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This paper surveys the emerging science of how to design a “COllective INtelligence” (COIN). A COIN is a large multi-agent system where:
In contrast, we wish to solve the COIN design problem implicitly, via the “adaptive”character of the RL algorithms of each of the agents. This approach introduces anentirely new, profound design problem:
Assuming the RL algorithms are able toachieve high rewards, what reward functions for the individual agents will, whenpursued by those agents, result in high world utility? In other words, what reward functions will best ensure that we do not have phenomena like the tragedy of thecommons, Braess’s paradox, or the liquidity trap?
Uber, a San Francisco-based personal transportation oriented startup, is facing a backlash from a few of its drivers. But the confrontation is less about Uber and more about the challenges facing a society being rebuilt because of connectedness.
Are we ready for a Quantified Society
However, if you look at the story from the context of just Uber, then you will miss the real narrative. This isn’t the last time we will hear about it — there are more Uber-like companies with on-demand workforce. There have been incidents on AirBnB.
That last comment by Alazzeh resonated with me because it encapsulates what work will be in the future and what the next evolution of labor unrest could be. And it also highlights a problem we have not thought about just yet: data-darwinism.
In the industrial era, labor unrest came when the workers felt that the owners were profitting wrongfully from them. I wonder if in the connected age, we are going to see labor unrest when folks are unceremoniously dropped from the on-demand labor pool.
What are the labor laws in a world where workforce is on demand? And an even bigger question is how are we as a society going to create rules, when data, feedback and, most importantly, reputation are part an always-shifting equation? (Reputation, by the way, is going to be the key metric of the future, Quora founder and Facebook CTO Adam D’Angelo told me in an interview.)
At present we rank photos, rate restaurants, like or dislike brands, retweet things we love. But if this idea of collaborative consumption takes hold — and I have no reason to think it won’t — we will be building a quantified society. We will be ranking real humans. The freelance workers — like the Uber drivers and Postmates couriers — are getting quantified. The best ones will continue to do well, but what about the others, the victims of this data darwinism? Do they have any protection or any rights?
I admit I don’t have any answers. And while I am as much of a techno-optimist as the next blogger, I don’t even know where to start. I do think it is important for us to start talking about what the etiquette of a connected and a quantified society will be.
I will use myself as an example. I would say, on most days, that I live up to my idea of a normal online citizen — living online like I do offline. I try not to talk about my family. I am an active Uber user. And I take every opportunity to provide feedback. But I don’t take the ratings system lightly, regardless of whether I’m giving someone one star or three stars or five stars.
Just as I am not shy about awarding five stars for timeliness and quality of service, I am happy to chastise, too. And I do the same for every service I typically use — Postmates or TaskRabbit or AirBnB or Exec. What if I give someone a wrong ranking? Given how often we are likely to rank and rate in the future, will wrong ratings even bring about any sense of guilt?
It is the 21st century. We are more narcissistic and more self-absorbed. Does human decency and sense of fair play shift to the online realm as well? It’s hard to know. I mean, we have seen some of the nicest people in real life turn into a baboon’s backside once they are online and are anonymous. Authenticity in a world where we are trying to play a role in a movie starring us takes on a entirely different hue.
There’s an epidemic going on in science: experiments that no one can reproduce, studies that have to be retracted, and the emergence of a lurking data reliability iceberg.
There’s an epidemic going on in science, and it’s not of the H7N9 bird flu variety. The groundbreaking, novel results that scientists are incentivized to publish (and which journalists are then compelled to cover) seem peppered with gaps: experiments that no one can reproduce, studies that have to be retracted, and the emergence of an iceberg of an integrity crisis, both for scientists personally and for those who rely — medically, financially, professionally — on the data they produce.
As a recent PhD, I can attest to the fact that many researchers first experience the iceberg as no more than an ice cube-sized annoyance impeding their work towards a Nobel Prize. Maybe the experimental instructions from a rival lab don’t quite seem to work. Maybe the data you’re trying to replicate for your homeworkassignment don’t add up, as UMass graduate student Thomas Herndon found. If a spreadsheet error that underpins sweeping global economic policy doesn’t convince you, here is some more evidence that we are already scraping the iceberg of a research and data reliability crisis.
