Lunch for good, food for thought

A post by friend Chiah Hwu today has reminded me of a topic that was on my mind recently. That being both the subtext and explicit goal of a series of well-catered, guested, and hosted lunches organized by the name of LunchforGood. Assembled by Chris Heuer and Myles Weissleder and made possible by Lunch.com's J.R. Johnson, the lunch series kept attendees well-fed in exchange for food for thought. The connecting thread, as drawn out by Chiah: better use of social technologies in support of conversation. And not just any conversation: good conversation, conversation for good.

This set me off in several directions and on more than one occasion I concluded that there will never be a social technology capable of steering conversation among participants to desired outcomes. That the basis for understanding and agreement between people has little if anything to do with the media and tools by which those people communicate with each other. In short, that the problem is simply orthogonal to the proposed solution.

I agree with Chiah that technologies do not solve social problems. They solve technical problems. And to frame a social problem in technical terms is likely a misguided approach leading to misdirected outcomes.

So on the tendency of social media to propagate good and goodness, I side with the skeptics. There is nothing intrinsically good or bad in social tools. And just as they are value neutral in themselves, it would be hard to make the claim that as tools they can bridge social gaps and misunderstandings. (Note that I mean "as tools" -- their uses can of course have impacts on culture, society, education, politics, economics, etc.)

But their use, well that's different.

Two points then come up around use of the social tool as tool for good. First, might there be uses of social tools that favor, if not directly produce, social good? And second, on what basis does good form: common identity or resolvable difference?

On the first point: Is is possible that social tools might be designed to facilitate constructive social processes (interaction, communication, commitments, trust, etc) as their social outcomes? (Differences in opinion around What counts as Good notwithstanding.)

And on the second point: Is it possible that common ground (what we have often called affinity) is a less interesting social attribute than differences of kind and degree?

If, in other words, commonality often takes the form of "I agree," and difference takes the form of "I disagree," which might engender the more rich and interesting conversation?

IF participants agree that Global Warming is bad, on what basis are they agreeing? Does this make them alike? Being alike, would they like each other? Is that the idea of commonality and affinity? For if it is, we can surely do better than to tag them all up, assign them a group name, and sell t-shirts emblazoned with "me too" and "follow me!"

Commonality based on shared identity comes at the price of individual differences. The issue, it seems to me, is less that we are different and more that we do not appreciate and understand the nature of our differences.

I, for one, think that a tool designed to tease out close differences would likely lead to far more interesting interactions than one designed to cement shared identities.

The problem raised over the course of the LunchforGood gatherings was, at some level, How do we improve social media so that we can all find what we have in common and get along better? But commonalities, whether as shared traits, passions, hobbies, beliefs, activities, record collections -- these do not provide a basis on which to extend the commonality. Commonalities in common are no guarantee of shared identity, shared affection, or harmony.

Shared attributes and qualities do not create a simple and smooth social unity and peace. Conflict and difference are not properties of identities and attributes -- they are a dynamic. They happen in context, during an event perhaps or due to a change in situation. And when differences erupt, it is not commonalities that resolve them but a shared commitment to constructive outcomes.

Conflict and peace are a matter of interaction and communication: they're a process. Shared interests are found through communication. Cooperation develops them. Conflict, when it erupts, is handled by means of interactions (brinkmanship is a classic type of interaction). Interactions are the way in which participants agree on a common course of action, by which they arrive at agreement on what to do if not why.

Interaction takes time, it involves turns, it is a process and is iterated. Now those all seem well within the purview of social media and social tools.

But getting there will take some creative thinking and design. And will take interaction models that can validate and capture far more than the overlapping interests of strangers on the line. (Commitment, for example, easily escapes the online environment. As can and do sincerity and honesty.) Interaction models perhaps involving shared resources, sequenced interactions, dependencies and knowledge/information partially revealed/concealed according to levels and commitments of trust earned and verified.

A final thought. Whether this is even a design problem for which there is a design solution is of course debatable. But the real world may offer some examples and references. Interaction dynamics have been found in conflict as well as peace and cooperation... For example, rituals, ceremonies, and less formal pastimes exist, which in their form and structure as social practices bind participants through objects, rules, moves, obligations (etc) to a shared course of action.

There may be many hidden dynamics and practices out there. We have perhaps only scratched at the surface of what social tools can be good at. And in many ways we cannot know what is possible, for that depends on practices and designs yet to be invented.

Dave Winer's little tweet reader: some thoughts

This morning I followed the suggestions of Marshall Kirkpatrick and tried out Dave Winer's new little twitter backup tool. I pulled the opml file into Google Reader as instructed and it wasn't long before i had one of those "Aha!" moments. The kind that happen when you re-encounter something you have been using for a while — a new perspective, a peripheral insight.

Marshall asks in his post if there are things we could imagine doing with the tool. Absolutely! Now, I'm not a coder so my understanding of api limitations is here restricted. But I'd want to build off the tool and create a conversation viewer. Twitter is an inefficient conversional tool, and third party apps have only limited effectiveness, because it simply delivers too many tweets. To make matters worse, each of us has different tweeting habits.

Personally, I'm constantly losing the people for the tweets. I use Seesmic desktop (love it) and have set up 7 panels each with 15 - 30 folks I follow in journalism, social media, marketing, user experience, philosophy and two groups of friends. Every few weeks I spend an entire morning reading the home stream and add people I've missed. This takes a lot of work!

