Identity and Search in Social Networks

Social networks have the surprising property of being "searchable": Ordinary people are capable of directing messages through their network of acquaintances to reach a specific but distant target person in only a few steps. We present a model that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions. Our model defines a class of searchable networks and a method for searching them that may be applicable to many network search problems, including the location of data files in peer-to-peer networks, pages on the World Wide Web, and information in distributed databases.Comment: 4 page, 3 figures, revte

Geometry of River Networks II: Distributions of Component Size and Number

The structure of a river network may be seen as a discrete set of nested sub-networks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length-scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.Comment: 16 pages, 13 figures, 4 tables, Revtex4, submitted to PR

Synergies and trade-offs between governance and costs in electricity system transition

Affordability and costs of an energy transition are often viewed as the most influential drivers. Conversely, multi-level transitions theory argues that governance and the choices of key actors, such as energy companies, government and civil society, drive the transition, not only on the basis of costs. This paper combines the two approaches and presents a cost appraisal of the UK transition to a low-carbon electricity system under alternate governance logics. A novel approach is used that links qualitative governance narratives with quantitative transition pathways (electricity system scenarios) and their appraisal. The results contrast the dominant market-led transition pathway (Market Rules) with alternate pathways that have either stronger governmental control elements (Central Co-ordination), or bottom-up proactive engagement of civil society (Thousand Flowers). Market Rules has the lowest investment costs by 2050. Central Co-ordination is more likely to deliver the energy policy goals and possibly even a synergistic reduction in the total system costs, if policies can be enacted and maintained. Thousand Flowers, which envisions wider participation of the society, comes at the expense of higher investment and total system costs. The paper closes with a discussion of the policy implications from cost drivers and the roles of market, government and society

Geometry of River Networks I: Scaling, Fluctuations, and Deviations

This article is the first in a series of three papers investigating the detailed geometry of river networks. Large-scale river networks mark an important class of two-dimensional branching networks, being not only of intrinsic interest but also a pervasive natural phenomenon. In the description of river network structure, scaling laws are uniformly observed. Reported values of scaling exponents vary suggesting that no unique set of scaling exponents exists. To improve this current understanding of scaling in river networks and to provide a fuller description of branching network structure, we report here a theoretical and empirical study of fluctuations about and deviations from scaling. We examine data for continent-scale river networks such as the Mississippi and the Amazon and draw inspiration from a simple model of directed, random networks. We center our investigations on the scaling of the length of sub-basin's dominant stream with its area, a characterization of basin shape known as Hack's law. We generalize this relationship to a joint probability density and show that fluctuations about scaling are substantial. We find strong deviations from scaling at small scales which can be explained by the existence of linear network structure. At intermediate scales, we find slow drifts in exponent values indicating that scaling is only approximately obeyed and that universality remains indeterminate. At large scales, we observe a breakdown in scaling due to decreasing sample space and correlations with overall basin shape. The extent of approximate scaling is significantly restricted by these deviations and will not be improved by increases in network resolution.Comment: 16 pages, 13 figures, Revtex4, submitted to PR

Optimizing Sequence Coverage for a Moderate Mass Protein in Nano-Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Sample pretreatment was optimized to obtain high sequence coverage for human serum albumin (HSA, 66.5 kDa) when using nano-electrospray ionization quadrupole time-of-flight mass spectrometry (nESI-Q-TOF-MS). Use of the final method with trypsin, Lys-C and Glu-C digests gave a combined coverage of 98.8%. The addition of peptide fractionation resulted in 99.7% coverage. These results were comparable to those obtained previously with matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The sample pretreatment/nESI-Q-TOF-MS method was also used with collision-induced dissociation to analyze HSA digests and to identify peptides that could be employed as internal mass calibrants in future studies of modifications to HSA

Optimizing Sequence Coverage for a Moderate Mass Protein in Nano-Electrospray Ionization Quadrupole Time-of-Flight Mass Spectrometry

Sample pretreatment was optimized to obtain high sequence coverage for human serum albumin (HSA, 66.5 kDa) when using nano-electrospray ionization quadrupole time-of-flight mass spectrometry (nESI-Q-TOF-MS). Use of the final method with trypsin, Lys-C and Glu-C digests gave a combined coverage of 98.8%. The addition of peptide fractionation resulted in 99.7% coverage. These results were comparable to those obtained previously with matrixassisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The sample pretreatment/nESI-Q-TOF-MS method was also used with collision-induced dissociation to analyze HSA digests and to identify peptides that could be employed as internal mass calibrants in future studies of modifications to HSA