In a production economy, value creation depends on land, labor and capital. In a knowledge economy, value creation depends mainly on the ideas and innovations to be found in people’s heads. Those ideas cannot be forcibly extracted. All one can do is mobilize collective intelligence and knowledge. If knowing how to produce and sell has become a basic necessity, it no longer constitutes a sufficiently differentiating factor in international competition. In the past, enterprises were industrial and commercial; in the future, they will increasingly have to be intelligent.
Via Howard Rheingold
You’re walking home alone on a quiet street. You hear footsteps approaching quickly from behind. It’s nighttime. Your senses scramble to help your brain figure out what to do. You listen for signs of threat or glance backward.
CONTEXTUAL COMPUTING: OUR SIXTH, SEVENTH, AND EIGHTH SENSES
In the coming years, there will be a shift toward what is now known as contextual computing, defined in large part by Georgia Tech researchersAnind Dey and Gregory Abowd about a decade ago. Always-present computers, able to sense the objective and subjective aspects of a given situation, will augment our ability to perceive and act in the moment based on where we are, who we’re with, and our past experiences. These are our sixth, seventh, and eighth senses.
Hints of this shift are already arriving. Mobile devices with GPS deliver location-based services, which sets a baseline for the many ways your phone can gather information it will use to make your life easier down the line. Amazon’s and Netflix’s recommendation engines, while not magnificently intuitive, feed you book and video recommendations based on your behavior and ratings. Facebook’s and Twitter’s valuations are premised on the notion that they can leverage knowledge of your acquaintances and interests to push out relevant content and market to you in more effective ways.
YOUR PERSONAL GRAPH CONTAINS (GULP) ALL YOUR BELIEFS
This is the set of data relating to a person’s deepest held beliefs, core values, and personality. It’s what makes a person unique in the world, just as the social graph helps to show what makes her similar to others. The data set is under-developed at the moment, and it’s quite difficult to design for, even conceptually.
Given that psychology still struggles to explain exactly how our personal identities function, it’s not surprising that documenting such information in a computable form is slow to emerge. There are early indicators that this will change, however. For example, Proust.com, a relatively new (and struggling) social-networking service, asks users to document intimate details of their lives and their beliefs based on the idea of the famed Proust Questionnaire. People have, quite reasonably so, been reluctant to share such information in a publicly viewable social network.
A more successful example is Evernote, which has built a large business based on making it incredibly easy and secure to document both recently consumed information and your innermost thoughts. Scraping such intimate files for data is currently the questionable realm of the NSA, however. Entirely new solutions will need to be created if the potential of the personal graph is to be reached.
YOUR BEHAVIOR CAN BE EASILY GRAPHED
It’s easy for data to depict what you actually do instead of what you claim to do. Sensors do the job. So do, if less elegantly, self-reporting mechanisms. This data can sit in pivotal contrast to the interest graph, allowing computers to know, perhaps better than you, how likely you are to go for a jog. It would be useful, too, for a travel site that notes how you tell friends you’d like to visit China but records that you only vacation in Europe. Rather than uselessly recommending vacation deals to Beijing, a smart travel app would instead feed you deals to Paris or Berlin. The behavior graph provides the foundation, to some extent, of Google Search, Netflix recommendations, Amazon recommendations, iTunes Genius, Nike+ run tracking, FourSquare, FitBit, and the entire "quantified self" movement. When mashed against the other three graphs, there’s a potential for real insight.
We investigate how online networks mediate contentious politics by analyzing communication around a global campaign launched in May 2012. We analyze about 450,0
We investigate how online networks mediate contentious politics by analyzing communication around a global campaign launched in May 2012. We analyze about 450,000 Twitter messages related to the Occupy and ‘indignados’ movements. We test how well integrated the two movements are; we characterize users posting content relevant to both movements; and we examine the robustness of the network to node removal. We find that global connectivity depends on a small percentage of users and that the two movements are mostly concerned with their local struggles: the bridges connecting the two flows of information channel just a small percentage of all information exchanged. We use these findings to assess theoretical claims about political protests in the digital age.
