Every year, the analyst firm Gartner publishes between 90 and 100 "Hype Cycles" with insight on about 1,900 different technologies.
Stephen Dale's insight:
According to Gartner, Big Data has about 2-5 years before reaching it’s ”Plateau of Productivity.” That’s the enviable point at which a technology finally delivers predictable value. The promise of Big Data, of course, is a treasure trove of high value across many industries – including healthcare. Everything from predictive and prescriptive analytics to population health, disease management, drug discovery and personalized medicine (delivered with much greater precision and higher efficacy) to name but a few.
Big Data is clearly where all the excitement and headlines are, but it’s the little data that is likely to have the most effect on our individual healthcare. That is at least until Big Data gets well beyond its “peak of inflated expectations” and closer to its “plateau of productivity.” The question then is – which vendors are likely to be around in 2-to-5 years?
Understanding personal learning networks: Their structure, content and the networking skills needed to optimally use them
Stephen Dale's insight:
Networking is a key skill in professional careers, supporting the individual’s growth and learning. However, little is known about how professionals intentionally manage the connections in their personal networks and which factors influence their decisions in connecting with others for the purpose of learning. In this article, we present a model of personal professional networking for creating a personal learning network, based on an investigation through a literature study, semi–structured interviews and a survey.
A useful insight into what 'digital curation' really means, and what differentiates it from "frictionless sharing", or "link spraying". It seems that in these pioneering days of content curation, the true meaning of the concept has not yet captured the imagination of knowledge professionals. #kmers
This article and infographic was posted by Jeff Bullas. We all know visual content attracts attention - here are some highlights on just how powerful it really is in social media.
"Visual content has been on a rapid upward trajectory over the last 12 months. Social media platforms such as Pinterest and Instagram have taken the social media world by storm. Instagram announced in July that it had acquired 80 million users"
** Pinterest and Instagram have taken the social media world by storm.Instagram announced in July that it had acquired 80 million users. To put some further perspective on its adoption and growth, the visual social media network is now being used by 40% of the worlds top 100 brands.
Simply Measured looked at Facebook’s top 10 brand pages to find out the real numbers and facts and figures on the engagement and sharing levels of photos and vides in comparison to text and discovered:
Videos are Shared Photos are liked 200% more than text updates
To put some perspective on the power of visual content other studies show that Photo and video posts on Pinterest are referring more traffic than Twitter, Stumbleupon, LinkedIn and Google+.
Selected by Jan Gordon covering "Curation, Social Business and Beyond"
The rise of big data is an exciting — if in some cases scary — development for business. Together with the complementary technology forces of social, mobile, the cloud, and unified communications, big data brings countless new opportunities for learning about customers and their wants and needs. It also brings the potential for disruption, and realignment. Organizations that truly embrace big data can create new opportunities for strategic differentiation in this era of engagement. Those that don't fully engage, or that misunderstand the opportunities, can lose out.
There are a number of new business models emerging in the big data world. In my research, I see three main approaches standing out. The first focuses on using data to create differentiated offerings. The second involves brokering this information. The third is about building networks to deliver data where it's needed, when it's needed.
* Differentiation creates new experiences.
* Brokering augments the value of information.
* Delivery networks enable the monetization of data.
In the last week Content Curation Tool Scoop.it announced some new features:
- Google Chrome extension turns your browser into a powerful curation tool. - The Scoop.it widget allows you to embed a slider from your topic pages. - The BufferApp and Scoop.it integration is a way to easily schedule the distribution of your posts to social networks.
Robin Good: Alexis Dufresne of Faveeo, an up and coming information filtering and discovery tool not yet available to the general public, has been posting some interesting articles on topics related to news curation, filtering and discovery.
In particular, I found interesting his recent analysis on automated solutions and algorithms designed to help scale curation efforts, as these are generally discarded as inappropriate for any type of professional work. But, as he rightly points out, there are several tasks inside a curator workflow that can indeed help and reduce the curator's workload without limiting his ability to manually select and edit what he finds most appropriate.
Alexis pinpoints at least three different areas in which algorithms and automated operations can indeed greatly help the curator's work. These are:
1) Discovery of new sources and networks: ...By teaching a machine about the kind of sources and users a curator is looking for, a machine could process from the incredible mass of sources and people out there to figure out those who are likely to be trusted sources of information. By using techniques of text analysis, social reach, semantic density, popularity and more, this task could be done by a machine.
2) Learning the profile of a curator: A lot of engines are focusing on filtering the semantic meaning of an article in order to recommend other content. But by using advanced NLP techniques and text extraction methods, we could go further and have an idea of the tone, the lenght and other signals that can indicate the preferences of a human curator, other than simply the actual keywords used in the text.
3) Social recommendations: ...By detecting users that seem to click, like, share or save the same articles, we can connect them together to mutualize their search and discovery operations, in order to speed things up.
This report demonstrates that surveillance policy makers have options, many of which are a lot less intrusive than the powers proposed by the Communications Data Bill (otherwise know as the 'Snooper's Charter'), and that civil society is open to meaningful engagement about surveillance laws in the digital age.
It is written for a general audience by leading experts, academics and representatives of a number of civil society groups. The articles in this publication serve as an example of the sort of conversations that would be possible through a proper public debate about what information should be collected and who should have access to it.
The report features contributions from a range of experts setting out how more privacy-friendly surveillance policy could work and concludes with
some recommendations for future surveillance policy making.
When we think of traditional news gatherers, we might conjure up the image of an obstreperous character brazenly hassling a slimy official for the real story -- or hovering paparazzi harassing a poor celebrity innocently shopping for handbags in...
Stephen Dale's insight:
Describes the growth and importance of Data Journalism in bringing informaton to life. Infographics and other visualisation techniques delivered with cutting and insightful narrative is the new and emergent paradigm for mainstream journalism.
