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tsuomela : social-networks   74

PLOS ONE: Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach
"We analyzed 700 million words, phrases, and topic instances collected from the Facebook messages of 75,000 volunteers, who also took standard personality tests, and found striking variations in language with personality, gender, and age. In our open-vocabulary technique, the data itself drives a comprehensive exploration of language that distinguishes people, finding connections that are not captured with traditional closed-vocabulary word-category analyses. Our analyses shed new light on psychosocial processes yielding results that are face valid (e.g., subjects living in high elevations talk about the mountains), tie in with other research (e.g., neurotic people disproportionately use the phrase ‘sick of’ and the word ‘depressed’), suggest new hypotheses (e.g., an active life implies emotional stability), and give detailed insights (males use the possessive ‘my’ when mentioning their ‘wife’ or ‘girlfriend’ more often than females use ‘my’ with ‘husband’ or 'boyfriend’). To date, this represents the largest study, by an order of magnitude, of language and personality."
social-networks  social-media  big-data  facebook  psychology  linguistics  mood  personality  gender  language 
october 2013 by tsuomela
Zapnito - Home
"The web has become an ocean of noise. With user driven content and social networks like Facebook and YouTube, the web has become more confusing and noisy than ever intended. Companies are struggling with how to manage their content and communities. We are the inverse of noisy social networks. A platform that allows organizations with leaders and communities to develop and grow their customer base, employee engagement and build new sources of revenues."
social-networks  micronetworking  expertise  business  consulting 
september 2013 by tsuomela
[1304.3480] Friendship Paradox Redux: Your Friends Are More Interesting Than You
"Feld's friendship paradox states that "your friends have more friends than you, on average." This paradox arises because extremely popular people, despite being rare, are overrepresented when averaging over friends. Using a sample of the Twitter firehose, we confirm that the friendship paradox holds for >98% of Twitter users. Because of the directed nature of the follower graph on Twitter, we are further able to confirm more detailed forms of the friendship paradox: everyone you follow or who follows you has more friends and followers than you. This is likely caused by a correlation we demonstrate between Twitter activity, number of friends, and number of followers. In addition, we discover two new paradoxes: the virality paradox that states "your friends receive more viral content than you, on average," and the activity paradox, which states "your friends are more active than you, on average." The latter paradox is important in regulating online communication. It may result in users having difficulty maintaining optimal incoming information rates, because following additional users causes the volume of incoming tweets to increase super-linearly. While users may compensate for increased information flow by increasing their own activity, users become information overloaded when they receive more information than they are able or willing to process. We compare the average size of cascades that are sent and received by overloaded and underloaded users. And we show that overloaded users post and receive larger cascades and they are poor detector of small cascades."
social-networks  friendship  connection  community  twitter  mathematics 
april 2013 by tsuomela
Imagining Twitter as an Imagined Community
The notion of “community” has often been caught between concrete social relationships and imagined sets of people perceived to be similar. The rise of the Internet has refocused our attention on this ongoing tension. The Internet has enabled people who know each other to use social media, from e-mail to Facebook, to interact without meeting physically. Into this mix came Twitter, an asymmetric microblogging service: If you follow me, I do not have to follow you. This means that connections on Twitter depend less on in-person contact, as many users have more followers than they know. Yet there is a possibility that Twitter can form the basis of interlinked personal communities—and even of a sense of community. This analysis of one person’s Twitter network shows that it is the basis for a real community, even though Twitter was not designed to support the development of online communities. Studying Twitter is useful for understanding how people use new communication technologies to form new social connections and maintain existing ones.