The reader view of tweets surfaced people I've been missing for months — many now only tweet irregularly and infrequently. Now I spend a lot of time in the stream, so if I'm missing stuff, I can't imagine what it's like for others (well, I can, and it relaxes me to do so).

Being in twitter is being in the flow. And the river is now huge, it flows quickly, it's crowded, everybody's shouting (some are whispering), some are muttering to themselves, others just saying hello... it's a mess. It's no more a conversation than it is a high-school auditorium in a pre-game frenzy and everybody's got a sign to wave about and there's a constant stream of students coming and going and the signs keep changing and it never stops.

So I'd like to go meta, and Winer's tool reminded me why. I'd like a conversation viewer. Not just for the messages I'm missing, and more importantly, the people I'm missing them from, but for the cross-talk, depth, and threads, too. I'd like to see not just a feed for each of the people I'm following but I'd like to see the dots connected. I'd like to see and be able to navigate from person to person, on topic or off topics. During certain periods of time -- for the episodic interactions that often happen in twitter.

I'd like to surface experts, and not just the ones who think they're experts and tweet like they are, but those who are responsive experts: the ones who are quiet till asked. And the friendly experts: the ones who pipe up when they encounter a fellow soccer fan, make an introduction, and follow.

And the recommenders: those who may not be topical experts but who have some pretty good reasons to make a recommendation: they know the person, they know what they like, and whose recommendations are timely and helpful.

And the helpers: those who may not be experts but who recently had the same experience and can offer timely and targeted advice.

And the inviters: those who know what's going on and invite people they think may be interested (or invite everyone) because they themselves are interested. People who may not be hosting their own event but are socially and culturally active.

And the buddies: those who are there but you might not know it until you tweet something personal and it turns out they've been paying attention. The ones whose tweets you remember because they're kind and comforting in a me-too and we-all-have-those-kinds-of-days way. The ones whose tweeting is personal.

And many more. I'd like a meta-view of the space, by topic, person, group, clique, culture, profession, hobby, activity, location, and event. Over time, for periods of time, with flow velocities and rates of change. A navigation system so that I can hop around through conversations and save, favorite, and share. I'd like a viewer for myself and one for clients. I'd like different kinds for clients, depending on whether they do community management, brand management, PR, marketing, customer service, or sales.

And a whole lot more. I think I'm going to dig up some of my old conversation analysis stuff now. Did I mention social analytics? So, thanks Dave! And thanks Marshall!

Transient conversation networks on twitter

This is a re-post of a comment left on a post by Larry Irons, who commented on my recent post about HP labs' research on twitter's social networks.

My comment became a post unto itself.

Larry,

Great post. i think there's little doubt that in talk tools like twitter, which are time-based and conversational (of a form), the Dunbar number, while constant, probably includes a smaller number of active conversation participants.

Let's say that some percentage of the Dunbar number is a close set of friends, with whom daily interaction is not necessary to sustain engagement and maintain the relationship -- but with whom that conversation might be very grounding, rewarding, and meaningful.

There might be another percentage that is a set of peers -- members of one's network with whom coded and informative exchanges serve to surface, explore, share discoveries and create collaborations.

And there might be some percentage given over to new contacts, or more accurately, twitter partners in talk -- transient network members with whom a relationship is latent but not yet enduring. People for whom we are available for talk, but with whom we have no explicit commitment to maintain contact. The conversational activity among members of this subset would be more governed by the etiquette and practices common to the social tool in use: twitter is not blog commenting is not facebook friending is not linkedin answering and so on.

I would like to see some research into twitter networks that is diachronic -- which tracks conversation over time and correlates that with follower/following count.

I would expect that the number of transient relationships increases with an increase in followers/following. Does the Dunbar number hold steady? Or is it the wrong metric altogether for conversation monitoring? I suspect it's the wrong metric. Our ability to sustain engagements would more likely be a matter of our attention spent on the site/service, our interest in it (which goes through phases), our "goals," our experience to date and historically with the site (rising interest after adoption, plateau, fade out, rediscovery....), and of course the runs of talk themselves (talk increases around cultural news and events).

I would imagine that these conversation engagement metrics would also correlate to user personality types, and to the differences between monological, dialogical, and relational (Self, Other, Relational activity-oriented) "archetypes" of people in general.

To wit, a Self-oriented person might talk more if s/he believes he commands a bigger and more attentive audience. Stats revealing traffic to his site, click throughs on his links, retweets and @replies will embolden his/her engagement and make him/her more enthusiastic about tweeting.

An Other-oriented person might talk more the more @names and Directs s/he receives. Being inclined to respond to people, and to engage in one-to-one conversations, this user's increasing following count will likely create more conversations -- but possibly very passing and transient ones -- as many of them are of course greetings and introductions (what we do when we meet people).

A Relational/activity oriented person might @name @name @name people more the more s/he sees group activity on twitter. This being the kind of interaction that is least well supported in twitter (multiple D messaging isn't possible, for example, cutting out backchannel chat). Chat-style communication, which is necessary to create a sense of communal or group involvement and interaction, isn't possible in twitter. So the relational/activity oriented user must sustain an awareness of social groups over time -- this is a gate to group interactions. [I'm finding that Yammer, which I use with adhocnium members, is a twitter-chat tool for me. There's no sense that a public reads our posts, and we conduct a slow chat over Yammer that in which, almost paradoxically, the @reply becomes a sidechannel!]