Positivity of the English language

Over the last million years, human language has emerged and evolved as a fundamental instrument of social communication and semiotic representation. People use language in part to convey emotional information, leading to the central and contingent questions: (1) What is the emotional spectrum of natural language? and (2) Are natural languages neutrally, positively, or negatively biased? Here, we report that the human-perceived positivity of over 10,000 of the most frequently used English words exhibits a clear positive bias. More deeply, we characterize and quantify distributions of word positivity for four large and distinct corpora, demonstrating that their form is broadly invariant with respect to frequency of word use.Comment: Manuscript: 9 pages, 3 tables, 5 figures; Supplementary Information: 12 pages, 3 tables, 8 figure

Acceptability of HIV self-sampling kits (TINY vial) among people of black African ethnicity in the UK: a qualitative study

Background: Increasing routine HIV testing among key populations is a public health imperative, so improving access to acceptable testing options for those in need is a priority. Despite increasing targeted distribution and uptake of HIV self-sampling kits (SSKs) among men who have sex with men in the UK, little is known about why targeted SSK interventions for black African users are not as wide-spread or well-used. This paper addresses this key gap, offering insight into why some groups may be less likely than others to adopt certain types of SSK interventions in particular contexts. These data were collected during the development phase of a larger study to explore the feasibility and acceptability of targeted distribution of SSKs to black African people. Methods: We undertook 6 focus groups with members of the public who self-identified as black African (n = 48), 6 groups with specialists providing HIV and social services to black African people (n = 53), and interviews with HIV specialist consultants and policy-makers (n = 9). Framework analysis was undertaken, using inductive and deductive analysis to develop and check themes. Results: We found three valuable components of targeted SSK interventions for this population: the use of settings and technologies that increase choice and autonomy; targeted offers of HIV testing that preserve privacy and do not exacerbate HIV stigma; and ensuring that the specific kit being used (in this case, the TINY vial) is perceived as simple and reliable. Conclusions: This unique and rigorous research offers insights into participants’ views on SSK interventions, offering key considerations when targeting this population.. Given the plethora of HIV testing options, our work demonstrates that those commissioning and delivering SSK interventions will need to clarify (for users and providers) how each kit type and intervention design adds value. Most significantly, these findings demonstrate that without a strong locus of control over their own circumstances and personal information, black African people are less likely to feel that they can pursue an HIV test that is safe and secure. Thus, where profound social inequalities persist, so will inequalities in HIV testing uptake – by any means

Reinforcement-Driven Spread of Innovations and Fads

We propose kinetic models for the spread of permanent innovations and transient fads by the mechanism of social reinforcement. Each individual can be in one of M+1 states of awareness 0,1,2,...,M, with state M corresponding to adopting an innovation. An individual with awareness k<M increases to k+1 by interacting with an adopter. Starting with a single adopter, the time for an initially unaware population of size N to adopt a permanent innovation grows as ln(N) for M=1, and as N^{1-1/M} for M>1. The fraction of the population that remains clueless about a transient fad after it has come and gone changes discontinuously as a function of the fad abandonment rate lambda for M>1. The fad dies out completely in a time that varies non-monotonically with lambda.Comment: 4 pages, 2 columns, 5 figures, revtex 4-1 format; revised version has been expanded and put into iop format, with one figure adde

Influence Diffusion in Social Networks under Time Window Constraints

We study a combinatorial model of the spread of influence in networks that generalizes existing schemata recently proposed in the literature. In our model, agents change behaviors/opinions on the basis of information collected from their neighbors in a time interval of bounded size whereas agents are assumed to have unbounded memory in previously studied scenarios. In our mathematical framework, one is given a network $G=(V,E)$, an integer value $t(v)$ for each node $v\in V$, and a time window size $\lambda$. The goal is to determine a small set of nodes (target set) that influences the whole graph. The spread of influence proceeds in rounds as follows: initially all nodes in the target set are influenced; subsequently, in each round, any uninfluenced node $v$ becomes influenced if the number of its neighbors that have been influenced in the previous $\lambda$ rounds is greater than or equal to $t(v)$. We prove that the problem of finding a minimum cardinality target set that influences the whole network $G$ is hard to approximate within a polylogarithmic factor. On the positive side, we design exact polynomial time algorithms for paths, rings, trees, and complete graphs.Comment: An extended abstract of a preliminary version of this paper appeared in: Proceedings of 20th International Colloquium on Structural Information and Communication Complexity (Sirocco 2013), Lectures Notes in Computer Science vol. 8179, T. Moscibroda and A.A. Rescigno (Eds.), pp. 141-152, 201