Disqus analyzed 500,000 comments made via their platform and found (shocker) that digital citizens using fictitious names (pseudonyms and persona), are actually responsible for the highest quantity and quality of comments on the web. They determined that 61 percent of its commenter's use pseudonyms, 35 percent remain anonymous and just 4 percent log in with Facebook to comment with their real identity.

“The average commenter using a pseudonym contributed 6.5 times more than anonymous commenters and 4.7 times more than commenters identifying with Facebook,”

These partially veiled commenters are also soliciting more “likes” and replies — positive quality signals, according to Disqus — than their anonymous and real name counterparts. Sixty-one percent of comments made by people using pseudonyms showed positive quality signals, while 51 percent of comments from those using their real names and 34 percent from the anonymous types possessed positive quality signals.

And what is the implication?

Google/ Twitter and Facebook centre on "identity" or at least an ability to track and Disqus thrives on comments. Disqus’ wants to show users will leave better comments when they can choose how they want to represent themselves.  Next round to the identity boys.....

A recent HBR paper What's Your Influencing Style? by Chris Musselwhite president and CEO of Discovery Learning Inc. and Tammie Plouffe is the managing partner of Innovative Pathways.

In this digital word as we search for influencers - what type is the most effect and what is the signal we are looking for?

Effective leadership today relies more than ever on influencing others — impacting their ideas, opinions, and actions.  From their research, they have a list of  five distinct influencing styles: rationalizing, asserting, negotiating, inspiring, and bridging.

• Rationalizing: Do you use logic, facts, and reasoning to present your ideas? Do you leverage your facts, logic, expertise, and experience to persuade others?
• Asserting: Do you rely on your personal confidence, rules, law, and authority to influence others? Do you insist that your ideas are heard and considered, even when others disagree? Do you challenge the ideas of others when they don't agree with yours? Do you debate with or pressure others to get them to see your point of view?
• Negotiating: Do you look for compromises and make concessions in order to reach an outcome that satisfies your greater interest? Do you make tradeoffs and exchanges in order to meet your larger interests? If necessary, will you delay the discussion until a more opportune time?
• Inspiring: Do you encourage others toward your position by communicating a sense of shared mission and exciting possibility? Do you use inspirational appeals, stories, and metaphors to encourage a shared sense of purpose?
• Bridging: Do you attempt to influence outcomes by uniting or connecting with others? Do you rely on reciprocity, engaging superior support, consultation, building coalitions, and using personal relationships to get people to agree with your position?

So now you know your style (could be corporate) do you think how your style will be received by someone else and how can you adjust your style to align with their model.....and make it more effective - signal given, signal received, transmission modified....closing the loop!

The Journey To Big Data Analytics - so here http://chucksblog.emc.com/chucks_blog/2012/01/the-journey-to-big-data-analytics.html is a blog from Chuck Hollis

VP, Global Marketing CTO EMC Corporation.  It is kind of interesting that they look at gathering data, storing data, analysing data and creating value aka the Digital Footprint business model - however they don't close the loop and complete the story.  They don't look into how to build it as a business for yourself and not them.  Great at selling a solution to the point where is has value for someone else but no growth for you.....  However it does put together the story, data scientist and what data if you need some back group.

Elizabeth Churchill is the a Principal Research Scientist at Yahoo! Research, was the speaker at the October 2011 Creative Mornings event in San Francisco.

In her talk she discussed how we hide, reveal and misinterpret emotion online and off.

<p>2011/10 Elizabeth Churchill | Emotion from San Francisco Creative Mornings on Vimeo.</p>

image source : http://www.datagovernance.com/ - download the framework from http://www.datagovernance.com/dgi_framework.pdf or http://www.datagovernance.com/11x17_DGI_framework_poster_color.pdf

Data governance is not fully defined and should be seen as an emerging discipline with an evolving definition. The discipline embodies a convergence of data quality, data management, data policies, business process management, and risk management surrounding the handling of data in an organization. Through data governance, organizations are looking to exercise positive control over the processes and methods used by their data stewards and data custodians to handle data.

