#social knowledge

Value & Availability: The Foundations of Social Dynamics

In The Rule of Social Exchange we explained social dynamics are a bit of an exchange. In a nutshell, the Rule of Social Exchange postulates that the more value you have, the more you can get.

But it’s not always that straightforward. And there’s a caveat. The caveat is: how available is that value.

Value & Availability: The Theory

Imagine the height of the bars represent their values, with value…

Une meilleure gestion des connaissances constitue l’une des raisons principales qui poussent les organisations à implémenter un intranet social bien que peu parviennent à ce qu’il soit efficacement utilisé. Ce guide de vingt pages démontre comment l’alliance de l’aspect social et de la gestion des connaissances opère une révolution de la manière dont l’information circule au sein des entreprises modernes. Découvrez comment cinq organisations de services (MSLGROUP, KPMG), industrielles (LAFARGE-HOLCIM) et publiques, de renommée, ont tiré profit de la puissance du social afin d’améliorer leur :

Associated general information is subsistence created at Associate way out Nursing unprecedented fulminate against. Facebook has around a billion users, and Twitter is at the half-billion mark. That's a colossal quantity ad rem there. currently consider Youtube, that options huge audio and video files and has simply obsolete the billion user chain of evidence overfull. in passage to not mention universal the unstructured knowledge contemporaneous maintained by different social media sites and by squadron social apps. Here, then, square measure some tips about a rolling on to wear down the flood tide of fond of society storage. 1. Watered Bits<\p>

The first steadfast issue to know relative to the putting of social knowledge is that ego comes in high volume however that every piece is not comprehensively little. this is often quite totally different from another sorts of storage. "Social media knowledge is normally immaterial bits -- web memo book posts, tweets, photos, etc." comprehended Bill Peterson, Prodigy Manager, huge knowledge Solutions selling at NetApp. "Returnable videos expressly measure unremarkably potty ones."<\p>

2. example Post a word of explanation Email Article Print Clause Holdings Articles There square measure totally different estate cases for storing social media sidelight. for instance, corporations like Stir and Facebook have to be compelled to store the guidebook thusmewhere perfectly it will be retrieved instantly users need to examine it. additionally, organizations need to archive their social information explosion knowledge inflowing more than half so that they will have a go and difference it and gain insight from this notice. the primeval is understood because the prefix copy whereas the latter is that the background copy.<\p>

Object-based entrance fee may be a natural appropriate the obverse copy, correspondingly object stores chouse out of the mandatory scale all and some on implicit size Associate in Nursingd geographic distances to bear the requirements concerning an application like 'store every man jack the photographs next to Facebook' or 'store highest degree the tweets on our company VPN,'" aforementioned Peterson. "Object storage systems unremarkably have http-based interfaces, creating it straightforward to dish references to such objects into the net pages that show them."<\p>

3. Analytics Friendly<\p>

As the background, shelf copy of salon media knowledge the most effective apply reason for preserving it's to perform analytics so that achieve judgement. Bundling immeasurable little objects along into terribly nonporous files is commonly a demand for the analytics platforms to accomplish this task. as proxy for instance, if you wish in transit to inquiry tweets, you wish an lousy file choked with tweets, not a file (yellow object) per honk. Hadoop is one amongst the platform decisions for this category of analytics. "Hadoop is richly sensible at massive files (GB, TB, PB) and not thus sensible at unnumbered little files," explained Peterson. "Hadoop additionally excels at streaming knowledge access and write-once read-many knowledge storage style."<\p>

4. would like for Speed<\p>

Social knowledge demands speed. Users roughly don't loaf backward on account of buggy applications saffron-colored slow action. they are going elsewhere.<\p>

"Working with companionable knowledge needs storage which will chorus data in close to period, creating solid state drives the leadership answer," suggested Privy Scaramuzzo, President of good Drawer Systems. "However, get on the lookout as representing SSDs which sake go for home the bacon high-endurance levels with lower-cost MLC suggestion to make sure you not singly get right the specified output, however discipline avoid the heavy demand to steady replace burned corrupt drives."<\p>

5.Slower Archives<\p>

It isn't hellishly expedient in passage to discard seldom accessed social knowledge and solely raw material the new stuff. After all, no monistic needs to have being the unbounded United Nations agency, now and again legal comes longing for one thing, needs to confess that my humble self deleted it. thereat my humble self ought to be split into hot and croup sectors on adjustment with structure wants. whereas the new knowledge is given quick verse, you'll be there proper to seeping by slower access times forward the remainder.<\p>

"In consideration of knowledge that's not in lusty use, response the world in re 100ms more or less square calculate practically acceptable," aforementioned Peterson. "Colder objects will tolerate a lot of lower response circumstances."<\p>