Keywords: contentious politics, digital protests, online social networks, structural constraint, modularity structure, network robustness
Are you an avid user of Snapchat, that kind of person who likes bits that go poof? If you or your kids are under 25, chances are you do. The wildly popular photo-sharing app—which promises that pictures self-destruct after 10 seconds—is a clear sign that many people long for privacy. Snapchat claims to have finally delivered to us a medium that does not forever save and store our data. We want that! Of course we do.
Unfortunately, Snapchat doesn’t quite transport us to the land of data privacy. It sounds too good to be true, and it is. In much the same way that Facebook deludes people into the belief that they can actually be private, it gives us a false sense of security. Twitter makes no bones about privacy; it is, and claims to be, an open public network where you are public by default. With the likes Snapchat and Facebook—and most of social media, in fact—many mistakenly believe in the illusion of being private.
The specific problem with Snapchat, of course, is that while the photo message on Snapchat disappears from the phone of the recipient after a few seconds, it does not prevent the nimble-fingered receiver from taking a screenshot. If that happens you get an alert, but what good does that really do? It certainly doesn’t prevent the screenshot from being shared with others, as happened at this New Jersey high school. There’s another hack to work around that alert. And last but far from least, a US-based company Decipher Forensics told the Guardian that they figured out how to recover photos from the Android version of Snapchat in a matter of days. The company is now trying to recover photos from the iOS version of Snapchat. The photo-app has been downloaded more than five million times in the Android marketplace and has been at the top of the Apple app store for quite a while.
In 2010 New York City added 54 million metric tons of carbon dioxide to the atmosphere (75% from buildings, the bulk of the rest from transport) but that number means little to most people because few of us have a sense of scale for atmospheric pollution.
Carbon Visuals, supported by Environmental Defense Fund, have created a film that makes those emissions feel more real - the total emissions and the rate of emission. Designed to engage the ‘person on the street’, this version is exploratory and still work in progress.
Emissions in 2010 were 12% less than 2005 emissions. The City of New York is on track to reduce emissions by 30% by 2017 - an ambitious target. Mayor Bloomberg’s office has not been involved in the creation or dissemination of this video.
See how we can help cities engage their citizens in carbon issues.
See video on YouTube
Street-level view of 10 metre (33 ft) spheres of carbon dioxide gas emerging at a rate of one every 0.58 seconds
For the technically minded:
In 2010 (the latest year for which data is available) New York City added 54,349,650 metric tons of carbon dioxide to the atmosphere = 148,903 tons a day = 6,204 tons an hour = 1.72 tons a second.
City of New York, Inventory of New York City Greenhouse Gas Emissions, September 2011, by Jonathan Dickinson and Andrea Tenorio. Mayor’s Office of Long-Term Planning and Sustainability, New York, 2011
At standard pressure and 59 °F a metric ton of carbon dioxide gas would fill a sphere 33 feet across (density of CO₂ = 1.87 kg/m⊃3;).
If this is how carbon dioxide gas was actually emitted in New York we would see one of these spheres appear every 0.58 seconds.
Google propose une nouvelle fonctionnalité dans son onglet "Tendance des recherches" : la possibilité de visualiser en temps réel les recherches effectuées sur le réseau.
Google propose une nouvelle fonctionnalité dans son onglet « Tendance des recherches » : la possibilité de visualiser en temps réel les recherches effectuées sur le réseau. Cette fonctionnalité n’est disponible actuellement que pour 11 régions du monde (Etats-Unis, Taiwan, Inde, Japon, Australie, Canada, Hong Kong, Israël, Royaume-Uni, Singapour, Russie) mais l’interface est fluide et sympathique.
Google permet aussi de visualiser les tops des recherches aux Etats-Unis, depuis 2004, selon différents critères : auteurs, équipes de basket, éléments chimiques, pop stars,… Et d’intégrer ces divers éléments dans ses sites.