twitter  social-networks  experience  imagining  community 
july 2012 by tsuomela
Identifying Influential and Susceptible Members of Social Networks
"Identifying social influence in networks is critical to understanding how behaviors spread. We present a method for identifying influence and susceptibility in networks that avoids biases in traditional estimates of social contagion by leveraging in vivo randomized experimentation. Estimation in a representative sample of 1.3 million Facebook users showed that younger users are more susceptible than older users, men are more influential than women, women influence men more than they influence other women, and married individuals are the least susceptible to influence in the decision to adopt the product we studied. Analysis of influence and susceptibility together with network structure reveals that influential individuals are less susceptible to influence than non-influential individuals and that they cluster in the network, which suggests that influential people with influential friends help spread this product."
social-networks  experiments  influence  random  statistics  models  network-analysis 
june 2012 by tsuomela
Premium Twitter Data from Gnip
Gnip has offered easy access to Twitter’s free data streams and dozens of other social media feeds since 2008. In November 2010, Gnip became the first authorized reseller of Twitter data.
twitter  social-networks  research  analytics  data-collection  data-sources 
june 2012 by tsuomela
echovar » Blog Archive » Year-End Processing: The Network as Growth Medium
"While networked computational tools can assist us in expanding the scope and breadth of the sharing we do with groups and individuals, it’s our ability to navigate the new social customs and ceremonies of the Network that will determine how far all this spreads. It’s a counter-cultural idea, instead of placing the highest value on independence and individuality, it takes us down the path of interdependence and coexistence. And this brings us back to this idea of a growth medium. As the old year ends, and the new one begins, I’m imagining an as yet unpublished Whole Earth Catalog filled with tools and perspectives on how we might grow this new crop in the fields of the Network. It’s a thing that “is” what it describes."
social-networks  social-media  business  culture  community  commons  sharing 
april 2012 by tsuomela
[1106.0296] The Emergence of Leadership in Social Networks
"We study a networked version of the minority game in which agents can choose to follow the choices made by a neighbouring agent in a social network. We show that for a wide variety of networks a leadership structure always emerges, with most agents following the choice made by a few agents. We find a suitable parameterisation which highlights the universal aspects of the behaviour and which also indicates where results depend on the type of social network. "
social-networks  networks  game-theory  leadership  agents  social-science  choice 
august 2011 by tsuomela
Why some social network services work and others don’t — Or: the case for object-centered sociality :: Zengestrom
" the term ‘social networking’ makes little sense if we leave out the objects that mediate the ties between people. Think about the object as the reason why people affiliate with each specific other and not just anyone. For instance, if the object is a job, it will connect me to one set of people whereas a date will link me to a radically different group. This is common sense but unfortunately it’s not included in the image of the network diagram that most people imagine when they hear the term ‘social network.’ The fallacy is to think that social networks are just made up of people. They’re not
social-media  social-networks  theory  objects  purpose  analysis  community  network 
april 2011 by tsuomela
Smoke Signals | the human network
When all four of these design principles are embodied in a work, another design principle emerges: resilience. Something that is distributed, transport independent, secure and open is very, very difficult to subvert, shut down, or block. It will survive all sorts of disasters. Including warfare.
design  computer  technology  freedom  open-source  privacy  transparency  social-media  graphs  social-networks  manifesto  internet  future  social  facebook  commerce 
march 2011 by tsuomela
Cormode - A manifesto for modeling and measurement in social media - First Monday - 6 September 2010
Online social networks (OSNs) have been the subject of a great deal of study in recent years. The majority of this study has used simple models, such as node–and–edge graphs, to describe the data. In this paper, we argue that such models, which necessarily limit the structures that can be described and omit temporal information, are insufficient to describe and study OSNs. Instead, we propose that a richer class of Entity Interaction Network models should be adopted. We outline a checklist of features that can help build such a model, and apply it to three popular networks (Twitter, Facebook and YouTube) to highlight important features. We also discuss important considerations for the collection, validation and sharing of OSN data.