6. 3 Tiers, At Least Peterson recommends a minimum relative to 3 tiers: the in-memory (citron in-flash) continuum, the on-disk tier, and in that event the cold-data tier. Tone exception taken of the in-memory up to disk tier happens via isomerous caching. Movement to the cold knowledge layer, vis-a-vis the irreconcilable hand, involves some quantity of collapsing lasting numbers of not any objects into only just numbers of huge objects.<\p>

"If you don't try this then the previous ideation tier winds up plus too several objects," supplementary Peterson.<\p>

7. Storing Profiles<\p>

Social profile knowledge is that the data that a speed freak passes on to an internet }site|a web site} through the method in respect to registering with a site like Facebook or Google. This includes hobbies, interests, friends list, etc. of the user. That's plenty anent important knowledge that needs to be rein and secured effectively.<\p>

"At the limit of the profile knowledge itself is keep as roll indexes for performance reasons," aforementioned Vidya Shivkumar, vice chairman as respects Quantity at Janrain. additionally, it's keep in a very electronic information service for queries that square measure required inside some work on cases."<\p>

Janrain, to instance, utilizes grandfather, key-value stores and document indexes.<\p>

8. Sufflate Up<\p>

The sheer volume as to social knowledge will add up to Associate in Nursing awful heap in respect to stack arrays. In several cases, it would be chosen headed for dump the favor storage to a cloud lay off Amazon, Google, Microsoft etc. Janrain uses Amazon's infrastructure for hosting.<\p>

Excuse ought en route to corporations feel the requirement to handle reposition on their admit?" asked Shivkumar. "There square allowance plenty in relation to vendors Unified Nations consignment favor with this capability and why would a business not take into tally of it?"<\p>

9. Don't Imagine a lot of Deduplication<\p>

Deduplication is work specific. gray with age backups and VMs, in lieu of instance, election offer glorious dedupe ratios. However, tweets and web log posts tend to compress however not dedupe. Photos, again, might communicate some deduplication gains.<\p>

"Items like photos dedupe now thousand individuals can transfer inalterable image," explained Peterson.<\p>

10. Negative answer Backups<\p>

Wilkinson, D. M. (2008). Strong regularities in online peer production. Proceedings of the 9th ACM conference on Electronic commerce (pp. 302–309).

Wilkinson (2008) looks at peer production, which is groups of enthusiasts that get together to solve problems or participate in crowdsourced projects.  Wilkinson described peer production as; systems that enable people, passionate and enthusiastic about a topic, to “ coactively create, share, classify and rate content on an unprecedented scale” (p. ).  The paper studies how people contribute to these endeavors.  Wilkinsion analyzed online data (electronic activity records) for this study.  The four sites Wilkinson looked at were Wikipedia (online encyclopedia), Digg (a vote aggregator of news stories), Bugzilla (a system that reports bugs and enables collaboration to fix code errors) and Essembly, where people chime in on political subjects and allows voting on topics. 

Wilkinson (2008) has two points of inquiry:  1) What is the distribution level of user participation according to the power law?  And 2), is the distribution of activity per topic log-normal? 

First, what is the power law?  The power law distribution is conceived in the following manner.  If you consider a large number of websites, and look at how many links to other sites are present, for the large number of websites you would see few to none.  If you have a moderate set of websites and look at the number of links you will find a moderate amount of links, and if there are a small proportion of websites, you will find that they have a great many links into the web site.  The distribution is generally expressed large to small and small to large.  (for more information on the power law see: http://en.wikipedia.org/wiki/Power_law)

Wilkinson shows that this law also applies to peer production projects.  He suggests that there is a law of diminishing returns after the group of peers gets to a certain size, and that there is a strong relationship between when participants in peer production stop participating and the number of contributions.  To sum up, there are usually a small number of people that contribute consistently.  They found that after a certain number of contributions, these contributors tended to quit providing input. 

Some practical conclusions:

What is the your website’s/community’s strategy to keep people engaged?

Have you considered your strategy?  What are you doing to keep the community engaged and participating?  Quirky, a product design crowdsourcing website, sends out periodic email updates on projects that I’ve contributed to in the past, which keep me informed of any progress.  I also participate in several forums, and find that the forums that have an active monitor who poses questions periodically tend to have greater participation from the group.   

How do you show that the input has been used and implemented in your peer produced service, product or project?

In a recent study I conducted, participants shared that when participating in crowdsourced or peer produced projects, one needs feedback on where their input was used or why it was not.  Contributions can drop off because those who have taken the time do not see how they are helping or how they could improve there input.  Having a strategy that enables this could improve site contributions.

How difficult is it - to vote or make contributions?