Información sobre tecnologías emergentes & impacto en negocios & sociedad
El objetivo es ayudar a los usuarios a evaluar la fiabilidad de la información que reciben de los medios sociales mediante el análisis del comportamiento de los reporteros ciudadanos. En concreto, Monroy, en colaboración con los otros autores de la investigación “Narcotuits: Social Media en tiempos de Guerra” ha recogido y analizado un importante volumen de datos de hashtags (etiquetas que permiten seguir un tema) como #Mtyfollows o #RiesgoMty. Por ejemplo, 600.000 tuits que contenían algúnhashtag relacionado con la guerra de la droga.
El enfoque social que desde sus inicios como investigador ha mostrado Monroy se sembró en su niñez. Su familia estuvo muy involucrada en movimientos políticos progresistas durante los años 80. Y a este entorno se unió su fascinación por la ciencia y la tecnología. “Me gustaba mucho leer una revista científica para niños llamada Chispa, de la cual aprendí mucho, y la enciclopedia Proteo, que era mitad historia de ciencia ficción sobre un robot y mitad enciclopedia científica”, recuerda el joven.
En la actualidad, Monroy trabaja en Microsoft Research y en el Centro Berkman para Internet y Sociedad en la Universidad de Harvard, ambas en EE.UU.. Desde ahí sigue trabajando para promover la participación ciudadana. “Más allá de mi interés personal por el hecho de ser algo que aflige a mi país de origen, el caso de los narcotuits me pareció fascinante desde el punto de vista científico porque las redes sociales han permitido que los ciudadanos tomen el rol del Estado y de los medios de comunicación tradicionales", explica. Por ello Monroy destaca el papel del ciudadano como seleccionador de contenidos; más aún teniendo en cuenta la dificultad que entraña la misma propagación de la información o -lo más difícil de cuantificar- la desinformación.
If you were to walk into my office, I’d have a pretty decent sense of your gender, your age, your race, and other identity markers. My knowledge wouldn’t be perfect, but it would give me plenty of information that I could use to discriminate against you if I felt like it. The law doesn’t prohibit me for “collecting” this information in a job interview nor does it say that discrimination is acceptable if you “shared” this information with me. That’s good news given that faking what’s written on your body is bloody hard. What the law does is regulate how this information can be used by me, the theoretical employer. This doesn’t put an end to all discrimination – plenty of people are discriminated against based on what’s written on their bodies – but it does provide you with legal rights if you think you were discriminated against and it forces the employer to think twice about hiring practices.
The Internet has made it possible for you to create digital bodies that reflect a whole lot more than your demographics. Your online profiles convey a lot about you, but that content is produced in a context. And, more often than not, that context has nothing to do with employment. This creates an interesting conundrum. Should employers have the right to discriminate against you because of your Facebook profile? One might argue that they should because such a profile reflects your “character” or your priorities or your public presence. Personally, I think that’s just code for discriminating against you because you’re not like me, the theoretical employer.
Of course, it’s a tough call. Hiring is hard. We’re always looking for better ways to judge someone and goddess knows that an interview plus resume is rarely the best way to assess whether or not there’s a “good fit.” It’s far too tempting to jump on the Internet and try to figure out who someone is based on what we can drudge up online. This might be reasonable if only we were reasonable judges of people’s signaling or remotely good at assessing them in context. Cuz it’s a whole lot harder to assess someone’s professional sensibilities by their social activities if they come from a world different than our own.
Given this, I was fascinated to learn that the German government is proposing legislation that would put restrictions on what Internet content employers could use when recruiting.
At this week’s Big Data in Biomedicine conference, David Ewing Duncan, author of Experimental Man, delivered a keynote speech titled “You as Data: Can Big Data Predict Your Future Health?”
Using himself as a guinea pig to explore the new age of personalized health, Duncan has collected close to 30,000 genetic traits about himself through numerous medical tests and scans and noted, “If everyone on the planet had this much data collected, you’d be in something called yottabytes”
In his talk, Duncan revealed what he’s learned from this tremendous reservoir of personal health data and discussed promising biomedical technologies and research that may boost longevity and lead to radical life extension. He urged attendees to contemplate how long they wanted to live - giving them the choice of 80 years, 120 years, 150 years or forever -and the implications of living that long.