A smart marketing tool would thus not use influence, but would use conversation dynamics and transient properties of social media conversations and their participants, to determine not who to impress, but rather how to distribute by means of user-centric social media communication networks.

I'll put this in Benjamin's language: Communication in the age of its technical mediation is contingent no longer on the interaction handling of facework but on the loosely-coupled coordination of asynchronously sustained individual commitments. I nearly called them "commentments." (reference is The Work of Art in the Age of Mechanical Reproduction - Walter Benjamin)

(This became so long that I'll blog it on my site, too. Thanks for the inspiration -- keep it going!)


Note: This blog post belongs to a series on "status culture." The posts examine status updates, facebook activity feeds, news feeds, twitter, microblogging, lifestreaming, and other social media applications and features belonging to conversation media. My approach will be user-centric as always, and tackle usability and social experience issues (human factors, interaction design, interface design) at the heart of social interaction design. But we will also use anthropology, sociology, psychology, communication and media theories. Perhaps even some film theory.
The converational trend in social networking sites and applications suggests that web 2.0 is rapidly developing into a social web that embraces talk (post IM, chat, and email) in front of new kinds of publics and peer groups. User generated content supplied to search engines is increasingly produced conversationally. Social media analytics tools provide PR and social media marketing with means to track and monitor conversations. Brands are interested in joining the conversation feeds, through influencers as well as their own twitter presence.
This changing landscape not only raises interesting issues for developers and applications (such as the many twitter third party apps), but for social practices emerging around them. So we will look also at design principles for conversation-based apps, cultural and social trends, marketing trends, and other examples of new forms of talk online.
These blog posts will vary in tenor, from quick reflections on experiences to more in-depth approaches to design methodology for conversational social media.

News and Feeds: Power Curve to the Long Tail?

The web, and the social web in particular, has been hailed for its contribution to a new economic principle: the long tail. It was brought to our attention convincingly a couple years back by Wired editor Chris Anderson, and has since enjoyed its own long tail of popularity. The argument goes, basically, that the web's connectedness, combined with its increasing use as communication among users, not only sustains but often accretes visibility to qualified products and services *over time*.

The marketing blitz favored by short-term and launch campaigns (the power curve) calls upon the attention supplied during a curious and enthusiastic audience. The long tail offers the opportunity for a much more slowly accumulating span of attention, which is the attention brought to the product or service by the interested user. Where the power curve delivers newsworthy results, the long tail delivers powerpoint-ready follow through.

Long tail is the discovery economy. It's a sort of "socialization of search results" -- it works by qualifying the value of results by means of social participation. The big stories in long retail have been entertainment and media consumption, e.g. Netflix, Yelp, Amazon, and so on: sites that enable discovery along the lines of "what I like" by means of meta data captured through site use and social participation along the lines of "things that are alike" and possibly "liked by members who are alike" and/or "liked by like-minded members" (the difference is associating people on the basis of what they like or whether they seem alike: interests vs. identities)...

Long tail works by talk -- a kind of structured talk (because it captures the declaration of like, the level of like, the likes associated, and then of course cross-indexes those with item data and meta data such as category, genre, etc). So it works because it happens when users are interested. And a user who is interested, like a user who is searching, is a good indicator of value and relevance.

Now let's consider the dramatic growth in conversational media: represented by tools like twitter and friendfeed. These are not tools designed to capture content in depth. Nor do they extract much by way of meta data, taxonomic relations, etc. They're designed for simplicity and used for a faster form of talk than we get in walled-garden social networking sites. But as there is a great deal of activity in the conversation, much of it highly relevant and most of it uniquely particular to its users, it behooves us to ask: what value can be extracted from the content and relationships of conversational media?

Where in these media would an advertiser wish to be? In the tweet? Between tweets? Alongside the twitterer, his or her stream, with or without friends? Or perhaps in search results? Hashtagged? ... You get the picture. Advertising always wants to be placed in the best context possible -- but the context of conversational media is highly biased towards use and utility. If twitter were ham radio, the context of use would be the microphone; the context advertisers know to recognize is not the microphone, but what comes out of the speaker. What gives conversational media their utility is their functionality. To use another analogy, we don't use phones for listening -- hence our resistance to tele-marketing. Of course, I have a suspicion, unproven, that far more attention is paid by twitters to the tweeting than to the tweet reading. That's a bias I think is shared by all posting media, and a reason for their high redundancy of communication.

There is enormous interest by third parties and by media-related businesses in the rise of conversational media. They want to know how to leverage these tools for their own purposes, be this through participation and engagement, or by monitoring and tracking. Social media marketing and advertising will mine status, news, activity, and other self-talk and conversational feeds for the kinds of valued relationships (people to people, people to things, events, etc) and associations (people in groups, audiences; things in groups, categories) they contain. The strategy here, however, may not be long tail.

Indeed the coming feed market may want to think in terms of the power curve. The personal and social news-making they are mostly used for have more in common with the power curve of news in general than they do with in-depth discovery. You might argue that discovery is surfaced through conversational tools, as in the blogs we read and then tweet to. Conversational monitors, and tools like Radian6, Buzzlogic, and smaller twitter monitoring apps, might then combine deep blog crawling for long tail value, and feed/conversational content for the power curve (breaking news, memes, viral, etc).

