Chill Your Viper

 Posted by at 7:00 am  Featured, Social Media, Web Technology  Comments Off
Feb 272012
 

Chill your viper

viper 

It is surprising how many corporations have archaic, tedious, annoying, time consuming and self-defeating fulfilment processes for free content (white papers, brochures, technical specs etc.)distribution. This is bizarre. Yes, they collect emails (some fake) and other personal detritus, but is this really the smartest way to distribute free content?

I prefer models such as Cloud:flood by ViperChill. To paraphrase: 

    1. Create a free product you want to give away to your website visitors. It could be an eBook on your chosen topic, an MP3 or even a Zip file full of PSD’s.
    2. Make a button, linking to the file you want to give away, and a page to promote.
    3. Place this button next to the freebie on the site. Site visitors see the freebie, and are asked to Tweet or Facebook share the link. Once they do, they are automatically given the freebie.

This is a nice ‘nudge’ – i.e. ‘pay’ for the freebie with a Tweet or share. This clearly drives viral marketing.

Very basic ‘social network analysis’ will pull back salient details of the Tweeter, allowing for light touch ‘intelligence gathering’. The benefit is the process is very much simplified and builds in a viral marketing step.

Please rethink those dated barriers, which are needlessly placed in the way of free content distribution.

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Feb 122012
 

Figure 1 – Conceptualisation – Pulling it all together

[Source: Steve Nimmons]

friends

If you’ve not yet seen this video from Friends School in Lisburn (FSL), take 8 minutes or so and peruse now.

It could be argued that such ventures are highly indulgent, but I find this interesting, and depict above why this has real merit:

  1. The concept / vision needs to be defined, articulated and agreed across multiple stakeholder groups (a great life lesson)
  2. Selling the concept to over 1,000 students and staff is non-trivial (stakeholder communications and evangelism in action), as well as dealing with trust and reputation protection complexities (particularly at the governance levels of the school)
  3. Planning, scripting, rehearsals, casting and dealing with associated tensions is challenging
  4. Choreography and co-ordination – many businesses dream of collaboration at this level, few achieve it
  5. Execution of the vision (direction, collaboration, mechanics of filming and arrangement), copyright restrictions etc.
  6. Editing and post-production – skills learned in packaging and streamlining the end product
  7. Viral marketing and exploitation of multiple distribution channels. Is this now an entirely ‘natural ability’ of the Web Native?
  8. Analysis of the results of viral marketing and sentiment (positive, negative and neutral feedback) – exposure to the realities of tough and cynical audiences/markets

The video is only a few weeks old, but what is its ‘legacy’?

  • Will the school repeat this exercise (periodically) to refresh the concept and participation?
  • Has there been an increase in collaboration in other areas?
  • Has there been an increase in ‘school pride’ / morale?
  • Has there been any disaffection / fall-out?
  • How will the management/governance functions of the school measure benefit, risk and ‘return on investment’?

My view: Kudos to Friends School. The greatest gift of education is teaching people to think. Cynics come and cynics go, “speaking of Michelangelo.”

The Official FSL LipDub Video

[source: YouTube]

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Figure 1: A (simplified) Big Data Ecosystem

[source: Steve Nimmons]

bigdataecosystem

 

In terms of ‘forces’ affecting the CIO Agenda, Information Strategy and Enterprise Architecture, Big Data is increasingly important. This is due to explosive growth in number of data source types: applications, digital media, mobiles, users, customers, unstructured data sets, sensors, emails, blogs etc. Data is complex and in mixed formats (text, video, audio), on-demand infrastructure scalability (including massively scalable storage) is needed to deliver Big Data capabilities, as are robust analytics and visualisation tools and techniques for distributed, parallel systems. Increasing bandwidth availability has also led to exponential data growth rates and capabilities e.g. social networks, video and microblogging.

Where do you start in formulating a reference architecture for Big Data and sourcing suppliers for a Big Data ecosystem?

Should you believe the Hype?

