing.

In social situations, activity and interaction are framed. That is, they unfold within a frame, which is to say that they make sense within context, and over a stretch of time. And in social interaction, the frame is often mutually constructed — two or more people know what they are doing and if asked, would describe the situation they are in with a high level of agreement. Their recognition of the frame would agree even if they are in disagreement with one another.

This contextuality of action, I think, applies to mediated interactions as it does to face to face encounters. The difference is real, but is understood. Some interesting misinterpretations of intent, motive, interest, and so on of course occur online, and indeed can enrich the experience with a touch of play, self-reference, and so on. But as is the case of the comedian who tells a joke about a pope in an airplane telling a story about an ace fighter pilot…. frames can be layered and embedded within one another, and we come out the other end for the most part still making sense.

I bring all of this up because it informs how we read and interpret, and thus also design, anticipate, and model, social media user experiences and social practices. Users provide more than just information and at the same time are less than informing. Our models need to interpret, for example, whether a user has recommended a movie to somebody, in front of a community, to be shared among friends, because she enjoys writing reviews, has a reputable movie blog, is considered (or believes herself to be considered) a movie expert, or believes in the principle of contributing reviews to the common good.

Would we get this from the review itself? Not likely. From envelope information (to whom it’s addressed, how messaged, where posted, how delivered)? From comments and their agreement/disagreement? From past movies reviewed? From movie categories covered (e.g. new releases vs film noir). I belabor the point — it’s complex (though do-able). In all cases, however, agency is neither explicit nor stated. ("I hereby submit this movie review to this esteemed blog for the sake of my reputation as a budding film noir critic and blogging habitue".)…

Designing social media to engage users is much simpler than accurately interpreting their actions, for design succeeds as long as users are compelled by their own experience. Users will remain engaged even if the experience is riddled with theft, robbery, and deception. To wit, Vegas. Social interaction designers don’t need to know what compels a user, as long as they understand that there is a range of users, and that their system facilitates communication and interaction, as well as an experience of presence which varies user by user, and which leads to social practices in the aggregate. Users work with what is given, on the screen and architecturally, as well as with those others who are present, and participating. Online interactions don’t have to be efficient, or even effective, to be rewarding.

But like the anthropologist studying a culture from the outside, or an archaelogist interpreting the meanings of cultural artifacts and found objects, analytical software, as a non-participant, is confronted with a more profound challenge: reverse engineering the artifacts, button presses, posts, comments, ratings, bookmarks and so on left behind by users whose mindfulness or mindlessness would be impossible to measure, and at times difficult to distinguish.

Information about what users do is not available in the information about what users have done.

This is where I tack differently from models based more squarely in data analysis and user activity tacking and measurement. Those methods, and I’m not a qualified statistician, may observe the disaggregated and yet predict in the aggregate, and successfully so, if we are to place any faith whatsoever in the long tail. Metrics may serve purposes of campaign analysis and even management. But engagement (social media marketing) tools would require a communicable messaging and engagement platform. The difference? Agency. Communicable engagement seeks not the acceptance of the user but his or her participation — it anticipates the significance of agency.

I so strongly believe that social analytics ought to be rooted in an intersubjective framework of action, and not one of information gathering alone, that I’ll close with a few quotes from Erving Goffman, master observer of social interactions and mentor in spirit:

"Given a speaker’s need to know whether his message has been received, and if so, whether or not it has been passably understood, and given a recipient’s need to show that he has received the message and correctly—given these very fundamental requirements of talk as a communication system—we have the essential rationale for the very existence of adjacency pairs, that is, for the organization of talk into two-part exchanges. We have an understanding of why any next utterance after a question is examined for how it might be an answer." Erving Goffman, Forms of Talk, P. 12

"Note that insofar as participants in an encounter morally commit themselves to keeping conversational channels open and in good working order, whatever binds by virtue of system constraints will bind also by virtue of ritual ones. The satisfaction of ritual constraints safeguards not only feelings but communication, too." Erving Goffman, Forms of Talk, p. 18

"And just as system constraints will always condition how talk is managed, so, too, will ritual ones. Observe that unlike grammatical constraints, system and ritual ones open up the possibility of corrective action as part of these very constraints. Grammars do not have rules for managing what happens when rules are broken." Erving Goffman, Forms of Talk, 21

"Uttered words have utterers; utterances, however, have subjects (implied or explicit), and although these may designate the utterer, there is nothing in the syntax of utterances to require this coincidence." Erving Goffman, Forms of Talk 3

