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The Coevolution of Language & Social Technologies
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The Coevolution of Language & Social Technologies


This presentation explores the hypothesis that language and social technology are in a coevolutionary state. The narrative cites arguments from Evolutionary Linguistics and showcases examples of how …

This presentation explores the hypothesis that language and social technology are in a coevolutionary state. The narrative cites arguments from Evolutionary Linguistics and showcases examples of how social technology is changing the way we communicate.

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  • Explore language and social technology COEVOLUTION45 minutes explain what coevolution is, share linguistic research + examplesWhere things may be headedInspire you to think about opportunities
  • Marketing by tradeNOT a linguist or data scientistBut I’ve worked with professionals who areI’m an entrepreneur interested in the opportunity space created by language and social tech
  • Assumes belief in evolutionRecognized that evolution applies to languagesIt’s not by academies, but by regular people
  • Including the people who MAKE social techAnd USE social tech
  • The idea that languages evolve is based on the idea of Memes
  • I’m NOT talking about ideas that spread and die out
  • I’m talking about persistent behaviors Sharing, commenting, tweeting, broadcasting in increasingly public ways.
  • The study of the evolution of languageIt’s relatively new disciplineStephen Pinker is a source of inspiration
  • If you think the language that we use was handed down from a mountain from a flying spaghetti monster ….Good time to find another session ….
  • I have three claims that I’ll go through today
  • Frame the conversation with the idea of CoevolutionThe humming bird and flower is a common exampleNot just at the species level, but a macroscopic biological levelLanguage and social tech are not “Species”This is where Memes and Evolutionary Linguistics come inHardware and Software are also considered to be in a Coevolutionary stateSelective pressures that affect one affect the other
  • Before we talk about language in detail, let’s look at recent changes in social techWe might see clues about the kinds of changes we’d expect to see in languageMobile tech is the dominant delivery mechanism for socialIt’s reach across the globe is growing exponentiallyBreaking down geographic barriers
  • Social Tech is also breaking down cognitive barriersInterface for autistic people who could not communicate or socializeSimilarly it breaks down literacy barriers
  • As well as language barriersCombined with services like Google translate, it’s possible to communicate across languages in real time …
  • At the same time the overall number of languages globally is declining
  • And more and more people are leveraging the most common language platformsCommunication is aggregating on a small set of languagesMore people, and a more diverse set of people, speaking fewer languages will surely impact langauge
  • And we see it pronounced on social networksGranted Twitter’s population is not a representative sample of the populationBut, there are many fewer languages being used on the platform than are present where it is available. I’d hypothesize that social technology will amplify that trend of language consolidation
  • Social tech is shifting inheritance from being generational (genetic) to being peer-to-peer (memtic)Historically technology was passed along through familial lines (familial trades)Today, our parents may provide their children with a device but the apps they use are driven by peers
  • Parents don’t know what SnapChat isThey don’t know what linguistic conventions are being developed on the platform Irony,SnapChat’s impermanence would give parents some solace in knowing that what kids share is not permanentWhile it gives kids solace knowing that their parents cannot find their message history.
  • This highlights difference between genetic and memetic evolutionMemes move and evolve fasterSo if language and social tech are coevolving we might expect to see language evolve faster as wellPerspective, Robin Lakoff proposed that literacy was the first social technology. It started this trend away from familiar inheritance towards peer-to-peer transmission.
  • Going back to the SnapChat example ….I find myself increasingly asking how do the affordances of a social technology create linguistic conventions?
  • Some observations:Social tech makes sharing seamless and fastIt increases the amount of data we shareIt increases the cadence of sharing
  • Consider emailIt’s focused on longer-form contentIt’s cadence is measured in hours and days
  • Consider WhatsAppIt’s short formAnd has a very rapid cadence ….Arguably is becoming more prevalent over timeWe have a broader portfolio of social tech available to use We’re optimizing communication across these channels and adapting language to these channels
  • Here’s an example based on some comments by Serge Brin about his use of Google GlassIt’s an entirely new language convention to reply to an incoming DM with an image or stream request that you dictate into your wearable.