The Gartner Hype Cycle places Big Data on ‘the upslope’ towards the ‘peak of inflated expectations’. Big Data is of course already underpinning many of the web giant’s architectures (typically because necessity has been the mother of invention).

Figure 2: Gartner Hype Cycle for Emerging Tech (2011)

[Source: Gartner]

image

  • Facebook uses Hadoop to store copies of internal log and dimension data sources and as a source for reporting/analytics and machine learning. There are two clusters, a 1100-machine cluster with 8800 cores and about 12 PB raw storage and a a 300-machine cluster with 2400 cores and about 3 PB raw storage.
  • Yahoo! deploys more than 100,000 CPUs in > 40,000 computers running Hadoop. The biggest cluster has 4500 nodes (2*4cpu boxes w 4*1TB disk & 16GB RAM). This is used to support research for Ad Systems and Web Search and to do scaling tests to support development of Hadoop on larger clusters
  • eBay uses a 532 nodes cluster (8 * 532 cores, 5.3PB), Java MapReduce, Pig, Hive and HBase
  • Twitter uses Hadoop to store and process tweets, log files, and other data generated across Twitter. They use Cloudera’s CDH2 distribution of Hadoop. They use both Scala and Java to access Hadoop’s MapReduce APIs as well as Pig, Avro, Hive, and Cassandra.

Other Hadoop users include:  1&1, A9.com, About.com, Amazon.com, American Airlines, AOL, Apple, Booz Allen Hamilton, Cerner, ChaCha, comScore, EHarmony, Federal Reserve Board of Governors, foursquare, Fox Interactive Media, Freebase, Hewlett-Packard, IBM, InMobi, ImageShack, ISI, Joost, Last.fm, LinkedIn, Microsoft, Meebo, Mendeley, Metaweb, Netflix, The New York Times, Ning, Outbrain, Playdom (now part of Disney Interactive Media Group), Powerset (now part of Microsoft), Rackspace, Razorfish, StumbleUpon and Twitter.

Hadoop Overview

Figure 3: Hadoop Overview

[source: Steve Nimmons]

hadoop

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

Hadoop has Commons, MapReduce and Distributed File System capabilities (HDFS) as well as sub-projects: HBase, Cassandra, Avro, Hive, Mahout, Pig, ZooKeeper and Chukwa.

Given the pervasive nature of Hadoop, this is a strong contender for any Big Data implementation. HBase is the Hadoop database. Cassandra is also a NoSQL database. Mahout is a data mining and machine learning component, Hive and Pig are querying components, Zookeeper a coordination component.

Hadoop Distributions, such as that from Cloudera, bundle Apache Hadoop with other Open Source tools to create a more feature rich ‘platform’. The Cloudera distribution is definitely one to evaluate.

A simple Reference Model

In terms of implementing ‘Big Data’ architectures there are a number of choices, particularly in the visualisation and analytics space (refer to Figure 1). A simplified reference model is provided in Table 1. This will be expanded in a series of future posts on architectures for Big Data, exploring key features and design trade-offs.

Table 1: Simplified Big Data Reference Model

[source: Steve Nimmons]

Function

Candidate Options

Storage NoSQL Databases – e.g. Cassandra, HBase, Voldemort, Membase
Processing MapReduce
Query Hive, Pig (assuming Hadoop is being used)
Analytics & Visualisation Refer Figure 1 (and Mahout for Data Mining)

Data Loaders (e.g. Sqoop) and log management (e.g. Flume, Scribe) could also be included in the reference model / ecosystem.

Further Reading and Interesting Tools

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organisationsdonttweet

Practical advice for managers on how the Web and social media can help them to do their jobs better

[source: Amazon]

I first heard Euan Semple speak about Social Media at a BCS (British Computer Society) ELITE event at BT Tower (in London) back in 2008. What differentiated him from others writing and speaking about the subject?

