Month: August 2018
Reply to Release Version 2.0 of Micropub plugin · Issue #150 · snarfed/wordpress-micropub
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[25-Aug-2018 18:42:14 UTC] http://nominatim.openstreetmap.org/reverse?format=json&extratags=1&addressdetails=1&lat=45.53548&lon=-122.621244&zoom=18&accept-language=en-US
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👓 On Twitter, Students Want to Know: How Many Retweets for a Full-Ride Scholarship? | The Chronicle
In the self-serving subculture of retweeting for fame, some universities have been hit with repeated requests for free tuition — if a prospective student can spur a storm of retweets.
👓 ‘One Must Respect The Game’: French Open Bans Serena Williams’ Catsuit” | NPR
Serena Williams caused a sensation with the black catsuit she wore at this year's French Open tournament. But French tennis officials aren't as fashion-forward. From now on, players' attire apparently will be subject to a dress code — and Williams' sleek outfit is out. "I feel like a warrior in it, a warrior princess ... from Wakanda, maybe," she told reporters in May, referring to the movie Black Panther. "I've always wanted to be a superhero, and it's kind of my way of being a superhero."
👓 Disconnected, fragmented, or united? a trans-disciplinary review of network science | Applied Network Science | César A. Hidalgo
During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to unify what has become a diverging body of literature. I argue that social and natural scientists fail to see eye to eye because they have diverging academic goals. Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. In the following pages I discuss the differences between both of these literatures by summarizing the parallel theories advanced to explain link formation and the applications used by scholars in each field to justify their approach to network science. I conclude by providing an outlook on how these literatures can be further unified.
Highlights, Quotes, Annotations, & Marginalia
Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. ❧
August 25, 2018 at 10:18PM
Science and Complexity (Weaver 1948); explained the three eras that according to him defined the history of science. These were the era of simplicity, disorganized complexity, and organized complexity. In the eyes of Weaver what separated these three eras was the development of mathematical tools allowing scholars to describe systems of increasing complexity. ❧
August 25, 2018 at 10:19PM
Problems of disorganized complexity are problems that can be described using averages and distributions, and that do not depend on the identity of the elements involved in a system, or their precise patterns of interactions. A classic example of a problem of disorganized complexity is the statistical mechanics of Ludwig Boltzmann, James-Clerk Maxwell, and Willard Gibbs, which focuses on the properties of gases. ❧
August 25, 2018 at 10:20PM
Soon after Weaver’s paper, biologists like Francois Jacob (Jacob and Monod 1961), (Jacob et al. 1963) and Stuart Kaufmann (Kauffman 1969), developed the idea of regulatory networks. Mathematicians like Paul Erdos and Alfred Renyi, advanced graph theory (Erdős and Rényi 1960) while Benoit Mandelbrot worked on Fractals (Mandelbrot and Van Ness 1968), (Mandelbrot 1982). Economists like Thomas Schelling (Schelling 1960) and Wasily Leontief (Leontief 1936), (Leontief 1936), respectively explored self-organization and input-output networks. Sociologists, like Harrison White (Lorrain and White 1971) and Mark Granovetter (Granovetter 1985), explored social networks, while psychologists like Stanley Milgram (Travers and Milgram 1969) explored the now famous small world problem. ❧
Some excellent references
August 25, 2018 at 10:24PM
First, I will focus in these larger groups because reviews that transcend the boundary between the social and natural sciences are rare, but I believe them to be valuable. One such review is Borgatti et al. (2009), which compares the network science of natural and social sciences arriving at a similar conclusion to the one I arrived. ❧
August 25, 2018 at 10:27PM
Links are the essence of networks. So I will start this review by comparing the mechanisms used by natural and social scientists to explain link formation. ❧
August 25, 2018 at 10:32PM
When connecting the people that acted in the same movie, natural scientists do not differentiate between people in leading or supporting roles. ❧
But they should because it’s not often the case that these are relevant unless they are represented by the same agent or agency.
August 25, 2018 at 10:51PM
For instance, in the study of mobile phone networks, the frequency and length of interactions has often been used as measures of link weight (Onnela et al. 2007), (Hidalgo and Rodriguez-Sickert 1008), (Miritello et al. 2011). ❧
And they probably shouldn’t because typically different levels of people are making these decisions. Studio brass and producers typically have more to say about the lead roles and don’t care as much about the smaller ones which are overseen by casting directors or sometimes the producers. The only person who has oversight of all of them is the director, and even then they may quit caring at some point.