  • Taking it one step further, we may not even need to dictate out loud soon.What kinds of short hand vocalization languages will be developed to support a service like this?
  • And, it’s not just outbound comms. It’s how we’ll ingest this content by way of solutions like Spritz that optimize reading speed. Of course, reading is just the beginning, we’ll see social technology providing translations across media types so that we can get the message in the best format for our current situation. You can’t read while your driving and you can’t listen while you’re at a concert. Hopefully this small set of examples have given you a sense of how social technologies exert evolutionary pressure on languageSubstantiate the claim that Social Tech is a primary driver of language evolution.
  • Story for Pinker’s Language InstinctDeaf school children in Nicaragua No exposure to formal sign language, Only rudimentary system of communication using pictures and signs -- nevertheless developed their own self-contained sign language...with its own hand gestures, associated body language, emotional intensifiers, etc.
  • “Slow down. Children are playing here.” Literal translation: “Lift your foot. There are small people playing here.”Absorbed “Warning” sign into their languageAppropriated this “scrap” as their own.This is a good metaphor for how we create, propagate and use lanaguage on social networks
  • Considering symbols such as the @ SignIn 2006, Robert Andersenthe first person on Twitter to use the "@" symbol to reply to another user. Not a proper @-mention Established a standard convention that we use todayAnd it’s crossed social platformsAndersen did exactly what the deaf children did. He picked up the scraps or affordances of what was around him and used it to create a new language conventionHow do things like this take off on services like Twitter? Twitter listened to the way people used the service and designed around that.
  • Of course, the HASHTAGNot only aggregated content by topic areaBut is used to put a message in contextAgain, it’s not being adopted across platforms Would tags in photos be considered a Symbol?Serge Brin’s seamless switching between text based communication and image based communication we’re reconstructing language in ways that optimize but also in ways that add depth and meaning. Think for a moment, before social technology came to market how often were new symbols introduced into popular culture?
  • And then there’s a massive inventory of new idioms:There is a story behind each of these …. TL;DR: “Too long, didn’t read.” Used before providing a gist or summary of a longer message.ELI5: “Explain it like I’m 5-years-old.” A popular kind of Reddit post that explains complex subject matter in simple terms.FTFY: “Fixed that for you.” Signaling a correction.ITT: “In this thread.” Used before offering a short assessment or upshot of the thread – e.g., “ITT: Everyone watches too much television.”Have an upboat. Used to make fun of Redditors who seek karma/upvotes and peer recognition to an excessive degree.ಠ_ಠ Used to denote one’s disapproval.
  • In many ways the idea of a global venue for conversation is relatively newObama’s team posts and people across the world actually engage in back and forth dialogueBrings together attracting fans, detractors, trolls, and people sharing their pleas for help.It’s not ALL just people posting into the ether.Unprecedented diversity on a common platform leads to unique pressures on language and social tech
  • Self identification is a primary behaviorNeil deGrasse Tyson as astrophysicist, book author, and radio show host. Adam Savage’s profile, as scientist and television figure.
  • Hopefully these examples point to how social tech becomes part of language the more we incorporate it into our parlance.But’s it’s not just limited to what we share in the forground of our communications.
  • There’s a wealth of date that’s being shared without any additional cognitive effort on our part.Sensors allow you to bundle in additional context dataTo engage in set-and-forget communications
  • As language and social tech become integrated there are parts that can be differentiatedForground content is what we interpret immediatelyBackground content is explicit but we may not interpret itImplicit content is what can be read between the linesFace to face, facial expression is background content that puts the foreground in context if you’re perceptiveAnd we chose our venue strategically …. Perhaps we prefer a conference call where we don’t see faces and where we have a backchannel.Insights are where things get most interesting from my perspective and take us to the third claim.
  • The utility of a service likeseparate signal from noise
  • At the foreground levelNo narrative thread. We often can’t see the forest for the trees.
  • Step back and we can begin to pull out patterns.