  • Experience: he has a very credible background in collaboration and communications, formerly at the BBC and latterly as an ‘independent consultant’ with blue chips and niche players.
  • Hype realism: a recognition of the need to drive real value from social media, delivering business outcomes, not ‘digital noise’.
  • Adoption complexity: it takes ‘10 seconds’ to sign up on Twitter, and less again to start using it in an ineffective and potentially damaging way. Forces such as consumerisation and social web have created mind shifts in business. Euan sets out simple, effective, engaging and sensible advice which will inform CxOs, marketers and communications professionals alike.

If you have an interest in the social web and optimisation of communications using social media, this book is a must buy.

Further Info

[source: Amazon]

Today′s managers are faced with an increasing use of the Web and social platforms by their staff, their customers, and their competitors, but most aren′t sure quite what to do about it or how it all relates to them. Organizations Don′t Tweet, People Do provides managers in all sorts of organizations, from governments to multinationals, with practical advice, insight and inspiration on how the Web and social tools can help them to do their jobs better. From strategy to corporate communication, team building to customer relations, this uniquely people–centric guide to social media in the workplace offers managers, at all levels, valuable insights into the networked world as it applies to their challenges as managers, and it outlines practical things they can do to make social media integral to the tone and tenor of their departments or organizational cultures.

    • A long–overdue guide to social media that talks directly to people in the real world in which they work
    • Grounded in the author′s unparalleled experience consulting on social media, it features eye–opening accounts from some of the world′s most successful and powerful organizations
    • Gives managers at all levels and in every type of organization the context and the confidence to make better decisions about the social web and its impact on them

Euan Semple is one of the few people in the world who can turn the complex world of the social web into something we can all understand. And, at the same time, learn how to get the most from it.

Ten years ago, while working in a senior position at the BBC, Euan was one of the first to introduce what have since become known as social media tools into a large, successful organisation. He has subsequently had five years of unparalleled experience working with organisations such as Nokia, The World Bank and NATO.

He is a one-man digital upgrade option for us all to download.

This world is changing fast, but he makes sense of it because he understands that the core basics remain the same: community, learning, and interaction. He is a master story-teller who offers a host of practical tales about how this new world can work for real people in the real world.

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Figure 1 – The Johari Window devised by Joseph Luft and Harry Ingham

johari window

The Johari Window is a model for describing personal awareness types and human interaction.

Quadrant A: encapsulates personal awareness and a wish to share information with others, for the purposes of simplicity assume this means publicly.

Quadrant B: encapsulates personal awareness of a different type. The motivations for concealment are plentiful (bad habits, competitive advantage, Machiavellianism, protection of personal interests etc.). The size of this box tends to diminish as trust relationships expand, however I contend: a) there are many types and levels of concealment implied here and b) many different levels of trust in different social circles.

Quadrant C: encapsulates weak personal awareness and misinterpretation (we assume others see us as we see ourselves, but this is not the case). This quadrant (in the context of Social Networking) provides an interesting opportunity for introspection and awareness development from social feedback, Social Network Analysis and sentiment analysis. This is a box full of brambles!

Quadrant D: Donald Rumsfeld’s infamous Known Knowns speech of 2002 sums up this quadrant.

A Prophetic View

Just under two years ago I wrote a somewhat prophetic article concerning Privacy and Social Networks in which I argued for the need for additional privacy controls and multiple walled gardens within social networks. Facebook lists were a crude approximation, but Goolge+ Circles now excel at delivering the concept. A sister post in February 2010 discussed Social Search and the Integrity of the Social Graph, concluding that Google was heading (with purpose) into the Social Networking space.

What I said back in January 2010:

Visualisation of Social Network privacy controls is poor. The granularity of access controls is too coarse. My solution would be creation of (either my privacy “Onion model”) or perhaps more simply a ‘radar’ or quadrant model on which connections could be placed within ‘trust zones’ (by dragging and dropping them onto the appropriate region). Configuration is half the battle, and visualisation of the resultant privacy controls effect is essential. This is where current controls are weakest. I also want multiple walled gardens to play with (where I could segregate user groups) and ensure no (uncontrolled) information leakage between…

A trust and privacy ‘radar’ would be equally interesting, with those closest to the centre having the greater trust relationship and access to more personal data.

