My Digital FootPrint

What do you consider personal information was the based question for research conducted by Ball State University's Center for Media Design published Feb 2011 and the reports finds that the notion of privacy is actually "situational," and depends on the context of the consumer, the nature of their information being tracked, and the organizations that are tracking it. The report is worth reading  " Notions of Privacy: Ignorance, Illusion or Miscommunication ," They have also supplied an excellent interactive infographic (main illustration) The work is very good and whilst it does lack the sense of global diversity around the world (different geographies what is personal very different), it does highlight that people have strange views about data.  Some data that people highlight as private is indeed public already and therefore the work represents the confusion between “what we would like/ believe we have as privacy and what we have in reality” Part 2 of t

Trying to determine someone level of influence is attractive for a number of reasons, not least to be able to understand how valuable you are as a multiplier in a social network. There are growing (nine as I write) significant attributes that will affect your influence. The issue is interruption of words... Authority What authority have you been given by you social graph and what authority can you command (depth) Credibility How credible are you on the topic in question, the closeness to your are of given authority Expertise Proven domain expertise from an independent third party that shows more than common knowledge or willing to stand up and be counted.  Think how others whom you are influenced by rate you Location Often overlooked but sometime meeting people helps or having someone local is a positive. Proximity Both the relationships between people and how they are connected. Closeness is more than family Reach Think about the size and potency of your "so

Trying to determine someone level of influence is attractive for a number of reasons, not least to be able to understand how valuable you are as a multiplier in a social network. There are growing (nine as I write) significant attributes that will affect your influence. The issue is interruption of words... Authority What authority have you been given by you social graph and what authority can you command (depth) Credibility How credible are you on the topic in question, the closeness to your are of given authority Expertise Proven domain expertise from an independent third party that shows more than common knowledge or willing to stand up and be counted.  Think how others whom you are influenced by rate you Location Often overlooked but sometime meeting people helps or having someone local is a positive. Proximity Both the relationships between people and how they are connected. Closeness is more than family Reach Think about the size and potency of your "so

Trying to determine someone level of influence is attractive for a number of reasons, not least to be able to understand how valuable you are as a multiplier in a social network. There are growing (nine as I write) significant attributes that will affect your influence. The issue is interruption of words... Authority What authority have you been given by you social graph and what authority can you command (depth) Credibility How credible are you on the topic in question, the closeness to your are of given authority Expertise Proven domain expertise from an independent third party that shows more than common knowledge or willing to stand up and be counted.  Think how others whom you are influenced by rate you Location Often overlooked but sometime meeting people helps or having someone local is a positive. Proximity Both the relationships between people and how they are connected. Closeness is more than family Reach Think about the size and potency of your "so

Dirty Data is a term used when referring to inaccurate information or data collected during capture.  Dirty data can be misleading, incorrect, without generalised formatting, incorrectly spelled or punctuated, entered into the wrong field or duplicated. Dirty data can be prevented using input masks or validation rules, but completely removing such data from a source can be impossible or impractical There are several causes of dirty data. In some cases, the information is deliberately distorted. A person may insert misleading or fictional personal information which appears real. Such dirty data may not be picked up by an administrator or a validation routine because it appears legitimate. Duplicate data can be caused by repeat submissions, user error or incorrect data joining. There can also be formatting issues or typographical errors. A common formatting issue is caused by variations in a user's preference for entering phone numbers. The reason for looking at this topic was

image from http://www.toothpastefordinner.com/ It may or may not be true that social media companies know more about us than our Government.  However what is known is that we are generating more data that can be tracked (aka one element of the digital footprint).  We know that value comes from how companies analyse this data and then use it to influence you in some purchase decision.  To increase the value companies are then trying to close the loop by understanding what influenced you and how you influence your social group. Johanna Blakley did an excellent TedTalk on the end of gender and how our current views of segmentation only provide a "distorted mirror of life".  In summary she says that ridged segmentation based on old school demographics is restrictive as it labels and define us assuming us all have similar behaviour, taste, likes and are predictable - based on your demographics and buckets.  This is however different to Dan Ariely views from "Predictab

Roger Grimes posted a very insightful blog about reuse of user ID and passwords, with the usual sprinkling of fairy dust and FUD to create sales for security experts, however it co-insides with Microsoft publishing some data about the reuse of passwords on different web sites and a very good research paper from INRIA in France which asked “ How unique and traceable are usernames ” Essentially can identities established on multiple web sites be linked together based on the usernames to recreate an “identity” and what are the implications for privacy?  INRIA experiment looked at over 10 million usernames from popular services such as Google and eBay. In some of the tests, Google profiles that listed multiple accounts on different web services were used to establish “ground truth” about linked usernames. The first finding was that the usernames chosen by people on the various websites tend to be very unique, with a probability of duplication being approximately one in one billion. Thi