August 25, 2018 at 10:52PM
Social scientists explain link formation through two families of mechanisms; one that finds it roots in sociology and the other one in economics. The sociological approach assumes that link formation is connected to the characteristics of individuals and their context. Chief examples of the sociological approach include what I will call the big three sociological link-formation hypotheses. These are: shared social foci, triadic closure, and homophily. ❧
August 25, 2018 at 10:55PM
The social foci hypothesis predicts that links are more likely to form among individuals who, for example, are classmates, co-workers, or go to the same gym (they share a social foci). The triadic closure hypothesis predicts that links are more likely to form among individuals that share “friends” or acquaintances. Finally, the homophily hypothesis predicts that links are more likely to form among individuals who share social characteristics, such as tastes, cultural background, or physical appearance (Lazarsfeld and Merton 1954), (McPherson et al. 2001). ❧
definitions of social foci, triadic closure, and homophily within network science.
August 26, 2018 at 11:39AM
Yet, strategic games look for equilibrium in the formation and dissolution of ties in the context of the game theory advanced first by (Von Neumann et al. 2007), and later by (Nash 1950). ❧
August 25, 2018 at 10:58PM
Preferential attachment is the idea that connectivity begets connectivity. ❧
August 25, 2018 at 10:59PM
Preferential attachment is an idea advanced originally by the statisticians John Willis and Udny Yule in (Willis and Yule 1922), but has been rediscovered numerous times during the twentieth century. ❧
August 25, 2018 at 11:00PM
Rediscoveries of this idea in the twentieth century include the work of (Simon 1955) (who did cite Yule), (Merton 1968), (Price 1976) (who studied citation networks), and (Barabási and Albert 1999), who published the modern reference for this model, which is now widely known as the Barabasi-Albert model. ❧
August 25, 2018 at 11:01PM
preferential attachment. In the eyes of the social sciences, however, understanding which of all of these hypotheses drives the formation of the network is what one needs to explore. ❧
For example what drives attachment of political candidates?
August 26, 2018 at 08:15AM
Finally it is worth noting that trust, through the theory of social capital, has been connected with long-term economic growth—even though these results are based on regressions using extremely sparse datasets. ❧
And this is an example of how Trump is hurting the economy.
August 26, 2018 at 08:33AM
Nevertheless, the evidence suggests that social capital and social institutions are significant predictors of economic growth, after controlling for the effects of human capital and initial levels of income (Knack and Keefer 1997), (Knack 2002).4 So trust is a relevant dimension of social interactions that has been connected to individual dyads, network formation, labor markets, and even economic growth. ❧
August 26, 2018 at 08:35AM
Social scientist, on the other hand, have focused on what ties are more likely to bring in new information, which are primarily weak ties (Granovetter 1973), and on why weak ties bring new information (because they bridge structural holes (Burt 2001), (Burt 2005)). ❧
August 26, 2018 at 09:45AM
heterogeneous networks have been found to be effective promoters of the evolution of cooperation, since there are advantages to being a cooperator when you are a hub, and hubs tend to stabilize networks in equilibriums where levels of cooperation are high (Ohtsuki et al. 2006), (Pacheco et al. 2006), (Lieberman et al. 2005), (Santos and Pacheco 2005). ❧
August 26, 2018 at 09:49AM
These results, however, have also been challenged by human experiments finding no such effect (Gracia-Lázaro et al. 2012). The study of cooperation in networks has also been performed in dynamic settings, where individuals are allowed to cut ties (Wang et al. 2012), promoting cooperation, and are faced with different levels of knowledge about the reputation of peers in their network (Gallo and Yan 2015). Moreover, cooperating behavior has seen to spread when people change the networks where they participate in (Fowler and Christakis 2010). ❧
Open questions
August 26, 2018 at 09:50AM
References
👓 Mud Bath Spa Treatments: Everything You Need to Know | Groupon
Visiting a mud bath spa presents a paradox. How do you bathe in something that makes you dirty? And more importantly, why would you? The short answer: spending some time up to your neck in mud can be good for your skin. The longer answer, however, is a bit more nuanced and involves a closer look at fangotherapy—treatments that involve mud. Read on to learn some key mud bath facts, which may convince you to act like a pig at your next spa visit.
🔖 Science and Complexity by Warren Weaver
🔖 Economic Action and Social Structure: The Problem of Embeddedness | Mark Granovetter | American Journal of Sociology: Vol 91, No 3
How behavior and institutions are affected by social relations is one of the classic questions of social theory. This paper concerns the extent to which economic action is embedded in structures of social relations, in modern industrial society. Although the usual neoclasical accounts provide an "undersocialized" or atomized-actor explanation of such action, reformist economists who attempt to bring social structure back in do so in the "oversocialized" way criticized by Dennis Wrong. Under-and oversocialized accounts are paradoxically similar in their neglect of ongoing structures of social relations, and a sophisticated account of economic action must consider its embeddedness in such structures. The argument in illustrated by a critique of Oliver Williamson's "markets and hierarchies" research program.