The Johari Window and Google+ Circles

Figure 2 – The Google+ Circle Model

circles

I have a number of Circles within Google+: Friends, Family, Acquaintances, Scientific Community, Social Media, Politics, Techies etc. There is also a ‘Public category’ which maps neatly onto Quadrant A of the Johari Window.

Quadrant B maps neatly to the different circles (Friends, Family etc.). This creates controlled separation, where I can isolate various topic discussions. This helps prevent Family members from being bored by discussions about Social Network Analysis or Social Psychology! Equally it saves Scientific Community colleagues reading my latest views on the European Union. There is a great deal more depth to this than simple ‘separation of interests.’ Despite what we may think, as multi-dimensional beings, we do not necessarily want everyone in cyberspace or our social sphere having a complete 360 degree view of our personality, interests or social connections.

Quadrant C could make for a ‘fun’ social network game – tell me something about myself that I don’t know, but you do know. Play at your own risk!

Quadrant D is ripe for Reality Mining as long as there is a digital footprint.

The Johari Window provides an interesting thinking framework on which to base an approach to online privacy protection and information sharing across social groups.

Extending the Johari Window for Privacy and Reputation Protection

I propose an extension to the Johari Window (as depicted in Figure 3). As information flows into a Circle we lose control of it. We must assume that we have chosen Circle members well and that each member will understand (and abide) by our privacy wishes in respect of that information. The obvious drawback however is that there is no adequate meta-data associated with the shared information to indicate to Circle members what is ‘allowable’. Perhaps Google will introduce ‘Circle Contracts’ to stipulate between parties what is acceptable!

Adding an A+ box (Figure 3) recognises that there will be information which I am happy to be disclosed by people acting as relays between Circles with no restrictions.

Box B+ recognises information disclosed to certain Circles must stay within that Circle or may be selectively disclosed to other Circles (not under my ownership) which meet certain membership/privacy criteria. There is currently however no way to express this (or manage disclosure across ‘logically chained Walled Gardens’).

Box C+ recognises that there is information about myself of which I am unaware, and would be happy about being disclosed. If it is information which may be publicly disclosed, it fits within box A. If it requires restriction per ‘Walled Garden’ or Circle, it fits within box B.

Box C++ recognises that there is information about myself of which am I unaware, and would be unhappy about being disclosed. This box is ripe for Reputation Protection.

Boxes C+ and C++ are interesting as I would be theoretically unaware of my privacy requirements until the information is disclosed (of course heuristics could be employed).

Boxes B, B+, C, C+ and C++ all have potential for information leakage. As Circles and Networks are highly interconnected, chances are the information could reach parties which you would rather not see it.

Extending the Johari Window and applying this thinking technique to online privacy within Social Networks is useful in terms of surfacing complexity and also challenging personal views of requirements for information management.

Figure 3 – Extending the Johari Window

[source: Steve Nimmons]

johari window extended

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Unseen Enemy

 Posted by at 3:41 am  Editors Choice, Social Media  Comments Off
Jun 102008
 
breakin

Article originally published by Evaluation Centre / Conspectus, Summer 2008

Steve Nimmons warns of the hidden threat to corporate privacy and reputation lurking within Web 2.0.

The Historical Problem

I recall (approximately eight years ago) reading an interesting poster on social engineering at a well-known electronics company in California. This wall-chart communicated sensible advice for dealing with unsolicited phone calls, ‘chance’ conversations and the importance of discretion when discussing corporate matters on planes, trains and automobiles.
Topics such as tail gating, the ‘risk of gallantry’, the social and psychological tricks used by experienced practitioners to project ‘belonging’, the need for discretion and vigilance in public spaces and of course ‘clear desk policies’ were explained in concise, relevant and accessible language. Continue reading »

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