It will be interesting to see where this goes. I don't think that the influencer approach most often cited as a model for conversational value is the be all and end all. It comes out of social networking models, and misses the conversational dynamics of talk tools. I suspect that the best mining applications will take a time-oriented approach over a network-based approach. (The network of followers is no network, it's a list, and there's no guarantee that the audience represented by a list of followers is paying attention to the stream).

Conversational media are short on content and long on activity. But if the medium is the message, the message value of conversation media may be on the envelope.

It's all words, but some words are more equal than others

Words. Wrapping up west wing last night (I had left the final episodes of season 7 dangling unseen for months, obtaining, as is the law of desire, more pleasure from anticipation than from the satisfaction itself, though I hope this does not apply to the current election year), I got a real kick from the show's depiction of political campaigns, and messaging in particular. The show's characters, brilliant beyond what is possible in the swift repartee and back-channel corridor correspondence they so effortlessly carry on, day after notable day, in the hallowed halls of the White House, drop political messages as culturally on target as they are tactically on point. Practically inventing policy from the wings of power, they print flights of fancy on poetic updrafts that, as if in winged migration, rise above the current political climate's spin cycle like the bouncy air that escapes a laundromat. Their words lift, and with them, our spirits.

At risk of overburdening the better angels of our nature with the heavy load of worn laundry, however, I'll cut out the preamble and let old Uncle Abe be.

All words are equal but some are more equal than others.

A philosophical moment here, then, on social and conversational media , on what we do with them and how analytical tools can make sense of them. And on the differences in both Kinds of Talk and the markets that are moved by them.

Strategic talk: this kind of talk wants to move the recipient, the listener, the audience, and without sincere concern for what s/he/t/hey *think*, produce a response or action.

Communicative talk: this kind of talk wants to maintain a relationship, create and build understanding, if not agreement. And even if it fails to produce consensus or peace, at least bridge differences and create some common ground upon which might grow a common wealth.

Professional and business needs and interests: are PR, marketing, advertising, branding, sales, and so on, and have an interest in distributing their message as well as in tracking audience follow through.

End users: more often than not, simply want to use the tools without hassle from the salesforce, for the purpose of coordinating daily realities and building and enjoying friendships online

Problem: Arriving at what is the unit of meaning that matters.

Solution: Varies by the profession, business interest, in other words the beholder in whose eyes value takes recognizable shape.

Current conversation and social media analytics still focus on words. Words can be searched. Sentiments cannot be searched. Opinions cannot be searched. Friendships cannot be searched. Influence cannot be searched. And attention cannot be searched. Yet.

Words look the same because the medium flattens speech into text, eliminates genre, idiom, style, and relationship from the form of writing analyzed.

In the case of speech, the utterance, utterer, and meaning uttered do not coincide: what a person says, and means in saying it, offer two distinct acts, and the listener can watch the person talking, or take what he says at "its word." But the speaker is not present for the production of meaning online, and only the words remain. Context, stylistics, intent, and so on can now only be inferred.

Words. We search them and from the results, try to obtain narrative, message, opinion, recommendation, review, conversation, even relationship, expertise, and psychology. We find the patterns we can see, and miss those we do not yet know how to map or model. The use of conversational and social analytics across social media is still focused on words, and the patterns we use rely on a coincidence of word use across all forms of online writing and talk. What we see is often what we want to see, what we can do is what we can think of doing.

The needs of PR
PR is about articulating messages that both define facts and seek to shape opinions. It's a form of impression management in which the burden is placed on the messaging to present the best face, the most appealing story, with the least controversy, and yet in a voice of measured integrity and with as much corporate sincerity as possible.

PR is an art -- the art of practicing strategy and executing tactically in forms that border on the personal. The press release is not so much a statement issued by a company as it is a statement already written about the company. Produced by an inside or outside department or agency, it takes the public's position on the company. This alone makes it interesting, for in taking the position of the consumer, outsider, market or what have you, the press release is highly suggestive: "here's what we would like you to think about us, in words you might find easy to pass along or quote" -- the release heads off controversy and anticipates challenges to the extent that it can, and is already a first cycle in spin.

I say this without judgment -- PR is an interesting form of discourse, and not a simple one. It requires a certain amount of knowledge not only of the company being written about, but about the audience being written to. PR is useless if it doesn't fly. But PR is even more valuable if it is picked up by end users, consumers, and so on, and passed along that way. There's no competing with the power of a message voiced in the first person consumer.

Some of the ways in which PR can benefit from social media and conversation tools like twitter would include:

distribution: how far has the message been distributed?
influencers: by whom?
pickup: with what kind of impact and pickup?
citations: where has it been cited/linked to?
On message quotes: where do we see direct citations, and by whom?
Off message quotes: where do we see topical citations, but reworded (and why? for credibility? or as a challenge to our message?)

Speed and acceleration: how quickly does our message get out? is it rapidly reported and then tails off, or does it accelerate? can we map that distribution path?