  • Princeton University / University of London analyzed a weighted and fair sample of 250,000 Twitter users.“...we were able to predict the network community of a user, a purely structural feature, by studying his or her word usage, and we found that this was possible with rapidly growing accuracy for relatively few words sampled.”Social groups can be segmented by language useIn context of increasing diversity on common language platforms this is not too surprisingWe have the technology to recognize more dialects This goes well beyond explicit self-identification
  • In the last year a round of acquisitions have validated the market for this kind of segmentationAt Oracle we acquired both Eloqua (B2B) and Responsys (B2C)Right message, right channel, right time.
  • Big brands are investing in systems to help them communicate with usThe question is, when will consumers use this same tech to engage with each other?BUT IT”S CONSUMERS THAT DRIVE LANGUAGE USE/EVOLUTION NOT COMPANIES
  • Consumer services do small pieces today. When is the best time to send an email or a tweet to a friend?That’s a good example of explicit contentAdd in the background context and we can expose relevant implicit informationYou both care about [x] topic.You both have been to X location.You’re both in the area- You should tweet this to him.
  • Add more variables here.
  • See this post for more info:


  • 1. The Coevolution of LANGUAGE & SOCIAL TECHNOLOGIES Source: Roland Smart Vice President of Social and Community Marketing Oracle @rsmartly SXSW - March 9, 2014
  • 2. Father, Designer, Social Technologist, B2B/B2C Marketer, Life Hacker, Thinker, Entrepreneur, Maker, Blogger, Manager, Innovator, Rock Climber, Mountain Biker, Aspiring Changemaker @Oracle
  • 3. “…Language is not, as we are led to suppose by the dictionary, the invention of academicians or philologists. Rather, it has been evolved through peasants, by fishermen, by hunters, by riders.” –Jorge Luis Borges …and by technologists and technology users.
  • 4. MEMES: the basic unit of change a word, phrase, idea, style, symbol, idiom, or behavior that spreads from person to person within a culture. #SocialCreole Source:
  • 6. 1 2 3 Social technology is a primary driver of language evolution. As social technology augments language, it becomes part of the language. As language and social technology coevolve expect more intermediation.
  • 7. COEVOLUTION: the influence of closely associated species on each other in their evolution
  • 8. Mobile is breaking down geographic barriers. Source: Statista and StatCounter
  • 9. Social applications are breaking down cognitive barriers…
  • 10. … as well as basic translation barriers.
  • 11. “Even if the numbers of people who speak a language are growing numerically, their portion of the overall landscape of languages that their language occupies is being compressed by the larger languages growing even faster than they are.” -David Harmon, Terralingua Source: National Geographic
  • 12. “Even if the numbers of people who speak a language are growing numerically, their portion of the overall landscape of languages that their language occupies is being compressed by the larger languages growing even faster than they are.” -David Harmon, Terralingua Source: National Geographic
  • 13. Source: MIT Technology Review and Semiocast
  • 14. For the most part, users aren’t learning how to use these technologies from school/parents/mentors… Source:
  • 15. 77%of all U.S. college students use Snapchat every day. …instead, they rely on peer exchanges and intuitive design. Source; Sumpto
  • 16. GENE MEME LOW Rate of Inheritance HIGH Rate of Inheritance
  • 17. a more accurate explanation: THE DESIGN OF SOCIAL TECHNOLOGIES + THE AFFORDANCES OF THESE DESIGNS are powerful behavioral agents
  • 18. Amount of time required to publish has decreased substantially Amount of data shared has increased substantially Feedback loops are much shorter, with the net result being more total interactions
  • 19. Consider the affordances and limitations of email Source:
  • 20. The average WhatsApp user (there are 450 million of them) sends and receives 3,534messages each month. Source Statista
  • 21. To send a message, just blink an eye and talk: Sources: fiickr/photos/gmprod and “Hi Allison - I’m front row at the concert! Want me to send a live stream to your big screen right now?”