Data governance is at best a set of processes that ensures that important data assets are formally managed throughout the enterprise, ensures that data can be trusted and that people can be made accountable for any adverse event that happens because of low data quality. It is all about putting people in charge of fixing and preventing issues with data so that the enterprise can become more efficient.

http://futureoffacebook.com/ Facebook is a social phenomenon that’s sweeping the globe, enabling people to connect across geographic and cultural boundaries, share information, and build meaning and value together in new ways. What are the implications of a technology relentlessly embedding itself into our everyday social fabric?

Contributors include Kevin Kelly (What Technology Wants, founder Wired), David Kirkpatrick (author The Facebook Effect), Howard Rheingold (author Smart Mobs), Nova Spivack (web innovator, co-founder Bottlenose), futurist Jamais Cascio, Doug Rushkoff (author Program or Be Programmed), Doc Searls (Berkman Center, author The Cluetrain Manifesto), social network research pioneer Valdis Krebs, cyborg anthropologist Amber Case, web anthropologist Stowe Boyd, innovation strategist Chris Arkenberg, Suzanne Fischer (curator Henry Ford Museum).

Original article is on Read/Write Web http://www.readwriteweb.com/archives/study_why_do_people_use_facebook.php

A new study entitled "Why do people use Facebook?" from Boston University's Ashwini Nadkarni and Stefan G. Hofmann proposes that the social network meets two primary human needs: (1) the need to belong and (2) the need for self-presentation. The study also acknowledges demographic and cultural factors as they relate to the belonging need, and the variation of personality types on Facebook usage.

Comment : Neither of these are new or revolutionary and continue to show that our digital self is just us – warts and all

Abstract

The social networking site, Facebook, has gained an enormous amount of popularity. In this article, we review the literature on the factors contributing to Facebook use. We propose a model suggesting that Facebook use is motivated by two primary needs: (1) the need to belong and (2) the need for self-presentation. Demographic and cultural factors contribute to the need to belong, whereas neuroticism, narcissism, shyness, self-esteem and self-worth contribute to the need for self-presentation. Areas for future research are discussed.

Guilt through association is a well written about topic and there are well published errors in analysis that have caused many outcomes to be misguided.  danah boyd wrote an article here on “Guilt through algorithmic association”  It is well worth reading and which picks up on several blogs on My Digital Footprint

When Big Data says "Happy Christmas", what is the sentiment?

Google changes the algorithm; nothing new but what about the bias of coders?

It is well reasoned (opens a debate) with some great comments, the critical point here is how does the fact become fact, is it content or is it because we searched for it.  Content is a source and can be tracked (or should be) this is why pagerank works: Authority.  However, as we give way to “search terms” as a source we are in danger of rumour, gossip and prejudice becoming fact based on an algorithm.

Algorithms can be gammed for benefit aka “Google Bombing” so the question becomes do people actually react to the instant search results and what is the level of influence.  

The next question is how does it become infectious and does an example of Google instant search need a higher level of crowd control….

On SSRN: The PII Problem: Privacy and a New Concept of Personally Identifiable Information

by Paul Schwartz University of California, Berkeley – School of Law, and Daniel Solove, George Washington University Law School

Abstract: Personally identifiable information (PII) is one of the most central concepts in information privacy regulation. The scope of privacy laws typically turns on whether PII is involved. The basic assumption behind the applicable laws is that if PII is not involved, then there can be no privacy harm. At the same time, there is no uniform definition of PII in information privacy law.

Moreover, computer science has shown that in many circumstances non-PII can be linked to individuals, and that de-identified data can be re-identified. PII and non-PII are thus not immutable categories, and there is a risk that information deemed non-PII at one time can be transformed into PII at a later juncture. Due to the malleable nature of what constitutes PII, some commentators have even suggested that PII be abandoned as the mechanism by which to define the boundaries of privacy law.

In this Article, we argue that although the current approaches to PII are flawed, the concept of PII should not be abandoned. We develop a new approach called “PII 2.0,” which accounts for PII’s malleability. Based upon a standard rather than a rule, PII 2.0 utilizes a continuum of risk of identification. PII 2.0 regulates information that relates to either an “identified” or “identifiable” individual, and it establishes different requirements for each category. To illustrate this theory, we use the example of regulating behavioral marketing to adults and children. We show how existing approaches to PII impede the effective regulation of behavioral marketing, and how PII 2.0 would resolve these problems.

full text of the article, The PII Problem: Privacy and a New Concept of Personally Identifiable Information by Paul Schwartz, Daniel Solove :: SSRN.