Tracking PR through social media:

• track messaging
  
• track mentions
  
• track links
  
• track circulation
  
• track comments and commentaries
  
• track reactions (sentiments)
  
• track influencers
  
• track social media pickup
  

The needs of branding

Branding has to do with the impression a brand makes on its customers (as well as a broader audience). This impression is part image, part message, part feeling, part tone, style, class, taste, and so on. Some brands want to be easy to identify with. Some play hard to get and out of reach. Some brands enjoy broad popularity, others seek to stand at the pinnacle of perceived value... Brands have historically sought out the advertising and branding media that suit their messaging and brand the best. And the internet has not historically been a site of deep value. Rather, it's seen as a medium that flattens out the differences between brands, that reduces margins to zero, laughs at loyalty, and which replaces the market of scarcity with one of surplus. It is hard, brands may feel, to rise above the sheer volume and availability of goods sold through commerce online. 

Might social media offer new possibilities? Audiences that want to show their brand allegiance publicly? Groups that enjoy brand affiliation? Markets that subscribe to a brand and buy with affinity? Consumers able to show their brand identities -- motivated by the social rivalry and mutually reinforcing "desire" that capitalist forces are meant to unleash when more people want the same thing than can  have it? 

Would users make brand announcements in their status or feed updates? Would they place brand decals on their facebook or myspace pages? Create slide shows, animations, videos, and other mashups in which they recontextualize pop culture, friends, and brands into one living and dynamic expression of co-branded personality and style? Or sign up to brand pages on social networking sites, track and subscribe to feeds, event announcements, participate in boards, forums, and so on and so forth?

Branding is about listening, watching, and possibly about leading consumer messaging and uptake -- but with an interest in seeing one's brand embedded in common discourse. So in this sense, yes, a brand wants to track conversations on social media: for the impressions made, for expressions in which it is embedded, for the phrases, images, and other kinds of statements that end users (consumers) add to the brand. For sentiments expressed about the brand, to whom, in front of whom, and so on.... Some brands may want to become conversational -- that is, reduce the separation between themselves and their consumers, and instead welcome and participate in dialog, trust-building interactions, and mutually enlightening exchanges. Not all, in fact most brand will not do this -- it is risky (or seen as risky), it takes control away from brand managers, and it can be seen to reduced brand equity (insofar as equity is "distinction" not provided by the common person)... But many may try, and those to do so first stand to benefit from the novelty of social media branding the most.

Tracking branding through social media:

• track impressions
  
• track sentiment
  
• track propagation
  
• track social media mentions
  
• track authentic speech for phrases, expressions
  
• track markets for affinity groups
  

The needs of market research

• track competition
  
• track trends
  
• track culture
  
• track society
  
• track mass media hits
  
• track social media cultures
  

The needs of sales

• track sales
  
• track seo
  
• track propagation
  
• track clickthroughs
  
• track interest
  
• track social media links, feed, profile page mentions
  
• track competition
  
• track reviews
  
• track recommendations
  
• track ratings
  

The needs of event promotion

• track word of mouth
  
• track reach
  
• track influence
  
• track trends
  
• track anticipation
  
• track sentiment
  
• track buzz
  
• track social graph adoption and pickup
  
• track changes over time as event nears
  

Note: this post is "ongoing".... 

Radian6 and climate change: views of mainstream, blog, and twitter conversations

Using Radian6 to investigate social media conversations around one of my own personal involuntary preoccupations -- climate change -- I geeked out this afternoon for a while and have these screen shots to share and discuss. What you see above are three topical clouds created by a search across media types over thirty days for the keyword phrase "climate change." (Click it for actual size.) All media (top left) includes blogs and forums, video, images, mainstream online media, and twitter. The top middle shows results from just blogs and forums, and twitter. And the top right window shows results for twitter only.

Below the cloud panes is a topical drill down spanning the same time period: showing results for terms within the "climate change" results. (In other words, a comprehensive survey would require additional searches. Each results in a bucket of results that can then be further filtered and searched.)


I noticed "radiohead" in the twitter view, top right, and clicked it to see posts. (screenshot on left). Cooler heads prevailing, Radiohead had turned down a US promotional gig to spare the air. True or not, I didn't have time to check.

Looking at the results, I clicked the peak on April 21 to see what was up that day. Doh -- earth day. I entered that, and a few other terms, for the screen to the left. (It being earth day every day here in San Francisco, this one had pretty much slipped out through the fissures that crack me up, in my mind, way in the back of my mind.... Ok, honestly, earth day a bit redundant nowadays, isn't it?)

I used the cloud views to find keywords to add to the trend panel. Radiohead didn't register in the trend panel, for example. "Green" is just below "earth day," suggesting that perhaps "Green day" could have taken advantage of some free media coverage (are they still together? I confess I don't recall. Another case of fissure. Fizz-ure... ) Next in prominence on that day were "food," "gas," "action," and "president," which, if I were a writer for The Colbert report, I could have made into a joke, using, perhaps, either "food" or "gas" as the subject of "action" taken against the "president."

Interesting that on Earth day both food and gas were of concern. Food growing or food eating? And seeing as "prices" are just beneath "president," it's possible that food and gas prices may have occurred in Earth day commentary that included administration policies and leadership. Or not. One doesn't want to read between the lines. (Though the lines are pretty close together, and track nicely, so hey, why not?)

As you can see making sense of these verbal trends is not rocket science. Could we have guessed without searching that food and gas prices would come up together? They track with earth day, but to be fair, there was a UN report released that wknd regarding the food crisis. It's possible that they're related. Wouldn't take a poet.