"The rules of conduct which bind the actor and the recipient together are the bindings of society. But many of the acts which are guided by these rules occur infrequently or take a long time for their consummation. Opportunities to affirm the moral order and the society could therefore be rare. It is here that ceremonial rules play their social function, for many of the acts which are guided by these rules last but a brief moment, involve no substantive outlay, and can be performed in every social interaction. Whatever the activity and however profanely instrumental, it can afford many opportunities for minor ceremonies as long as other persons are present. Through these observances, guided by ceremonial obligations and expectations, a constant flow of indulgences is spread through society, with others who are present constantly reminding the individual that he must keep himself together as a well demeaned person and affirm the sacred quality of these others. The gestures which we sometimes call empty are perhaps in fact the fullest things of all." Erving Goffman, Interaction Ritual, 91

To put this simply, if it were Prime Suspect (or my favorite, Cracker), vs CSI — I’d pick Prime Suspect.

This post was authored by Adrian Chan who runs a social interaction design firm in San Francisco, California.

I happened on a local bookstore going out of business yesterday and raided the psychology section, picking up a number of cardinal texts at $2.98 a pop. One of them was Please Understand Me, by David Keirsey and Marilyn Bates, of the Keirsey personality test. Actually, they call it temperament, not personalities. Reading the complete descriptions of what makes up INTFs and ENTPs et al was a real eye-opener, not to mention an entertaining and insightful read.

Character types, modified to account for the effects of social media and related technologies on interaction and communication, and taking into account users’ communication styles, relationship preferences, and sense of self and self image, could be a powerful addition to current efforts to architect social analytics and conversation analytics programs.

The state of the art in measuring and making use of social media users and social graphs still centers on relatively straight-forward views of influence, attention, intention, and social capital. While these are more easily measured on closed social networks, a model for analysis of distributed social media tools, including feed-based apps, is clearly on a lot of people’s minds. PR, marketing, advertising, branding, and customer service industries all want in on social media, and whether they stand by the sidelines watching, tracking, and monitoring, or jump into the river of conversation and engage, analytical tools and engagement applications will be essential. Nobody, but nobody, could possibly manage to be in the flow everywhere and at all times.

Traditional mass media approaches to audience metrics may have given us the right questions, and brought us to an appropriate starting point. But social media approaches will be needed now if we’re to make proper sense of audience behavior. And here’s where character psychologists like Keirsey might be of help.

I have an approach to social interaction design that takes conventional view of user experience and interaction design and extends it to social media users. With an eye to interpersonal dynamics, communication, and social practices, I like to call user behaviors "competencies." Each of us, as users interacts with social media and with others using it according to personal preferences, tastes, and most importantly, perceptions and interpretations. Our social skills online are social competencies. But each of us is different in our uses and, as psychologists would say, our behavior is informed by our psychology.

While this might be looking down the road a couple years, wouldn’t an effective social analytics tool, and engagement platform (say, for advertisers and marketers) use not only social metric data but also psychological and personality models? Take the concept of the influencer, for example. As it stands today, an influencer is a well connected, credible, trusted, and active. He or she may also be on topic. That’s not currently in the model, but should and probably will be, shortly, as we fold in not only who the person is but what s/he talks about (with credibility). So we might add expert to influencer.

But there are other kinds of user types, too, whose role in conversation can benefit specific marketing, branding, or advertising interests. There’s the expert. The inviter. The emcee. The connector. The artist. The follower. And more. Keirsey has 16 types, I’ve got a similar number, tho based around communication and presencing styles. The inviter, for example, would serve the needs of event promoters. The follower, the needs of PR and news dissemination. The expert validates new products. The emcee gathers together like-minded friends, and would benefit branding or entertainment rollouts.

This is a new medium, and it begs for appropriate analysis. The metrics used in mass media measurement serve the purposes of a medium in which two-way and friend or peer-network constrained interactions don’t exist. The future is engagement. Granted, masses of data will have to be mine and modeled. But isn’t that what we’re good at?

There’s consistency in psychology, and applied appropriately and insightfully, durability in behavior and relationships. The noise will subside if we can wise up and if we put users first. If we fail, the doors blow open and a river of spam will inundate the flow. Either way, the mass marketplace is going to enter the stream.

This post was authored by Adrian Chan who runs a social interaction design firm in San Francisco, California.