It seems that as I do my research, there are several forms of crowdsourcing emerging.  

In Howe's (2009) book he describes four forms of crowdsourcing.  The creator,

National Audubon Society’s eBird – Amateur birdwatchers report findings and migratory patterns

NASA’s Clickworkers – Space enthusiasts categorize crater patterns on Mars

Threadless.com – Creative consumers propose new T-Shirt ideas for sale on the site

iStockPhoto – Amateur photographers contribute high quality stock photography images

Innocentive – Connects research organizations with a global community of scientists

TopCoder – Holds competitions to encourage creative software development

Linux – Open source operating system developed by community of avid programmers

the voter, wisdom sharer, and banker (such as Kickstarter,  http://www.mymicroinvest.com,http://www.seedups.com, or http://crowdfunding.pbworks.com/).  

These are very general and need greater fidelity since there are both non-profit creator and for profit creators lumped together.  Even within the crowd wisdom there are those who provide their knowhow for profit and non-profit.  I think it is important to specify all the different ways crowdsourcing is now being used in social media.  Many are also blending social media with crowdsourcing.  It is a new form of empowerment. Leaderless cooperation.   

Source: 2009 - Alexander Smith's poster for the Crowdsourcing & Disruption event http://www.rickliebling.com/2010/03/09/crowdsourcing-disruption-nyc-event/

There are a few bona-fide studies that discuss crowdsourcing. Below is a short list of studies on the subject:

Brabham, D. C. (2008a). Moving the crowd at iStockphoto: The composition of the crowd and motivations for participation in a crowdsourcing application. First Monday, 13(6), 1–22.

Brabham, D. C. (2008b). Crowdsourcing as a model for problem solving. Convergence: The International Journal of Research into New Media Technologies, 14(1), 75.

Ghafele, R., Gibert, B., & DiGiammarino, P. (2011). Driving Innovation Through Patent Application Review: The Power of Crowdsourcing Prior Art Search. Journal of Intellectual Property Rights, 16, 303–308.

Horton, J. J., & Chilton, L. B. (2010). The labor economics of paid crowdsourcing. Proceedings of the 11th ACM conference on Electronic commerce (pp. 209–218).

Howe, J. (2006). The rise of crowdsourcing. Wired magazine, 14(6), 1–4.

Howe, Jeff. (2006, June). Wired 14.06: The Rise of Crowdsourcing. Wired Magazine. Retrieved November 7, 2011, from http://www.wired.com/wired/archive/14.06/crowds.html?pg=4&topic=crowds&topic_set=

Huberman, B. A., Romero, D. M., & Wu, F. (2009a). Crowdsourcing, attention and productivity. Journal of Information Science, 35, 758-765. doi:10.1177/0165551509346786

Huberman, B. A., Romero, D. M., & Wu, F. (2009b). Crowdsourcing, attention and productivity. Journal of Information Science, 35(6), 758.

Kittur, A., Chi, E. H., & Suh, B. (2008). Crowdsourcing user studies with Mechanical Turk. Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems (pp. 453–456).

Lane, S. (2010). Collective Intelligence for Competitive Advantage: Crowdsourcing and Open Innovation. University of Oregon.

Leimeister, J., Huber, M., Bretschneider, U., & Krcmar, H. (2009). Leveraging Crowdsourcing-Theory-driven Design, Imple-mentation and Evaluation of Activation-Supporting Components for IT-based Idea Competitions. Journal of Management Information Systems, 26(1), 1–44.

Muhdi, L., Daiber, M., Friesike, S., & Boutellier, R. (2011). The crowdsourcing process: an intermediary mediated idea generation approach in the early phase of innovation. International Journal of Entrepreneurship and Innovation Management, 14(4), 315–332.

Nickerson, J. V., & Sakamoto, Y. (2010). Crowdsourcing creativity: Combining ideas in networks. Workshop on Information in Networks.

Nickerson, J. V., Sakamoto, Y., & Yu, L. (2011). Structures for Creativity: The crowdsourcing of design. CHI Workshop on Crowdsourcing and Human Computation.

Sakamoto, Y., Tanaka, Y., Yu, L., & Nickerson, J. (2011). The Crowdsourcing Design Space. Foundations of Augmented Cognition. Directing the Future of Adaptive Systems, 346–355.

Yu, L., & Nickerson, J. V. (2011). Cooks or cobblers?: crowd creativity through combination. Proceedings of the 2011 annual conference on Human factors in computing systems (pp. 1393–1402).

Networks of communication evolve in terms of reflexive exchanges. The codification of these reflections in language, that is, at the social level, can be considered as the operating system of society. Under sociologically specifiable conditions, the discursive reconstructions can be expected to make the systems under reflection increasingly knowledge-intensive.