Big data is cool and all, but is it really changing the way companies function? Yes. Here are 10 stories that show that transformation.
Big data has become something of a buzzword. Everybody talks about it, but its impact can be elusive. How is big data really changing the way companies and other organizations function? These 12 stories highlight that transformation: from helping health insurers keep better tabs on patients, to changing how cars are made, to easing traffic congestion on busy freeways. These case studies show big data at work.
3. Presidential campaigns
4. Highway traffic
5. Pro basketball
7. Social networking
10. Social change
11. Prescription drugs
Global Outlook :: Digital Humanities (GO::DH) is pleased to announce the first Global Digital Humanities Essay competition. Topic: This competition is for research papers looking at some aspect of ...
This competition is for research papers looking at some aspect of the national, regional, or international practice of the Digital Humanities. Within this broad subject, participants may choose their own approach: focussing in individual problems or projects (e.g. some specific scholarly, preservation, or cultural heritage issue), or broader philosophical, geographical, sociological, political, or other discussion of the practice of Digital Humanities in a global context.Prizes:
Up to four awards of $500 (CAN) each plus an opportunity for fast-track publication inDigital Studies/Le champ numérique. Additional awards, including fast-track publication, may be available for runners up and honorary mentions.Eligibility:
The competition is open to any interested party including students, graduate students, junior faculty, and researchers unaffiliated with a university or research institution. Only one submission is permitted per person.Language:
Submissions may be in any language. The adjudication committee will attempt to find readers for languages that lie outside its own experience (A list of members of the adjudication committee and the languages they read is found below). Digital Studies/Le champ numérique publishes in English or French. Winning contributions in languages other than French or English will be published in their original language with a translation into either English or French.Adjudication criteria:
The committee will adjudicate essays based on their interest and topicality, the quality and breadth of their research, and the quality of analysis and data. In each case these criteria will be considered in relation to the chosen topic. The committee is also committed to ensuring a diversity of voices and experiences in represented in the competition and among the finalists.Submission process:
June 30, 2013: Deadline for initial submission. Submissions may take the form of extended abstracts (500-1000 words) or complete drafts (recommended length: 6,000-15,000 words). Winning entries in this round will receive an interim award of $200.
October 30, 2013: Deadline for final submission. Winners from the initial round will be invited to submit their completed papers by October 30, 2013 for review, copy-editing, and submission to Digital Studies/Le champ numérique. Upon successful completion of the review process, the winning contestants will receive a completion bonus of $300.
Send your submissions to email@example.com. Preferred formats are PDF, HTML, Plain Text, Word, Open Office, or LaTeX.
Una nueva aplicación desarrollada por un joven estadounidense permite a los consumidores comprar productos de empresas cuyos principios comparten, así como tomar parte en campañas a favor o en contra de ciertas ideas.
Una nueva aplicación desarrollada por un joven estadounidense permite a los consumidores comprar productos de empresas cuyos principios comparten, así como tomar parte en campañas a favor o en contra de ciertas ideas.Ivan Pardo, un estadounidense de 26 años de edad de Los Angeles, tardó unos 16 meses en crear una aplicación que lleva el nombre de Buycott. Su funcionamiento consta de dos partes. Una vez descargada la aplicación, los usuarios pueden buscar los grupos disponibles que abogan por apoyar o boicotear varias iniciativas y unirse a ellos.
Una de las campañas más populares es la que se denomina 'Diga 'no' a Monsanto', que incluye a unos 10.000 usuarios que se oponen a la empresa biotecnológica que produce alimentos genéticamente modificados. Unas 29.000 personas también se unieron al grupo 'Exija la etiquetación de los OGM'.
Las campañas se dividen por temas: la educación, el medio ambiente, la justicia económica, la responsabilidad social o los derechos de los inmigrantes, entre otros. Por el momento, la aplicación cuenta con más de 100 campañas y la lista sigue aumentando. Pardo insta a la gente a crear campañas si existe alguna causa que ellos quieren ver en la aplicación.
