PUBLIC MARKS with tag socialnetwork

# Not all social networks are the same.

# You cannot assume network transitivity.

# You cannot assume that properties that hold for one network apply to other networks.

When we move into any social space we have to choose which of our faces to show. At any given moment, a few of them are visible. The others are hidden, often because we think they are somehow "weird".

there was a popular blogger and he also had a Twitter account and he was complaining that his cable was out, and he was I'm going to write about this cable company, Compass and how terrible they are and its going to be the number one search result in, in search engines for year to come. And they were monitoring Twitter search for any mentions of they're brand name. And they saw that within a few minutes and they replied to him on Twitter, and they said what seems to be the problem, they were going to send a van out to your house. And they had his cable fixed in like 30 minutes, so the next day the blog post was, Compass has great customer service, and it was like a, you know a complete reversal and we were like wow, they're really smart about it,

social location games are titles which interact with your location and are sensitive to your surroundings, adapting to where you are. For example, it might mean that, if you are on a boating trip, the system will give you in-game activities that are linked to fishing or water sports.

The Big Board is a real-time collaborative environment for mapping. Users open “conference rooms” on a shared map, and join conversations in these conference rooms, much like in a regular teleconferencing application. However, instead of sharing faces and powerpoints and speech over the wire, users draw on and add content to a shared map or very large image.

More than one hundred thou­sand person­al raw data sets were crawled from the web to fill this pa­ram­e­ters with subject mat­ters. Based on the thesis that the dig­ital identity is measur­able and compa­ra­ble these data sets were vi­su­alized us­ing custom compu­tational tools.

These stud­ies were designed to under­stand the data and determine its char­ac­ter­is­tics regard­ing the construction of dig­ital identity.

Af­ter the anal­ysis phase the data was vi­su­ally abstracted and interpreted to give the disembod­ied dig­ital identity a unique and char­ac­ter­is­tic »Gestalt« in form of a generated sculp­ture.

Today almost everybody has at least one digital representation in one of the numerous social communities, like Flickr, Facebook and MySpace.

There are also no such things as “digital natives.” Just because many of today’s youth are growing up in a society dripping with technology does not mean that they inherently know how to use it. They don’t. Most of you have a better sense of how to get information from Google than the average youth. Most of you know how to navigate privacy settings of a social media tool better than the average teen. Understanding technology requires learning.

Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.

There are over 2 billion literate, mobile phone subscribers in the developing world, many living on less than $5 a day.

Corporations pay people to accomplish millions of simple text-based tasks.

txteagle enables these tasks to be completed via text message by ordinary people around the globe.

Behavioral Inference across Cultures: Using Telephones as a Cultural Lens

Eagle, N.

Intelligent Systems, IEEE

Volume 23, Issue 4, July-Aug. 2008 Page(s):62 - 64

Digital Object Identifier 10.1109/MIS.2008.58

Summary:Most people carry mobile telephones, which automatically capture behavioral data and store it in service provider databases around the world. The different types of captured data can provide insight into human cultures. Examples from various cultures and hundreds of millions of individuals illustrate how phones can serve as a cultural lens, improving our understanding of social networks, outlier events, and a culture's pace of life.

SensorPlanet is a Nokia-initiated cooperation, a global research framework, on mobile device-centric large-scale Wireless Sensor Networks.

Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.

The original Reality Mining experiment is one of the largest mobile phone projects attempted in academia. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations.