social networks

Analysis: Product Push Vs. People Pull Model

Piyush Gupta — Mon, 21 Jul 2008 01:31:04 -0700

Description

Internet is the sea of information and the information access model has shown a paradigm shift to result in bigger successes in the recent few years.

Observation 1: PRODUCT PUSH
There are just about a million CMS applications that rule the Internet today. 99% of the people follow blogs today. Suprised?
99% people do the search for information and there's hardly any topic which is not talked about on Blogs, therefore, blogs are one of the ubiquitous source of opiniontated information. Let's look at the model the Blogs follow:
i. Subscribe to a blog feed.
ii. You are now at the receiving end.
Information will now keep getting pushed to you. Some of it would be of your interest and some not but still all this information is being pushed to you. TC, F|R, GOM, Pluggd.in, Slashdot, Webyantra etc. are the few ones I follow. Almost all these platform talks about iPhone, gPhone, XBox, startups, products, corporate politics, innovation etc. These are the platforms which have Products in the mainstream.

Observation 2: PEOPLE PULL
And there are platforms which have People in the mainstream, The Social Networks e.g. Professional (linkedIn) and Casual (Facebook, Orkut). The current scenario looks something like this:
i. I join
ii. I connect
iii. I share (days or weeks or months)
iv. I keep lying in the connections list of several hundreds of people (A good looking Island)
v. I become the target for the Online Marketeers of various consultants/ companies.

Should I want to know more about people of some particular kind or with some common interests. I have to search and find more about them, thus, pulling the information. Social Networks have now evolved as an unorganized encyclopedia. A couple of years hence the problem would be as big as we have with the Internet today.

THINK ABOUT IT
Is there any bigger art in this world than the art of learning to deal with people?
Is there a bigger bet in this world than the people itself?
Is there any bigger constant craving than to know more about people in whole of your life?
Are products or the people the target for most of the controversies globally?

If the answers to any one of them favors People, then,
i. How many platforms have you seen which talk about people as the Subject and not the Predicate?
ii. How many platforms you know talk about people and work on the Push model?

Observation 3: WHY DID BLOGS SCORE HIGH OVER WEBSITES?
Both Blogs and Websites have two fundamental components i.e. the URL & the Content. Fundamentals that bring the biggest differentiation in them are:
i. The URL of a Blog refers to a person, Website URL to a non living thing.
ii. The Content in the Blogs follows a Push model, Website content showcases Pull Model.

Blogs attempted to bring People at the front as a Subject, the content is the trail of these people. Most of the personal blogs that we follow may not impart that valuable an information but we read them to read the mind of that person (because we want to keep knowing about this person or we have an interest in knowing people in general).

Observation 4: WHAT ABOUT TWITTER?
For a minute let's evaluate what model does Television follow:
i. One Personal TV Box.
ii. Several Channels to follow.
iii. Several Programs on a single Channel.
iv. Freedom to follow any channel.

Television lacked two features however:
1. Two way communication - We can't immediately respond to a channel that we follow.
2. High Barrier to Entry to start you own Channel.

What Did Twitter do?
1. One Personal Account.
2. Every Account is a channel.
3. Every tweet is the program - The life-cycle of this program is too short (140 characters).
4. Freedom to follow any Account.
5. Instant response mechanism to the channel you follow.
6. Soon as you join, you become a channel yourself.

THINK ABOUT IT
While twitter is not about any technology, product, startup etc. It is just about people, talks only about people and let only people speak (irrespective of what hat do they wear). Essentially People are the subject and their profiles are the predicate.

Had twitter been this big a success if Blogs weren't there before?

Observation 6: Putting Observations 1 and 2 together - There is a huge need for the Push platform centered around People.
Observation 7: Putting Observations 3 and 4 together - There are certain things that succeed following the success of a parent Idea. Looking at Product Push platform immense success, it's time for the People Push platform to emerge.

CONCLUSION
Manpower, Co-founders, Senior Management, like minded relationships are the buzzwords of today. There is a dearth of platforms which talks about people as a subject and controlled by a trusted entity and follow the Push model. Perhaps Social Networks demand a fundamental change in the design and need to incorporate Push model to them.

Source

Self

Social Information Processing

Matt Daniels — Mon, 28 Apr 2008 17:33:19 -0700

Description

Social Information Processing:

The label “social media” has been attached to a quickly growing number of web sites, such as blogs, wikis, Flickr, and Del.icio.us, whose content is primarily user-driven. In the process of using social media sites, users are generating content and adding metadata in the form of (1) tags: content annotations using freely-chosen keywords; (2) ratings: passive or active evaluation of content; and (3) social networks: where users designate others as friends so as to track their activities. The connections between content, users and metadata create layers of rich interlinked data that is revolutionizing information processing by facilitating new methods of interacting with information. We call this "social information processing." Social information processing allows users to collaborate implicitly (or explicitly) by leveraging the opinions and knowledge of others to solve problems such as information management, discovery, and personalization. In addition to improving individual user experience, social information processing may lead to new solutions to collective problems, such as ensuring fairness, managing common resources, etc. Another exciting possibility is that wholly new kinds of knowledge will emerge from the distributed activities of many users.

Source

http://www.aaai.org/Symposia/Spring/sss08symposia.php#ss06

Radar Networks: Twine

Matt Daniels — Mon, 28 Apr 2008 17:04:07 -0700

Description

Twine is a new network that helps users organize, share and discover information around their particular interests.

Radar Networks is pioneering the mainstream adoption of the Semantic Web, or what is sometimes called "Web 3.0." The company was founded by Web visionary, Nova Spivack and has attracted an all-star team of industry veterans. Headquartered in San Francisco, the company is funded by leading investors including Velocity Interactive Group, Draper Fisher Jurvetson, Vulcan Capital and Leapfrog Ventures.

Source

http://www.radarnetworks.com/

Interdisciplinary Research in Natural and Social Sciences

Sabine Hossenfelder — Sat, 22 Mar 2008 07:32:22 -0700

Description

"[I]ngenuity comes in two distinct kinds: the kind used to create new technologies [...] and the more crucial kind used to reform old institutions and social arrangements and build new ones [...] I call these two kinds technical and social ingenuity. [O]ur supply of ingenuity [...] involves both the generation of good ideas and their implementation within the society. It's not enough for a scientist, community or society simply to think up an idea [...] the idea must also be put into practice. [M]any of the critical obstacles occur not when ingenuity is generated, but when people try to implement new ideas."
~Thomas Homer-Dixon, The Ingenuity Gap, Knopf (2001) p. 22/23

The complexity of our social networks and the tasks that we have to deal with is constantly increasing. The question how we organize and manage our societies is becoming more crucial with every passing year. Politicians, economists, and demographists are faced with incredibly involved relations that are growing over their heads, questions for whose answer they have insufficient or no reliable scientific basis.

It is not surprising that in this context the question of efficient organizational management, as well as sociology and psychology receives an still increasing amount of interest from company leaders as well as governments. Many of the present studies lack a thorough model building approach, and - more importantly - lack applications of these insights. It can be seen though that governments are willing to export expert questions (i.e. environmental impact or about which regulation would have what effect) to specialists. This trend has already been there in economy (econophysics) for some while and it is likely to spread out once the understanding of model building for very complex systems is sufficiently advanced. (For a brief introduction, see e.g. Complex Adaptive Systems: An Introduction to Computational Models of Social Life, John H. Miller and Scott E. Page, Princeton University Press (2007))

I think that the area at the intersection of mathematics/theoretical physics on the one hand and sociology/politics on the other hand will become increasingly more important and better funded once people realize the importance of these studies, especially in the area of the science of networks and complex adaptive systems.

Source

Reality Mining

Alex Soojung-Kim Pang — Mon, 03 Mar 2008 12:24:12 -0800

Description

Technology Review declares reality mining one of its top 10 ideas for 2008.

Every time you use your cell phone, you leave behind a few bits of information. The phone pings the nearest cell-phone towers, revealing its location. Your service provider records the duration of your call and the number dialed.

Some people are nervous about trailing digital bread crumbs behind them. Sandy Pentland, however, revels in it. In fact, the MIT professor of media arts and sciences would like to see phones collect even more information about their users, recording everything from their physical activity to their conversational cadences. With the aid of some algorithms, he posits, that information could help us identify things to do or new people to meet. It could also make devices easier to use--for instance, by automatically determining security settings. More significant, cell-phone data could shed light on workplace dynamics and on the well-being of communities. It could even help project the course of disease outbreaks and provide clues about individuals' health. Pentland, who has been sifting data gleaned from mobile devices for a decade, calls the practice "reality mining."

Why does this matter?

Personal reality mining infers human relationships and behavior by applying data-mining algorithms to information collected by cell-phone sensors that can measure location, physical activity, and more.... Cell phones are now sophisticated enough to collect and analyze data on personal behavior, and researchers are developing techniques that allow them to effectively sort through such information.

Impact: Models generated by analyzing data from both individuals and groups could enable automated security settings, smart personal assistants, and monitoring of personal and community health.

Context:

Source

http://www.technologyreview.com/read_article.aspx?ch=specialsections&sc=emerging08&id=20247&a=

Social network studies will move from sociology to online interactions and contagion

Peter Levin — Tue, 04 Dec 2007 06:37:07 -0800

Description

Sociology seems to be unable to capitalize on the recent explosion of interest in social networks. Economic sociology has embraced networks since the early 1980s, with Harrison White 1981 article 'Where do Markets Come from?' arguing that "markets are self-reproducing social structures among specific cliques of firms and other actors who evolve roles from observations of each other's behavior" (518).

But more recently, the emergence of quantitative technologies and large network data sets has pushed social networks further. Duncan Watts has been central in this effort, with his work on Small World networks - where properties of real-world networks can be embodied by relatively simple mathematical models interpolating between order and randomness. Measures for density, randomness, and separation (the shortest path length between nodes) can all be determined for a surprisingly wide range of real-world networks.

Much of this work has migrated from sociology to physics, and from there to studies of disease spreading, power line transmissions, and internet web usage. This work is rather alarming, for instance, that we could expect that 'random shortcuts' in networks would result in more dangerous human-to-human diseases.

As network scholars have turned to 'idea contagion', the findings are more interesting. Unlike diseases, ideas are not memory-free processes - if you are exposed to the same idea twice, it has a cumulative effect. So instead of a linear probability of infection, there is a threshold model of infection. Fads, rumors, ideas, are likely to exhibit 'all of a sudden' effects. Here, the social network literature provides the scientific basis for Tipping Points arguments.

Practically, network studies are most likely to have impacts in disease and online environments. Contagion has been embraced as a model for understanding disease, and it is not surpising to find it there. But the growth of social networks in online spaces, and the interests and monetization of online search provide fertile ground for networks. Watts himself has begun working for Yahoo to improve their social networking applications, along with a number of his students.

Reality Mining at MIT's Media lab provides another place where network studies will continue to take shape and influence online interaction. Drawing on data culled from the so-called 'soft' signals of social interaction (voice inflection, conversation browsing at a conference), researchers have proposed social interactional data as a source for mining the 'new rules of social interaction'. The breakthrough aim is to provide more contextual interpretation for non-face-to-face-interactions. The implications for 'improving' online interaction 10-20% or more (as claims Alex (Sandy) Pentland, would possibly be a fairly dramatic increase in adoption of online interactions, especially in business.

Boots, Michael and Akira Sasaki. 1999. 'Small worlds' and the Evolution of Virulence: Infection Occurs Locally and at a Distance. Proceedings of the Royal Society Series B 266: 1933-1938.

Watts, Duncan. 2003. Six Degrees: The Science of a Connected Age. NY: Norton

Watts, Duncan. 2004. The 'New' Science of Networks. Annual Review of Sociology 30: 243-270.

Watts' Small World site

White, Harrison. 1981. Where do Markets Come From? American Journal of Sociology 87(3): 517-547.

Signals

Reality Mining

Social networks constructed by blog and SMS in China

Post-semantic web enhances society and the meaning of data

David Gutelius — Sat, 24 Nov 2007 16:57:31 -0800

Description

In 1999, Tim Berners-Lee first described the semantic web in this way: " I have a dream for the Web [in which computers] become capable of analyzing all the data on the Web – the content, links, and transactions between people and computers. A ‘Semantic Web’, which should make this possible, has yet to emerge, but when it does, the day-to-day mechanisms of trade, bureaucracy and our daily lives will be handled by machines talking to machines. The ‘intelligent agents’ people have touted for ages will finally materialize."

Since that time, there has been significant progress towards making such an idea reality (note Radar Networks' Twine, or Metaweb's Freebase). It has also become more tightly constrained and defined (e.g. Wikipedia's current definition: "The Semantic Web is an evolving extension of the World Wide Web in which web content can be expressed not only in natural language, but also in a format that can be read and used by software agents, thus permitting them to find, share and integrate information more easily.").

Going beyond RDF-related technologies OWL and other ontology frameworks, however, we may be approaching a post-semantic web phase of development of the Internet. It's not that the "semantic web" as Tim B-L dreamed it or Wikipedia defines has really fully appeared. In fact, I have a suspicion that in either case, it may never appear and function the way its proponents envision. For one, there is still deep disagreement over standards - for all its Sematicness, the community can't even agree on the semantics!

By post-semantic web, I do not mean that it has become irrelevant - but it is beginning to show signs of turning out far differently than anyone could have imagined.

We are now seeing advanced machine learning combined with natural language processing, social graph analysis, and data mining techniques that half a decade ago few could have imagined. These technologies are being put to use by incredibly powerful compute resources (particularly those in mesh or p2p networks) to pick up and analyze a tremendous array of "signals". By signals, I mean not just those most in vogue in "web 2.0" like tags or networks of friends, although these are new and valuable sources for machines to learn to serve people more effectively. I also mean "digital gestures" - small signals that convey meaning to others but differently than "natural language" typically conveys; examples might include symbology or avatars. We are becoming more expressive digitally, and we are now just beginning to be able to also harvest these expressions and have machines learn from them in order to adapt to us.

The artificial intelligence field has for many years been fascinated with the idea of autonomous agents - semi-stupid digital servants that can act on our behalf under certain circumstances. The recent push into probabilistic reasoning and advances in a particular subfield of AI called machine learning (a characteristically poor name for a field of inquiry, but oh well) has begun to produce something better than semi-stupid in terms of serving us users.

The promise of a post-semantic web goes beyond just a language and representation framework (the techno-wonk vision of the semantic web) or a series of agents that do things for people. It's really a combination of 1) the power of distributed computing, 2) the growing expressivity of digital life and the signals such a life leaves behind, and 3) a way for software to learn and adapt itself to serve users and the human communities that they belong to, better. The implications for such powerful applications are not that they necessarily do things for us (although that would be a useful side effect), but rather give us new cognitive, and perhaps social, capabilities that let us do what we humans already do - just more and better.

AAAI Symposium on Social Information Processing - http://www.aaai.org/Symposia/Spring/sss08symposia.php#ss06

iLink KDD - http://www.ai.sri.com/pub_list/1523

Radar Networks' Twine: http://www.radarnetworks.com/

Metaweb - http://www.metaweb.com/

Signals

Radar Networks: Twine

Machine-to-Machine Intelligence (m2mi) Corporation

Social Information Processing

Web companies race to social and open information streams

Mike Love — Tue, 30 Oct 2007 14:05:30 -0700

Description

Many large web companies are racing towards a similar goal: owning people's online attention streams by providing the most benefit to those that use their services. For an example of this direction of new products, a San Francisco company, Radar Networks, recently unveiled a new service at the Web 2.0 Summit, Twine, which will assimilate and make sense of the information in users' lives if they feed it with bookmarks and the content of emails.

At the same time, we can see a push towards letting users choose if they want to open their digital identity and network. A new initiative from Google will add a social component to more of their services. Similar to Facebook, it looks like Google will open up a new set of APIs to let developers access the services.

Some details about Maka-Maka have already leaked out, particularly how Google plans to use the feed engine that powers Google Reader (known internally as Reactor) to create “activity streams” for other applications akin to Facebook’s news and mini feeds.

Google is planning to “out open” Facebook with a new set of APIs that developers can use to build apps for its social network Orkut, iGoogle, and eventually other applications as well.

A New York Times article describes Google, Myspace, LinkedIn and some of the most popular social networking sites convening on a commons standard for social network developers, OpenSocial:

MySpace and Bebo, two of the world’s largest social networking sites, on Thursday joined a Google-led alliance that is promoting a common set of standards for software developers to write programs for social networks....

The open standards could create a boom of innovation around social networks as applications reach more users than ever and encourage developers to create more Internet tools.

Data mining on a large scale has been common practice for companies and the government for years now, but these new ambitious data aggregation and data mining projects will potentially open their results to the public. At the least, each individual user will be benefitted with better recommendations by the addition of data by others.

Radar Networks: Twine http://www.twine.com/
Google's Response to Facebook http://www.techcrunch.com/2007/10/29/googles-response-to-facebook-maka-maka/
MySpace Joins Google Alliance
http://www.nytimes.com/2007/11/02/technology/02google.html?_r=2&oref=slogin&oref=slogin
Plaxo: More on social network portability http://blog.plaxo.com/archives/2007/08/more_on_social.html
Twine, Freebase and Powerset http://mikelove.wordpress.com/2007/10/21/twine-freebase-and-powerset/

Signals

New Technologies for Cooperation

Alex Soojung-Kim Pang — Tue, 23 Oct 2007 11:10:30 -0700

Description

New technologies for cooperation and a better understanding of cooperative strategies may create a new capacity for rapid, ad hoc, and distributed decision making.

Within 10 years, a range of nascent technologies and practices may come together in a way that enhances our ability to cooperate in both established and ad hoc groups. Examples of these tools for collective action include:

Self-organization mesh networks, which support new ways of creating and managing stocks and flows of information
Community computing grids, which model efficient use of resources and solve complex problems
Peer production networks, which provide a framework for rapid problem solving
Social mobile computing, which builds contextual understanding of problems and dilemmas and fosters trust and group identity in ad hoc situations
Social software, which builds trusted networks and networked knowledge bases to enhance sense making, trust, and emergent leadership
Social accounting methods, which take advantage of rating, ranking, and referral mechanisms to build trust and provide important management and control levers for leaders
Knowledge collectives, which demonstrate structures, rules and practices for managing knowledge as a collectively created common-pool resource

These new technological tools could support the emergence of new markets and spaces for creation of economic value by helping to overcome classic social and psychological obstacles to cooperative action. This could potentially lead to the emergence of new capitalist structures, akin to the development of limited-liability corporations during the early days of capitalism. By eliminating middlemen, and placing creative power in hands of consumers, these tools could facilitate new kinds of trade and commerce."

This will be enabled by:

Increasing broadband penetration
Development of advanced mobile devices and wireless data networks
Continuing development of software agents

Early indicators include:

The advent and rapid spread of wikis and blogs
Appropriation of art and media through mash-ups and remixing
Formation of clans in massively multiplayer online games

What to watch:

The first Nobel prize in economics is awarded for the study of cooperation in the (online) economy.
Fraud levels approach zero in trust-based online trading spaces.
New intellectual property regimes based on distributed co-creation gain traction.