🔖 An Experimental Study of the Small World Problem by Jeffrey Travers and Stanley Milgram | Sociometry
Arbitrarily selected individuals (N=296) in Nebraska and Boston are asked to generate acquaintance chains to a target person in Massachusetts, employing "the small world method" (Milgram, 1967). Sixty-four chains reach the target person. Within this group the mean number of intermediaries between starters and targets is 5.2. Boston starting chains reach the target person with fewer intermediaries than those starting in Nebraska; subpopulations in the Nebraska group do not differ among themselves. The funneling of chains through sociometric "stars" is noted, with 48 per cent of the chains passing through three persons before reaching the target. Applications of the method to studies of large scale social structure are discussed.
🔖 Trust: The Social Virtues and The Creation of Prosperity by Francis Fukuyama
In his bestselling The End of History and the Last Man, Francis Fukuyama argued that the end of the Cold War would also mean the beginning of a struggle for position in the rapidly emerging order of 21st-century capitalism. In Trust, a penetrating assessment of the emerging global economic order "after History," he explains the social principles of economic life and tells us what we need to know to win the coming struggle for world dominance. Challenging orthodoxies of both the left and right, Fukuyama examines a wide range of national cultures in order to divine the underlying principles that foster social and economic prosperity. Insisting that we cannot divorce economic life from cultural life, he contends that in an era when social capital may be as important as physical capital, only those societies with a high degree of social trust will be able to create the flexible, large-scale business organizations that are needed to compete in the new global economy. A brilliant study of the interconnectedness of economic life with cultural life, Trust is also an essential antidote to the increasing drift of American culture into extreme forms of individualism, which, if unchecked, will have dire consequences for the nation's economic health.
Given the large number of “Trust” and “Truth” related books being released this year, most in reference to Donald J. Trump’s administration, this might be an interesting read which takes him out of the equation and potentially better underlines the bigger problem we’re seeing in a growing anti-scientific leaning America?
🔖 Equilibrium points in n-person games by John Nash | PNAS
One may define a concept of an n-person game in which each player has a finite set of pure strategies and in which a definite set of payments to the n players corresponds to each n-tuple of pure strategies, one strategy being taken for each player. For mixed strategies, which are probability distributions over the pure strategies, the pay-off functions are the expectations of the players, thus becoming polylinear forms in the probabilities with which the various players play their various pure strategies.
Any n-tuple of strategies, one for each player, may be regarded as a point in the product space obtained by multiplying the n strategy spaces of the players. One such n-tuple counters another if the strategy of each player in the countering n-tuple yields the highest obtainable expectation for its player against the n − 1 strategies of the other players in the countered n-tuple. A self-countering n-tuple is called an equilibrium point.
The correspondence of each n-tuple with its set of countering n-tuples gives a one-to-many mapping of the product space into itself. From the definition of countering we see that the set of countering points of a point is convex. By using the continuity of the pay-off functions we see that the graph of the mapping is closed. The closedness is equivalent to saying: if P1, P2, … and Q1, Q2, …, Qn, … are sequences of points in the product space where Qn → Q, Pn → P and Qn counters Pn then Q counters P.
Since the graph is closed and since the image of each point under the mapping is convex, we infer from Kakutani’s theorem1 that the mapping has a fixed point (i.e., point contained in its image). Hence there is an equilibrium point.
In the two-person zero-sum case the “main theorem”2 and the existence of an equilibrium point are equivalent. In this case any two equilibrium points lead to the same expectations for the players, but this need not occur in general.
Communicated by S. Lefschetz, November 16, 1949
🔖 Some Statistics of Evolution and Geographical Distribution in Plants and Animals, and their Significance by J.C. Willis & Udny Yule | Nature
Abstract
IN a paper read at the Linnean Society under the above title on February 2, the statistical methods long employed in “Age and Area” were pushed to their final conclusion. Age and area (review in Ann. of Bot., October, 1921, p. 493) is the name given to a principle gradually discovered in many years of work upon the flora of Ceylon, which, in brief, affirms that if one take groups of not less than ten allied species and compare them with similar groups allied to the first, the relative total areas occupied in a given country, or in the world, will be more or less proportional (whether directly or not we do not yet know) to their relative total ages, within that country or absolutely, as the case may be. The longer a group has existed the more area will it occupy. Tens are compared in order to eliminate chance differences as much as possible, and allied groups to avoid as far as may be the complications introduced by different ecological habit, etc. Herbs, for example, probably spread much more rapidly than trees, but both will obey Age and Area. It is of course obvious that age of itself cannot effect dispersal, but inasmuch as predictions as to distribution of species, occurrence of endemics, etc., can be successfully made upon the basis of age alone, it is clear that the average rate of spreading of a given species, and still more of a group of allied species, is very uniform, and therefore affords a measure of age. The result of the work is to show that in general the species (and genera) of smallest areas are the youngest, and are descended from the more widespread species that usually occur beside them.
🔖 Emergence of Scaling in Random Networks by Albert-Laszlo Barabasi and Reka Albert | Science
Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.