social-networks  social-media  network-analysis  networks  research  measurement  methods  twitter  data  social  network 
october 2010 by tsuomela
Show me your friends and I will tell you what type of person you are: How one's profile, number of friends, and type of friends influence impression formation on social network sites - Utz - 2010 - Journal of Computer-Mediated Communication
This experiment examines how far extraversion of the target (self-generated information), extraversion of the target's friends (friends-generated information), and number of friends (system-generated information) influence the perceived popularity, communal orientation, and social attractiveness of the target. The warranting principle states that judgments rely more heavily on other-generated than self-generated information because the former is more immune to manipulation
social-networks  communication  peers  popularity  project(Papers) 
august 2010 by tsuomela
Econometric Measures of Systemic Risk in the Finance and Insurance Sectors
We propose several econometric measures of systemic risk to capture the interconnectedness among the monthly returns of hedge funds, banks, brokers, and insurance companies based on principal components analysis and Granger-causality tests. We find that all four sectors have become highly interrelated over the past decade, increasing the level of systemic risk in the finance and insurance industries. These measures can also identify and quantify financial crisis periods, and seem to contain predictive power for the current financial crisis. Our results suggest that hedge funds can provide early indications of market dislocation, and systemic risk arises from a complex and dynamic network of relationships among hedge funds, banks, insurance companies, and brokers.
economics  complexity  systems  risk  measurement  modeling  interconnection  social-networks  network-analysis  finance 
august 2010 by tsuomela
Researchers Identify Critical 'Bridging' Connectors in Social Networks | News | Communications of the ACM
In order to calculate an individual's bridging, the team systematically deleted each link in the network and calculated the resulting changes in network cohesion. The average change for each person's links is a measure of bridging. A person with two links to members in two different groups when no one else links the groups is a perfect bridge.
social-networks  analysis  network-analysis  community 
june 2010 by tsuomela » Consequential Strangers
If market culture sees us as a mass of disconnected individuals, each without a history or enduring affiliations, the commons sees us as interdependent social creatures. It is refreshing to see this perspective affirmed in such a rich, detailed way by a new book, Consequential Strangers: The Power of People Who Don’t Seem to Matter But Really Do (W.W. Norton), by Melina Blau and Karen L. Fingerman.
commons  social-networks  interaction  social  strangers  people  weak-ties  social-capital 
january 2010 by tsuomela
[0911.2390] How Creative Should Creators Be To Optimize the Evolution of Ideas? A Computational Model
There are both benefits and drawbacks to creativity. In a social group it is not necessary for all members to be creative to benefit from creativity; some merely imitate or enjoy the fruits of others' creative efforts. What proportion should be creative? This paper contains a very preliminary investigation of this question carried out using a computer model of cultural evolution referred to as EVOC (for EVOlution of Culture)....For all levels or creativity, the diversity of ideas in a population is positively correlated with the ratio of creative agents.
creativity  innovation  modeling  evolution  social-networks  analysis 
december 2009 by tsuomela
James Fowler
James Fowler is an Associate Professor in the Center for Wireless and Population Health Systems at CALIT2 and the Political Science Department at the University of California, San Diego.
James's work lies at the intersection of the natural and social sciences. His current interests include social networks, behavioral economics, evolutionary game theory, political participation, cooperation, and genopolitics (the study of the genetic basis of political behavior).
people  school(UCSanDiego)  research  networks  science  politics  academic  cooperation  social-networks  political-science 
september 2009 by tsuomela
Connected: The Surprising Power of Our Social Networks
Renowned scientists Christakis and Fowler present compelling evidence for our profound influence on one another's tastes, health, wealth, happiness, beliefs, even weight, as they explain how social networks form and how they operate.
book  social-networks  community  networks  popularize 
september 2009 by tsuomela
Tracing information flow on a global scale using Internet chain-letter data — PNAS
Although information, news, and opinions continuously circulate in the worldwide social network, the actual mechanics of how any single piece of information spreads on a global scale have been a mystery. Here, we trace such information-spreading processes at a person-by-person level using methods to reconstruct the propagation of massively circulated Internet chain letters. We find that rather than fanning out widely, reaching many people in very few steps according to “small-world” principles, the progress of these chain letters proceeds in a narrow but very deep tree-like pattern, continuing for several hundred steps. This suggests a new and more complex picture for the spread of information through a social network. We describe a probabilistic model based on network clustering and asynchronous response times that produces trees with this characteristic structure on social-network data.
