Multitasking? No.
Multitasking? Cognitive, behavioral, neurological sciences are moving towards a clear no; http://eicker.at/Hyperconnectivity
Multitasking? Cognitive, behavioral, neurological sciences are moving towards a clear no; http://eicker.at/Hyperconnectivity
Does Google favour its own sites in search results? New study: Google less biased than Bing; http://eicker.at/SearchEngineBias
SEL: “Does Google favor its own sites in search results, as many critics have claimed? Not necessarily. New research suggests that claims that Google is ‘biased’ are overblown, and that Google’s primary competitor, Microsoft’s Bing, may actually be serving Microsoft-related results ‘far more’ often than Google links to its own services in search results. – In an analysis of a large, random sample of search queries, the study from Josh Wright, Professor of Law and Economics at George Mason University, found that Bing generally favors Microsoft content more frequently, and far more prominently, than Google favors its own content. According to the findings, Google references its own content in its first results position in just 6.7% of queries, while Bing provides search result links to Microsoft content more than twice as often (14.3%). … The findings of the new study are in stark contrast with a study on search engine ‘bias’ released earlier this year. That study, conducted by Harvard professor Ben Edelman concluded that ‘by comparing results across multiple search engines, we provide prima facie evidence of bias; especially in light of the anomalous click-through rates we describe above, we can only conclude that Google intentionally places its results first.’ … So, what conclusions to draw? Wright says that ‘analysis finds that own-content bias is a relatively infrequent phenomenon’ – meaning that although Microsoft appears to favor its own sites more often than Google, it’s not really a major issue, at least in terms of ‘bias’ or ‘fairness’ of search results that the engines present. Reasonable conclusion: Google [and Bing, though less so] really are trying to deliver the best results possible, regardless of whether they come from their own services [local search, product search, etc] or not. … But just because a company has grown into a dominant position doesn’t mean they’re doing wrong, or that governments should intervene and force changes that may or may not be “beneficial” to users or customers.”
Edelman/Lockwood: “By comparing results between leading search engines, we identify patterns in their algorithmic search listings. We find that each search engine favors its own services in that each search engine links to its own services more often than other search engines do so. But some search engines promote their own services significantly more than others. We examine patterns in these differences, and we flag keywords where the problem is particularly widespread. Even excluding ‘rich results’ (whereby search engines feature their own images, videos, maps, etc.), we find that Google’s algorithmic search results link to Google’s own services more than three times as often as other search engines link to Google’s services. For selected keywords, biased results advance search engines’ interests at users’ expense: We demonstrate that lower-ranked listings for other sites sometimes manage to obtain more clicks than Google and Yahoo’s own-site listings, even when Google and Yahoo put their own links first. … Google typically claims that its results are ‘algorithmically-generated’, ‘objective’, and ‘never manipulated.’ Google asks the public to believe that algorithms rule, and that no bias results from its partnerships, growth aspirations, or related services. We are skeptical. For one, the economic incentives for bias are overpowering: Search engines can use biased results to expand into new sectors, to grant instant free traffic to their own new services, and to block competitors and would-be competitors. The incentive for bias is all the stronger because the lack of obvious benchmarks makes most bias would be difficult to uncover. That said, by comparing results across multiple search engine, we provide prima facie evidence of bias; especially in light of the anomalous click-through rates we describe above, we can only conclude that Google intentionally places its results first.”