El segundo servicio que ofrece la aplicación es escanear y analizar el código de barras de productos e identificar su marca y la empresa productora. Después, la aplicación comprueba si estas actúan contra la filosofía de las campañas que el usuario seleccionó.
Questions for drive CI "genome" design:
What is being done? ----- Goal
Who is doing it? ---------- Staffing
Why are they doing it? --- Incentives
How is being done? ------ Structure/Process
Exemples about CI design : Linux (hierarchy) and wikipedia (crowd).
- Collaboration "gene", Crowd (multitud) "gene".
- Handbook of CI. 100 exemples about CI.
- Differences and similarities onto CI models : "Threadless" and "InnoCentive".
Do groups have genetic structures? If so, can they be modified?
Those are two central questions for Thomas Malone, a professor of management and an expert in organizational structure and group intelligence at MIT’sSloan School of Management. In a talk this week at IBM’s Center for Social Software, Malone explained the insights he’s gained through his research and as the director of the MIT Center for Collective Intelligence, which he launched in 2006 in part to determine how collective intelligence might be harnessed to tackle problems — climate change, poverty, crime — that are generally too complex to be solved by any one expert or group. In his talk, Malone discussed the “genetic” makeup of collective intelligence, teasing out the design differences between, as he put it, “individuals, collectively, and a collective of individuals.”
A look at some of biology’s communication networks
Those same electrons that kept New York Telephone customers connected also work to facilitate energy transfer between bacteria. In “Live Wires” Mohamed El-Naggar and Steven Finkel recount the birth and development of electromicrobiology, a fascinating new field of research that explores the transmission of electrical signals between microbes. The authors describe how electrons move not only along thin hairs called pili that project from the cell bodies of certain bacteria, but also in the shared periplasmic space of long chains of thousands of linked bacteria, and from the membranes of several bacterial species to extracellular mineral surfaces. “This vision of integrated microbial circuits was unimaginable 10 years ago,” the authors conclude. “But as we unravel the molecular and biophysical basis of long-distance electron transport, these bacteria may one day become essential components of everyday technologies.”
Yes, we are all connected—and always have been, long before we could phone a friend, eavesdrop on microbial and molecular crosstalk, or begin to know how to strengthen and secure our most precious natural bonds.
The usefulness of understanding relationships within networks is becoming more apparent, so it is fortunate that our ability to explore and analyze networks by visualizing them is improving. Common examples of networks that analysts examine include connections between terrorists or connections between linked sites on the World Wide Web. While these networks in particular get a great deal of attention today, other more run-of-the-mill networks can be explored more insightfully as well, such as the connections between products that are often purchased together, which we’ve pursued as market-basket analysis for ages. The most common and typically most useful form of network visualization consists of nodes (things, such as people or products) and links (connections between things), displayed as a diagram in various arrangements. When networks are large, consisting of thousands or millions of nodes, node-link diagrams can become so overwhelmingly cluttered, they’re sometimes called “giant hairballs.” Consequently, those who study information visualization have been trying to develop ways to simplify and clarify these diagrams. A new approach described in a paper titled
Interactive Infographic - Plastic pollution in the oceans represents a major global environmental challenge. At a global scale, man-made debris has been observed to accumulate in remote areas of the ocean in large circulating gyres.
Accumulation of marine floating debris originated from highly populated coastal regions
Plastic pollution in the oceans represents a major global environmental challenge. At a global scale, man-made debris has been observed to accumulate in remote areas of the ocean in large circulating gyres. The source of this plastic is assumed to be mostly land based, however little is known about the relative contribution of different land based sources to each gyre.
Did you know there’s new information collected about you, every time you go to the doctor? But what happens to that data after you leave?
Did you know there’s new information collected about you, every time you go to the doctor? But what happens to that data after you leave? Roughly 80 percent of collected health data is stored in hundreds of different forms such as lab results, images and medical transcripts, making it virtually useless.
That’s why health-care organizations are leveraging big data technology to capture patient information. The idea is to improve health care through care coordination, population health management and patient engagement and outreach.
