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An increasing number of public/private initiatives are exploring novel ways of conducting scientific research, including the use of social media and online collection of self-reported data.
Research relying on collection of self-reported data by self-selected participants has known methodological limitations, including selection bias, information bias, and confounding.
Such limitations may mean that results and conclusions of research using data obtained through online communities need to be interpreted with caution, as further replication is often required.
The findings of research, including their potential actionability, should be communicated to participants in a way that is understandable, accurate, complete, and not misleading.
The potential for sharing participants' data with third parties as well as the commercial uses of research findings should be disclosed to participants prior to consent.
Via bacigalupe, cometa23
Networks guru and author Albert-László Barabási says diseases are the results of system breakdowns within the body, and mapping intracellular protein networks will help us discover cures.
Via ukituki
One of the rules of thumb taught in many communications courses is to know your audience. It can also be useful to know what your audience thinks of you.
Via ukituki
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Suggested by
ukituki
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Valdis Krebs: Connect on your similarities and benefit from your differencies.
So when you map your world, check these issues: Are you happy with how diverse it is? If it is not diverse you will find it hard to use crowd sourcing etc and you will be too deep in your own echo chamber Do you know who your key connectors are and do you care enough about them? For they give you the best access to the sub networks? Do you know who counts the most in each network? Again this is all about leverage.
Via ukituki
I’ve been huge football fan since I was a child1 and have always watched closely various national championships as well as international competitions. That was one of the reasons to collect transfer data for the football seasons 2010-2011, 2011-2012 and the current one 2012-2013 (although it is still in the beginning) and look at it trough the lens of social network analysis. My idea was to see which are the most active clubs, how are they connected and whether through visualization I can find something interesting. I was not surprised by the finding of the frequent transfers from Arsenal to Manchester City, after all it is a well known joke among football fans that Man City look at Arsenal as their own academy
Via ukituki
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eRelations
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Just about every major social network allows marketers to share visual content in some capacity, but that doesn't necessarily mean that particular network is the best medium for visual promotion. And in a world of hundreds of ...
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eRelations
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Teens and young adults are hyper-immersed in technology. A total 95% of teens ages 12-17 are online, 76% use social networking sites and 77% have cell phones.
I'm sure you have experienced meeting a stranger at a party, and finding that she is a friend of a schoolmate of yours, or an acquaintance of a relative, or ...
Via ukituki
Guest lecture at Free University in Knowledge Management course by Maura Soekijad and Roos Erkelens
Via ukituki
Alexander Semenov's slides from ASNA2012 with some findings from dataset I've gathered from Twitter during protest meetings in Moscow on 24th of December 2011
Via ukituki
In an era of heightened competition and a changing workforce, new models of social and real-time interaction and networked, community-based collaboration are creating exceptional business value.See it on Scoop.it, via Social network data analysis...
Via Fred Zimny
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Gephi’s project aims to bring the perfect tool for visualizing and manipulating networks.
Via cometa23
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eRelations
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Social Media Conflict Management: eRelations will help you manage online conflicts/crises in social media networks through ADR conflict resolution skills.
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eRelations
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eRelations Social Network Analysis gives businesses tools and expertise to perform SNA: work with Gephi and other GUI to analyze nodes and connexions.
There is no line on the balance sheet for "ability to innovate" or "skill at managing brand."
Here is the Social Network Analysis Money Quote in this HArvard Businerss Review piece:
Case in point, SNA conducted at Novartis helped reveal a pattern of communication — and the existence of parallel innovation efforts — that made it possible to combine teams before they reached a crucial stall point in the development of a new vaccine. At a major retail bank, early signals of an emerging rift between factions — manifested in very different networks of information sharing — made it possible to save an acquisition before it came apart. And a rapidly growing pharmaceutical manufacturer discovered through network analysis that management bottlenecks were holding back critical decisions and alienating lower level employees.
Via John Sumser
The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods.
Via Complexity Digest, Spaceweaver, David Rodrigues, ukituki
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eRelations
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Unbound, http://unbound.co.uk/, puts the power of publishing in the hands of authors and readers. Authors pitch their book ideas directly to you.
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Continuous data protection technologies allow companies to take snapshots of data within the data center, backup this data more often and replicate it to an offsite data center, reducing data loss to almost zero.
Welcome to our socially networked world. One of the most puzzling things about it is why normally sane, well-adjusted, intelligent people lose not only their judgment but also their marbles when confronted with the opportunities for exposure offered by Twitter, Facebook, Foursquare, Path, Instagram et al.
Via Ilkka Olander
Basic concepts and methods
Via ukituki
This piece was brought to my attention by my wonderful friend and colleague, Jennifer Sertl. It was written in April of 2011 by Jay Deragon who is always articulates the present and the future in a way that hopefully expands your awareness which we all need in today's marketplace. Here are some of the highlights: **People are gathering in "tribes" to connect, collaborate, discover and influence change. **Social technology provides people the ability to aggregate around everything and anywhere. **The market sees this and attempts to aggregate self serving tribes but the people have a different purpose & their own tribe **The aggregation of tribes has become the pursuit of the market. Pulling groups and custom networks has become a common practice of the markets managing these tribes with a purpose different than simply gatering of the trade. The evolving dynamics of tribal aggregation are the dynamics that will change the way markets interact with tribes 1. Tribes control the message with growing influence over markets 2. Tribes have a purpose. Help them fulfill their purpose and just maybe you'll become part of that tribe 3. Companies will have to learn that they are not the "connection" to the tribes, internal and external hold the keys to tribal influence 4> Tribes do need management, they need tools to accomplish their objectives and will always be self managed 5. Tribal leaers are more interested in serving tribe members than themselves. Here is a great takeaway: Seth Godin writes: "Tribe management is a whole different way of looking at it. **It starts with permission, the understanding that the real asset isn't an amorphous brand but is in fact the privilege of delivering anticipated relevant messages to people who want to get them
Selected by: Jan Gordon covering "Curation, Social Business & Beyond"
Via janlgordon
A new survey has found many health care providers make use of health data analysis, but few use analytics in direct patient care.
Via Linda Lia
Along with the development of Web 2.0 applications, social media services has attracted many users and become their hands-on toolkits for recording life, sharing ideas, and social networking. Though social media services are essentially web or mobile applications and services, they combine user-generated content and social networks together, so that information can be created, transmitted, transformed, and consumed in the cyberspace. Thus, social media somehow could be regarded as a kind of sensor to the real life of its users. In general, the data from social media is of low quality. Pieces of information in social media are usually short, with informal presentation, and in some specific context that is highly related to the physical world. Therefore, it is challenging to extract semantics from social media data. However, we argue that given sufficient social media data, users' collective behaviors could be sensed, studied, and even predicted in a certain circumstance. Our study is conducted on data from two services, i.e. Twitter, and Sina Weibo, the most popular microblogging services all over the world and in China, respectively. Collective behaviors are actions of a large amount of various people, which are neither conforming nor deviant. Various collective behaviors are studied in the context of social media. Our studies show that there are various information flow patterns in social media, some of which are similar to traditional media such as newspapers, while others are embedded deep in the social network structure. The evolution of hotspots is highly affected by external stimulation, the social network structure, and individual user's activities. Furthermore, social media tends to be immune to some repeated similar external stimulations. Last but not the least, there is considerable difference in users' behavior between Twitter and Sina Weibo. Source: http://bit.ly/TgqfPt
Via Anna Evangelista
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