ICLE: “A new report released [PDF] by the International Center for Law und Economics and authored by Joshua Wright, Professor of Law and Economics at George Mason University, critiques, replicates, and extends the study, finding Edelman und Lockwood’s claim of Google’s unique bias inaccurate and misleading. Although frequently cited for it, the Edelman und Lockwod study fails to support any claim of consumer harm – or call for antitrust action – arising from Google’s practices. – Prof. Wright’s analysis finds own-content bias is actually an infrequent phenomenon, and Google references its own content more favorably than other search engines far less frequently than does Bing: In the replication of Edelman und Lockwood, Google refers to its own content in its first page of results when its rivals do not for only 7.9% of the queries, whereas Bing does so nearly twice as often (13.2%). – Again using Edelman und Lockwood’s own data, neither Bing nor Google demonstrates much bias when considering Microsoft or Google content, respectively, referred to on the first page of search results. – In our more robust analysis of a large, random sample of search queries we find that Bing generally favors Microsoft content more frequently-and far more prominently-than Google favors its own content. – Google references own content in its first results position when no other engine does in just 6.7% of queries; Bing does so over twice as often (14.3%). – The results suggest that this so-called bias is an efficient business practice, as economists have long understood, and consistent with competition rather than the foreclosure of competition. One necessary condition of the anticompetitive theories of own-content bias raised by Google’s rivals is that the bias must be sufficient in magnitude to exclude rival search engines from achieving efficient scale. A corollary of this condition is that the bias must actually be directed toward Google’s rivals. That Google displays less own-content bias than its closest rival, and that such bias is nonetheless relatively infrequent, demonstrates that this condition is not met, suggesting that intervention aimed at ‘debiasing’ would likely harm, rather than help, consumers.”
Does only written knowledge count? Wikipedia and the rules of citation and verification; http://eicker.at/WikipediaCitations
Scientists validate Dunbar’s number in Twitter conversations; http://eicker.at/AttentionEconomy (via @paisleybeebe)
Goncalves, Perra, Vespignani: “Modern society’s increasing dependency on online tools for both work and recreation opens up unique opportunities for the study of social interactions. A large survey of online exchanges or conversations on Twitter, collected across six months involving 1.7 million individuals is presented here. We test the theoretical cognitive limit on the number of stable social relationships known as Dunbar’s number. We find that users can entertain a maximum of 100-200 stable relationships in support for Dunbar’s prediction. The ‘economy of attention’ is limited in the online world by cognitive and biological constraints as predicted by Dunbar’s theory. Inspired by this empirical evidence we propose a simple dynamical mechanism, based on finite priority queuing and time resources, that reproduces the observed social behavior. … Social networks have changed they way we use to communicate. It is now easy to be connected with a huge number of other individuals. In this paper we show that social networks did not change human social capabilities. We analyze a large dataset of Twitter conversations collected across six months involving millions of individuals to test the theoretical cognitive limit on the number of stable social relationships known as Dunbar’s number. We found that even in the online world cognitive and biological constraints holds as predicted by Dunbar’s theory limiting users social activities. We propose a simple model for users’ behavior that includes finite priority queuing and time resources that reproduces the observed social behavior. This simple model offers a basic explanation of a seemingly complex phenomena observed in the empirical patterns on Twitter data and offers support to Dunbar’s hypothesis of a biological limit to the number of relationships.”
Brooks: “If the thing that makes it real is your capacity to have a theory of mind relationship with a certain number of people, I can still imagine that social media would increase people’s capacities. … If [social media tools] succeed they will slowly break Dunbar’s number. … I would expect that Twitter would have a small number of people with a huge number of connections, but they’re not listening to that many people, they’re just talking to that many people.”
Social network sites do not increase offline social network size or relations; http://eicker.at/Friends (via @gedankenstuecke)
Game design elements in non-gaming contexts: great gamification introductory papers for CHI 2011; http://eicker.at/GRN
Handsfree gaming accessory Kinect controls virtual worlds, robots, scans objects, goes science; http://eicker.at/KinectHacks
Drexler: How to understand; http://eicker.at/2a – and learn about everything; http://eicker.at/2c (via @Optimistontour)
Tim Rueb 20:19 on 23. August 2012 Permalink |
It’s called “hiring employees” – the truest form of multitasking for the truly successful.
Gerrit Eicker 07:50 on 25. August 2012 Permalink |
Well said!