information-cascade  information-science  information  communication  email  dissemination  viral  networks  network-analysis  ideas  rumor  internet  circulation  epidemics  diffusion  research  paper  probability  model  social-networks 
august 2009 by tsuomela
ACM Ubiquity - In Search of the Real Network Science: An Interview with David Alderson
David Alderson has become a leading advocate for formulating the foundations of network science so that its predictions can be applied to real networks. He is an assistant professor in the Operations Research Department at the Naval Postgraduate School in Monterey, Calif., where he conducts research with military officer-students on the operation, attack, and defense of network infrastructure systems. We interviewed him to find out what is going on.
interview  networks  network-analysis  science  powerlaw  mathematics  graphs  social-networks 
august 2009 by tsuomela
What is the (Next) Message?: Karen Stephenson at OCAD: Organization Beyond Social Networks
She observes – correctly, I think – that most strategic insight and initiative is limited by the fact of ego-centric networks: we know who we know, and only on a very limited basis do we indirectly know those whom our direct network knows.
network-analysis  social-networks 
april 2009 by tsuomela
Huberman, - Social Networks that matter: Twitter under the microscope
Scholars, advertisers and political activists see massive online social networks as a representation of social interactions that can be used to study the propagation of ideas, social bond dynamics and viral marketing, among others. But the linked structures of social networks do not reveal actual interactions among people. Scarcity of attention and the daily rhythms of life and work makes people default to interacting with those few that matter and that reciprocate their attention. A study of social interactions within Twitter reveals that the driver of usage is a sparse and hidden network of connections underlying the “declared” set of friends and followers.
twitter  research  social-networks  networks  behavior 
february 2009 by tsuomela
T N T — The Network Thinker: So many people, So little time
So, if many of the social circles above are already interconnected do I have follow an individual in each social circle/community on Twitter? Probably not. The trick is to find the people that reach many social circles and follow them. Of course, we need to find more than the minimum of people to follow -- you want some redundancy in your network so that there are multiple paths to places of interest for you. Finding these key nodes is what social network analysis is all about.
twitter  social-networks  community 
january 2009 by tsuomela
Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study -- Fowler and Christakis 337: a2338 -- BMJ
Objectives To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks.

Design Longitudinal social network analysis.

Setting Framingham Heart Study social network.

Participants 4739 individuals followed from 1983 to 2003.

Main outcome measures Happiness measured with validated four item scale
happiness  network  social-psychology  social-networks  research  longitudinal  psychology  diffusion  emotion 
december 2008 by tsuomela
Diversity in open social networks
Online communities have become become a crucial ingredient of e-business. Supporting open social networks builds strong brands and provides lasting value to the consumer. One function of the community is to recommend new products and services. Open social networks tend to be resilient, adaptive, and broad, but simplistic recommender systems can be 'gamed' by members seeking to promote certain products or services. We argue that the gaming is not the failure of the open social network, but rather of the function used by the recommender. To increase the quality and resilience of recommender systems, and provide the user with genuine and novel discoveries, we have to foster diversity, instead of closing down the social networks. Fortunately, software increases the broadcast capacity of each individual, making dense open social networks possible. Numerically, we show that dense social networks encourage diversity. In business terms, dense social networks support a long tail.
social-networks  diversity  business 
october 2008 by tsuomela
Social networking -
In Evaluating social networking services, this report then describes how to use a toolkit – a social networking evaluation chart covering six different social networking services, and an accompanying checklist, which are available to download from the D
social-networks  research  policies  youth 
june 2008 by tsuomela

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