  • 22. Actually, you can talk voicelessly if you want. Source: Dominic Hart, NASA
  • 23. Read 1,000 WPM. Don’t worry about content overload. Spritz: “Focused on text streaming technology.”
  • 24. 2 As social technology augments language, it becomes part of the language.
  • 25. “In social situations where adults communicated using a pidgin, children who had only the pidgin as input transformed it into a creole–a “full” language with all of the properties of languages which have developed through normal language evolution.” –Stephen Pinker, The Language Instinct Turning Pidgins into Creoles Source:
  • 26. MEME: SYMBOLS Nov. 2, 2006: The first @ conversation on Twitter May 30, 2007: Twitter officially launches an @ feature, complete with user “Replies” pages Source:
  • 27. MEME: SYMBOLS Aug. 23, 2007: Chris Messina proposes the # symbol to organize tweets for groups; Twitter executives originally deem the idea “too nerdy” July 2, 2009: Twitter officially launches # feature; Facebook and G+ follow suit Source:
  • 28. MEME: IDIOMS & SLANG tl;dr ELI5 FTFY ITT Have an upboat _
  • 29. MEME: NORMS & BEHAVIORS Who is @neiltyson? “Astrophysicist. Am Museum of Natural History: Author: Space Chronicles, Pluto Files, Inexplicable Universe [Video], Host: StarTalk Radio.” Who is @adamsavage? “I play a scientist on TV. Obsessive maker of things. Host of Mythbusters on the Discovery Channel.”
  • 30. These are all examples of foreground content; social technologies have added these symbols, words, norms, and behaviors to our everyday languages. But what else is there?
  • 31. - Temperature - Barometric pressure - Infrared proximity - Infrared gestures - RGB light - Accelerometer - Multiple microphones - Multiple cameras - GPS - Wireless Sensing and Surfacing the Background Context …
  • 32. Explicit Implicit Foreground Content Social Messages + Some Metadata (e.g., Hashtags) Insights (e.g., segmentation/affiliation, bias, sentiment) Background Content Metadata (e.g., Location/Environmental/Healt h Data) Source:
  • 33. 3 As language and social technology coevolve expect more intermediation.
  • 34. Analyzing (Supposed) Randomness
  • 35. Source:John Bryden, Sebastian Funk, and Vincent Jansen and “The research on Twitter word usage throws up a pattern of behavior that seems to contradict the commonly held belief that users simply want to share everything with everyone.” “In fact, the findings point to a more precise use of social media where users frequently include keywords in their tweets so that they engage more effectively with other members of their community or tribe.” -Jason Rodrigues, The Guardian
  • 36. Digital Body Language - Primary Interests - Primary Dislikes - Purchase Intent - Brand Sentiment - Income Level - Social Popularity - Intent to Switch - Susceptibility to Material Incentives - Habits Based on Hidden Data
  • 37. Andrew Pole had just started working as a statistician for Target in 2002, when two colleagues from the marketing department stopped by his desk to ask an odd question: “If we wanted to figure out if a customer is pregnant, even if she didn’t want us to know, can you do that? ”
  • 38. Uncovering Shared Interests & Automating “Starter Messages” tartingRelationships
  • 39. Interpreting Social Data to Help Us Strengthen Our Relationships
  • 40. Providing Helpful Relationship Reminders “When the relationship starts ("day 0"), posts begin to decrease. We observe a peak of 1.67 posts per day 12 days before the relationship begins, and a lowest point of 1.53 posts per day 85 days into the relationship. Presumably, couples decide to spend more time together, courtship is off, and online interactions give way to more interactions in the physical world.” Source:
  • 41. What will you build? How will you change the languages of social technologies? “The new media have caught on for a reason. Knowledge is increasing exponentially; human brainpower and waking hours are not. Fortunately, the Internet and information technologies are helping us manage, search, and retrieve our collective intellectual output at different scales, from Twitter and previews to e-books and online encyclopedias. Far from making us stupid, these technologies are the only things that will keep us smart.” -Stephen Pinker Thank you! @rsmartly