Oner example cited in the piece is data on crime numbers -- public statistics provided by local police departments. The data is collected as part of the police force's daily operations, and it's published for anyone who bothers to look at it. It's pretty drab stuff -- numbers up, numbers down -- until a data journalist gets hold of it.
A data journalist will collect those numbers over time -- often delivered by the agency weekly or monthly, along with geographic coordinates like addresses. That let's the data journalist generate maps, visualisations, reports and adjectives for the neighborhoods within the agency's jurisdiction, thus letting readers keep current on local crime.
"Data journalism is a fast-developing field that has transformed investigative reporting across newsrooms for decades in the U.S. and more recently in the UK," said Minal Patel of City University London's the Center for Investigative Journalism.
Journalists can get a sense of how to get started with their own projects by consulting the Data Journalism Handbook.
Do you remember that old familiar chime “you’ve got mail!”? You couldn’t wait to open the mailbox flag icon on your desktop that signaled a new email message was waiting to be read.
Stephen Dale's insight:
Many organizational leaders today struggle with the decision to remain in the comforts of communicating with colleagues through familiar email platforms, or to move to more advanced social collaboration platforms that encourage communicating and sharing between teams in real-time. And in this later scene, significant benefits can be received such as increased employee engagement, knowledge sharing and productivity.
Email works well when sending confidential or restricted information, or if you want to control the content or broadcast a message to multiple contacts as part of an online marketing campaign. However when it comes to collaborating with teams on time-sensitive projects, or to gain critical insight from others on documents and business decisions, email has proven time and time again to be a major hindrance to an organisation’s productivity.
Brian Solis expounds the importance of the 'human algorithm', the people and skills required to anaylse and interpret the data that is being collected in ever-increasing volumes (big data is BIG), and with the insight and ability to put knowledge to work.
The human algorithm is a function of extracting insights with intention, humanising trends ad possibilities and working with strategists to improve and innovate everything from processes to products to overall experiences.
The human algorithm can have an immediate impact with social media listening. In addition to tracking simple data signals such as conversations, sentiment, share of voice and service inquiries, data can present insights into preferences, trends, areas for innovation or refinement, R&D, and co-creation Even though sophisticated tools can help track data points that can lead to these insights, it still takes a human touch to surface them and in turn advocate findings within the organisation.
At present the community or social media manager is not tasked with this type of responsibility therefore, insights largely remain undiscovered. It takes a new role that unites the disciplines of business intelligence and social media with the perseverance of a change agent. Without it, the insights that lead to innovation will be stifled by fear and skepticism.
Big data is not new. It has existed for ages and can be attributed even to the initial years of computing. However, one might do well to consider why is there an increased buzz around this now.
The answer is quite simple: Significant advances that have been brought about by x86 hardware have actually helped in bringing computing power to the masses. However, with new technologies, cloud computing has extended this power. Now, users have extended perimeters, while still being able to control costs effectively...
The beauty and challenge of Twitter is stuffing your most sophisticated thoughts and feelings into a measly 140 characters (or less). No good tweet is ever going to be 140 characters because it’s impossible to share, respond or reference a tweet that’s already at it’s max. If you want to make a big statement with a small message, you have to trim the fat. From the basic beginner to a tweet-savvy expert, this cheat sheet will help you navigate the perplexing and concentrated language that often appears in the stream, and make you seem like a regular pro in no time.
Conversation Agent quotes on Influence from Valeria Maltoni It's the age of the connected customer and people are now comfortable using technology to share -- privately or in public.
Here are some highlights:
How social currency influences behavior
**Social influences include peer pressure and social exchange. The latter is stronger than an economic motive.
**Most human interactions consist of an exchange of value. From a psychological standpoint, actions like sharing signal desire for self expression, need for validation, and social status recognition, and also simply altruism and affinity with a group or cause.
**Both social influences are amplified in public settings.
Psychologist Robert Cialdini documented six principles of ethical persuasion:
Selected by Jan Gordon covering "Curation, Social Business and Beyond"
Giuseppe Mauriello: I read this interesting article on GigaOM by Jim Hornthal that published an excerpt from his TED ebook “Haystack Full of Needles: Cutting Through the Clutter of the Online World to find a Place, Partner, or President.”
Here are some points that they caught my attention:
"What happens when data is huge? We get lost. Discovery, not search, will produce the next data-exploration breakthrough.
In the modern era, information overload has become an even larger problem than information scarcity. Data is generated by the ton, and most of it is not remotely relevant or useful. The way we search has even created a gray market in this thin veneer of content, often referred to as “faux content.”
Estimates vary but all point to evidence that a great percentage of the web today is simply manufactured sites created specifically to scoop up visitors in search of ad dollars. The effect isn’t just a nuisance, and makes sifting through the ever growing tons of online data even more confounding.
The back-link game, or the process by which websites can purchase inbound links — Google’s original secret sauce that generated results based on the “authority” of a web page — has become vital to generating superior search results, and the multibillion-dollar search-engine optimization industry is built on reverse-engineering the actual search algorithms for commercial gain.
Rich Skrenta, the CEO of the spam-free search engine Blekko, frames this de-evolution in an interesting way: “Today, the Web has become a tragedy of the commons, a social system ruled by spam — over 90 percent of URLs today are pure junk!”
Fortunately, there is a growing band of innovators who have taken up the challenge and are tackling those issues — with startlingly similar approaches. Their universal mission is to employ relevant, expert-based pattern recognition to generate a useful consumer outcome.
For these passionate discovery engineers, the goal is not to find a needle in a haystack, but instead to present a haystack of needles, an array of potential valuable answers to a growing list of useful and impactful questions..."