Now what's cool about this tool is that you can read the news sources for any additional key phrases right here. Even view videos. And you can browse a list of influencers (sites and blogs) for the topical profile. Shown here are influencers and a "river of news." Global warming was the biggest hit within "climate change," and shown here are posts that refer to global warming. (Inluencers can be sorted by unique commenters, total comments, enagement (number of comments and length of comment), and topical inbound links.

Now in this view, which focuses on April 20 - 22 (earth day and one day prior and post), there are interesting differences between the topic clouds for mainstream media. Look at the list below. Differences in terms used in the mainstream media, on blogs and twitter, and on twitter alone, are clear. Mainstream media describe a high-level view of the discourse, blogs, commentary on that discourse, and twitter, more personal and actionable conversation.

_____mainstream_____
emissions
issues
america
government
department
public
scientists
national
federal
country
world


_____blogs and twitter_____
save
reduce
live
weather
real
better
information
future
article
action


_____twitter_____
industry
fight
students
right
difference
help
water
citizen
officials
college
sustainability

So far this search has turned up roughly what one would expect of it, and indeed you find what you're looking for when using measurement tools. The benefit of tracking end user conversations such as those on twitter ought to be in the authenticity of twitter talk, and in its speed and immediacy. Radian6, because it updates in real time, can be used to follow these conversations as they happen. That said, it's necessary to supplement twitter talk with blogs and mainstream media, for they provide the narratives, arguments, and semantic map of the conversation space. Topical context is assumed by twitter users (as it is often in chat and IM) -- that context is provided by the slower talk media. At this time, twitter is still very small, and on-topic results for searches on twitter are noisy and fragmented. But for those interested in personal expressions and conversation, and for a read on real-time audience attention and interest levels, there's a lot of potential yet in what twitter can surface.


Note: I did not explore Radian6's tools for influencer results and additional keyword drilldowns in this post.

Hashing through twitter hashtags -- a look at structured conversation

In my ongoing binge to ferret out the social mechanics of twitter third party sites and tools, hashtags deserves attention. It's small, and by all appearances might die on the vine, which would be sad. But if the great culling whose season draws near were to remove hashtags from the social media dna pool, it would be for reasons owing less to the operationaI think and more to fundamental problems with the user experience.

Hashtags make a big demand on the twitterer. They ask that she tag up posts while writing, which requires a) added effort, b) a pause to reflect on meta while composing, c) a sense of the benefit provided to folks who search by tag in the future. (A) and (b) pull the user out of the immediacy of twittering -- not much, but maybe enough to matter.

I remember working with a startup that was into the idea of tagging up chats for better discovery -- of like-minded chatters and of topically-related chats. I thought the idea was great, especially because chats aren't logged, and in theory at least the promise of social web is to connect people around what they talk about (in common). But to get meta from talk requires either automation or a change of user behavior. Either sites and services mine talk for the meta, and build links and suggestions of topics and talkers, or the user declares meta while talking (or just after, as in tagging).

Chat was one problem, twitter is similar. Because twitter is a kind of slow-moving chat. And like all other feed-related sites and tools, twitter I think aims to do more than provide dis-intermediated chat channels. Unless I'm completely mistaken, there are a lot of folks out there who believe that there's value in fast web conversations, call it feeds, micro-blogging, or what have you.

And because it's always hard to structure a conversation and to keep it on topic, not to mention expect users to follow topical threads, the goal of hashtags was to capitalize on what's said *inside* of posts. Their benefit would be to extract topical continuity and consistency from disparate flows (conversations) -- to re-flow if you will, by tag.

The benefit of exposing and surfacing common topical threads from talk accrues primarily to those who come along after the posts have been published. That's the purpose of topical mining, and it's an approach to making the web useful that Google has mastered for pages. But for posts, or conversational turns, the challenge is huge.

Conversation is notoriously poor at providing explicit meta about itself. It's just not how it works or how we talk. We know what we're talking about when we talk, and it involves the person(s) with whom we're talking. We don't declare what we're talking about if it can be already understood. Seo is built on this -- embedding meta in copy and pages for better search results. If you're talking about orchids you're unlikely to speak "flowers" in the same breath. We don't supply meta while talking (Dave Sifry used to describe this as getting meta out of the exhaust).

A lot of social web sites live on the principle of using a small number of active participants to produce content that can be enjoyed by those who come later. The good ones, like Yelp, offload the member-to-member communication from the topical content as much as possible. In Yelp's case, with gestural tokens, a questions page, etc -- to keep the reviews as clean as possible. (Could tweeted reviews work even? They'd devolve into highly subjective recommendations probably.)

Two challenges face hashtags. First is getting the user to tag as an act of talking. Second is that all tags are equal. There's neither vertical hierarchy (tag, subtag, subsubtag) nor modal organization. The latter is interesting, and worth a note, and since I just made it up I need to think out loud here a minute.

Talk is not all equal. Statements of speech can be declarative, performative, can be a form of request or appeal, and so on. Just think of the differences in the kind of utterance that are: invitation, recommendation, flirt, factual declaration, opinion, observation, question, answer. Modal organization of tweets would suggest that in addition to semantic tagging we have statement types: question, recommendation, announcement, link, flirt, and so on. You can see where this goes: Yahoo has Answers, Facebook has social apps, Linkedin has recommendations, Yelp has symbolic tokens, Google has (wait, google doesnt seem to get social. oops), etc etc.