Marty Kohn, chief medical scientist for IBM Research and a former ER doctor said, “The U.S. lags most other countries in health care. Our health-care system needs a transformation to compare to those around the world. We need to make it more personalized to make it more efficient and safer.”
Kohn offered three examples of how big data is already transforming patient health care at various organizations.
Data-driven decisions: This is when new evidence, or secondary evidence, is drawn from existing data. Big data can search for patient similarities through thousands of characteristics to help diagnose a problem.
Stream computing: In stream computing, data is not collected and stored. It’s used “near real-time,” or the time minus minimal processing delays.
At The Hospital for Sick Children in Toronto, for example, every baby in the neo-natal ICU has vitals monitored and can predict an upcoming problem before it happens. Hospital staff will be alerted to a life-threatening infection up to 24 hours earlier than current practices.
Patient Care and Insight: This third use involves predictive data analysis for high-risk patients.
Kohn said using the information around us will help doctors make better decisions. Technology enables doctors and health-care providers to create better health-care patterns for the future, he said.
(2012). BECOMING A TWEEP. Information, Communication & Society: Vol. 15, A decade in Internet time: the dynamics of the Internet and society, pp. 680-702. doi: 10.1080/1369118X.2012.666256
Consistent with what the diffusion of innovations literature would predict (Kwon & Zmud 1987; Rogers 1995; Koivumäki et al.2008), our results suggest that individuals who were already using similar services (such as other SNSs) and engaging in behaviours common on Twitter in 2009 (such as posting status updates) were more likely to be using Twitter the following year. These results are similar to the findings of a national survey using cross-sectional data that found that those who regularly used other SNSs were more likely to engage in status updating and to use Twitter than those who did not use SNSs as often (Webster 2011). Similarly, we also found evidence that one's prior online consumption and production activities play a role in Twitter adoption. While prior research has already shown that a person's topical interests play a significant role in becoming a Twitter user (Hargittai & Litt 2011), our results further this finding by demonstrating that the specific types of online content that one has experience consuming and producing at earlier times impact service adoption as well. On the aggregate level, those who engaged with topics on the Internet that are also popular on Twitter as identified by prior literature (Cheong 2009; Marwick 2010), such as entertainment and celebrity news and sports, were more likely to use the service a year later than those not engaging in such activities. These findings suggest that people who are already looking for and discussing online content related to topics popular on Twitter are more likely to begin using the service. While we did not directly test one's perceptions of Twitter's usefulness, the Technology Acceptance Model suggests that if people believe a technology will be beneficial, they are more likely to use it (Davis1989). It may be then that people adopted Twitter because they knew that it would be an appropriate source for the content they were already seeking and sharing. We found that certain types of content production and consumption seem to influence Twitter adoption more than others. When controlling for one's background characteristics, online skill and cell phone experiences, results imply that participants who engaged with entertainment-focused topics, such as movies or TV shows, were more likely to use Twitter than those who did not. Research by Marwick and boyd (2011) suggests that Twitter may be especially relevant to people interested in content of this nature because of the ‘perception of direct access to a famous person’ (p. 6). Our findings seem to support this claim. In contrast, other popular topics on Twitter do not seem to influence Twitter adoption from either a production or a consumption perspective. While politicians and news outlets are prevalent on Twitter (Kim et al. 2010; Marwick 2010), neither an interest in politics and/or news as found by earlier work (Hargittai & Litt 2011) nor the consumption or production of such material relates to the adoption of Twitter among a group of young adults. This may be due to the specific age range of study participants. Were we to have data on people representing a wider age range, we may have found different results about how engagement with news and political topics relates to Twitter use. Our research also contributes to the growing body of literature on the digital savvy of young Internet users (Bennett et al. 2008; Zimic 2009; Gui & Argentin 2011). Even among this diverse group of young adults, a variation in digital media experiences and Internet skill exists, which, in turn, appears to impact Twitter adoption. One significant predictor of uptake in all our models is Internet skill. Those with higher online skills are more likely to adopt Twitter. While mainstream media highlight the digital prowess of the younger generation (e.g. Henley 2010), our findings do not support assumptions about a universally Net-savvy generation (Prensky 2001).