So on hashtags, if you root around, you'll find some totally unorganized examples of this. There are (and oddly or not so oddly enough Germans seem to have gotten into organizing talk -- I lived in Berlin for a year and a half so I've had fun comparing German and English equivalents...). On hashtags there are posts tagged "now," "love" "jokes" -- tags that suggest the modal type of tweet. "Now" is not a topic but leads to conversations about what users are doing. "Love" is as much an expressive identifier (I'm in love, who's in love?) as much as it is a factual identifier. "Jokes" is topical, but it also is an attractor for quips and humor -- and joking is a performative form of speech unto itself if anything is.

When social media work to produce informative content for those who primarily consume, it's because they are a means of production. By analogy to the industrial age, the communication age (our era) uses information technologies as means of production. Communication acts leave behind content. Interaction tools that simultaneously publish to a public, as are all social media, "manufacture" a new form of talk. It's mass media gone social. But we know this already.

Is there a soft or hard threshold, then, for social media tools that ask the user to produce meta while in the act of posting/talking? Believers in the public utility of the social web as a means of democratizing the media and information might say no. Believers in connectivity, communication, and the social utility of social media might say yes. Hashtags sits between the two.

Much of my work involves helping social media companies to engineer interactions and communication for the purpose of producing leftover utility to latecomers and consumers. It's a social engineering challenge -- call it the art of generating unintended utility out of useful socially practices. It's an art because it requires engaging the user's motivation. Incentives (to benefit consumers by writing restaurant reviews) only work for a handful of users. For most, the byproduct of added value has to be in the exhaust -- and the act of participation should be enough in itself to motivate engagement. Users simply have to like using the tools -- for their own reasons (which are many indeed, but that's a whole different story).

Let's quickly take a look at this from a different angle -- social media marketing. Twitter offers the promise of mining and tracking conversations, if not participating in them, with an unprecedented degree of proximity, directness, and immediacy. Twitter search engines and meme trackers currently offer more breadth than hashtags for the simple reason that many more users simply type "movies" than type "#movies." But check "movies" on a site like summize (say you're a social media marketer), and results will include this: "Uncle. I can't work on this paper anymore. Let's go to the movies!." Use hashtags and you'll get better posts, though far fewer, because users have declared their topical selection of "movies." Intent is among the metrics measured by those in social analytics, and you can't get better than hashtags for that.

If only users could be asked to declare their intentions while conversing so that mining companies could extract the gold! No, it seems far more likely that the success stories and serendipitous moments ahead for web 2.0 will be found among those tools that can engineer social interactions such that the meta is an accurate but unintended byproduct of talk and engagement. (Beacon?) We'll have to watch this unfold and keep testing the frontiers. Either way, there's a lot to talk about.

Hashtags

Reputation, Conversational Index, Twitter, and Tweeterboard

I geeked out on tweeterboard.com last night and found myself getting lost in the conversation metrics the site displays in its box score tab, and which it presumably uses to calculate reputation scores. Their metric's not transparent to me, and if anyone has thoughts on how they calculate reputation, I'd love to hear from you. But I got to thinking about it, and so began mapping a few measurements of my own to see if they made sense.

In doing so, it quickly became apparent that "reputation" is in itself a fuzzy marker. And in the context of conversation and conversation analysis, especially.

For example, reputation speaks of the person, firstly. A person has a reputation. How is it earned? By their identity? By what they say? By who they know? And who knows them? By appearance, or by fact? By integrity, consistency, and other personal attributes. But also by their social status, their contributions, credibility, and effectiveness even.

In terms valuable to social media marketing, reputation might mean influence to some. Authority to others. Credibility and experience. Popularity and social capital. Participation and involvement. Also responsiveness and social value as a hub or connector.

Perhaps reputations are multiple -- reputation for something. For leadership, for success, for matchmaking, for consistency, for connectedness, for influence, for independence.

And if reputation is also to be used for something, that is, leveraged in womm viral campaigns, for example, consumers/users will offer value according to the type of reputation they have.

A social media marketer might want influence in some campaigns, might want to reach experts in another, or reach connectors/inviters for yet another. If the social marketer wanted campaign traction by pushing a branding campaign across the social graph, for example, his or her point of access and entry would suggest that s/he use influencers of a certain type. For popularizing, a user with a reputation for popularity. For credibility, a user with a reputation for integrity and expertise. For event promotion, a user with a reputation for being first to know and for inviting friends. And so on.

Individual influence varies according the communicability of their status in a social graph/social network. I have friends whose restaurant recommendations I would take no questions asked, others who can recommend films, music, or car repair. But they're all different people. Recommendations are personal, and so there's little knowing about a recommender without knowing about his or her relationships.

Which was why this exercise was so interesting: conversations captured on twitter at tweeterboard reveal several of the elements critical to reputation analysis. Granted that without semantic content analysis, they're only structural. Interesting nonetheless, however.

So now, to tweeterboard and this exercise in imagining reputation metrics. First off would be the conventional Friend and Follower count. Should be fine, but there are already potential issues here. (Note: by analogy to serp/seo/sem speak, friends = links; followers/followed should = link polarity.)

Number of followers : should indicate influence by means of popularity. However twitter users add friends as fast as Britney Spears loses them. Friends make a person look like somebody, are a friction-free connection (on twitter), and are a means to being found. In other words not a good enough indicator in and of itself.

Number following : should indicate enagement, and some amount of social context. You follow who you know, and who you find interesting. But here, too, the number is biased. It serves to enhance a user's appearance, and is not an declaration of either interest (level or kind) or attention (listeners are not always listening).


So then qualify influence by number of people with posting frequency (for participation level) and post volume (for engagement).

Number of posts: Post volume and frequency is the currency of measure on a conversation tool. Like money supply and velocity, posts are flow volume and rate of flow. Here again, there is an issue, for when it comes to reputation, all posts are equal but some posts are more equal than others. There are users who produce torrents of tweets, and who clearly enjoy twitter as a kind of group IM/chat. And others who post to make a point. And all points in between. Activity online is not all action, and communication online is often inactive communication (or communicative inaction -- a bug/feature that Facebook has raised to a cultural phenom with its activity, news, and friend feeds and status updates).

Communication becomes action, so say the linguists, when it takes the form of moves: statement - response. Talk is serial by nature, and so conversation usually involves a round of moves, or what we sometimes call "turn taking." The low rate of response and the improbability of responsiveness on a public or semi-public chat tool like twitter is a simple and direct byproduct and symptom of the technology's presence bracketing. Users don't know who's paying attention, not to mention who's listening. If talk were supposed to be a reciprocal exchange of linguistically embedded claims upon speaker and listener leading to understanding, agreement or even consensus, twitter would not be our first choice of talk format!

But that's what makes it so compelling -- clearly "conversation" doesn't even begin to describe what twitter is or does. Social media are about new forms of talk (and new forms of presence). I'm preaching to the choir -- we all get this.

Onward, to more of what Tweeterboard must presumably fold into its fluffy mix of conversational dough (read: currency ;-) ).

The spread: Now this one is fascinating. High spread numbers (e.g. between two twitter users, number posts to @recipient vs number posts received from recipient to @sender) indicate asymmetry. Meaning that these users don't like each other equally? No way to know that, so how about these one user wants more from the other? A negative spread shows that the user sending messages isn't getting equal number of replies. The issue here is that we can't measure the relationship by sent/replied because twitter is imperfect. @name messages may go unheeded because they're missed -- that simple. Message delivery is imperfect on twitter because so many users prefer to @name in public (for valid social reasons, mostly) than direct message (even tho the latter offers a higher delivery guarantee). Posting @name in public accrues visibility and social capital to the sender, not to mention findability. Same for positive spreads.

So perhaps the thing to measure in the spread is the degree of spread (I've seen 0:50). Or the range of spreads in the aggregate. Then a user who has a tight and narrow range of spreads would be a responsive user, an attentive user. A wide and wild range of spreads would be an inconsistent, unresponsive user. This is plausible, tho spam posts would screw this one up and require yet another round of filters (If I receive spam posts I don't want to lose reputation points just because I've not replied to them).

Then there's the difference between @name posts and @name citations. When a tweet begins with @name, it's usually for @name. But if @name is cited within a post, it's possible that the message expresses thanks, recognition, or is a citation, promotion, or other form of social referencing and distribution. I wouldn't have a clue if tweeterboard makes the distinction. The high degree of @name citations on twitter would suggest it that these uses could be used to build soft (tacit) social graphs. (Interesting thought: a Milieu Metric).

Some, and often highly influential twitter users, also show a large number of orphaned post exchanges. These show up as 0:1 or 1:0, and are indicated in the box score as 1 or -1. A very large number of 1's might indicate that other twitterers want to be in this user's audience and circle. But again, it might simply mean the user missed the @name message. Hard to know intent, but absolute number of 1's/-1's would seem to suggest visibility and social capital.

Getting creative, here are few other possibilities that spring to this (now tired) mind.


@name cited (but never sent to @name : this might indicate rubbing elbows, or wanting to appear in the company of @name. Benefit to user posting but not directly communicating to @name would be apparent social capital (what I like to call social media's proclivity not just for appearance but also "apparancy").

@recipient_name sent or cited and leading to other @recipient_name citations : this might indicate a tight social clique of users attentive to each other. @name messages get the attention of others and solicit uptake. For example "congrats to @name for whatever" leads to a round of "yeah congrats @name!". Could be used by marketers to suss out active trust circles.
ditto for: @recipient_name sent or cited and leading to other @recipient_name replies

@recipient_name sent or cited and leading to other @sender_name replies : would raise the former to the level of friendship, e.g. from clique to group. Because in this version the reply is more than a citation, it's reply. Attention is paid not just to the @name cited but to the @sender who posted the citation. Could be used by marketers to suss out active conversationalists.

@recipient_name sent or cited and leading to other @sender_name citations : is somewhat uncommon, but responding to the poster not just the post is a sign of friendly attention and might be a metric of social presence. This is a "great to see you" moment and proffers a measure of relational density. Unless the message is nasty and mean, it's a sign of friendship, for the users are acknowledging each other (from "i follow you to I see you," or to quote Genesis, "Follow you, follow me"; every look wants a look back, and online "I see you" must be stated explicitly, so it's always *already* "I see you and therefore I want to see you seeing me" -- and on twitter, if this is in front of others, all the better!)

Ok, enough for now. I came up with more but you'll have to hire me. (just kidding.)

Damn I love twitter.

gratitude and respect goes to Stowe Boyd for pushing the conversational index long ago, and for reflections on twitter and the flow