Assembling thefacebook: Using heterogeneity to understand online social network assembly

Online social networks represent a popular and diverse class of social media systems. Despite this variety, each of these systems undergoes a general process of online social network assembly, which represents the complicated and heterogeneous changes that transform newly born systems into mature platforms. However, little is known about this process. For example, how much of a network's assembly is driven by simple growth? How does a network's structure change as it matures? How does network structure vary with adoption rates and user heterogeneity, and do these properties play different roles at different points in the assembly? We investigate these and other questions using a unique dataset of online connections among the roughly one million users at the first 100 colleges admitted to Facebook, captured just 20 months after its launch. We first show that different vintages and adoption rates across this population of networks reveal temporal dynamics of the assembly process, and that assembly is only loosely related to network growth. We then exploit natural experiments embedded in this dataset and complementary data obtained via Internet archaeology to show that different subnetworks matured at different rates toward similar end states. These results shed light on the processes and patterns of online social network assembly, and may facilitate more effective design for online social systems.Comment: 13 pages, 11 figures, Proceedings of the 7th Annual ACM Web Science Conference (WebSci), 201

Competition and Selection Among Conventions

In many domains, a latent competition among different conventions determines which one will come to dominate. One sees such effects in the success of community jargon, of competing frames in political rhetoric, or of terminology in technical contexts. These effects have become widespread in the online domain, where the data offers the potential to study competition among conventions at a fine-grained level. In analyzing the dynamics of conventions over time, however, even with detailed on-line data, one encounters two significant challenges. First, as conventions evolve, the underlying substance of their meaning tends to change as well; and such substantive changes confound investigations of social effects. Second, the selection of a convention takes place through the complex interactions of individuals within a community, and contention between the users of competing conventions plays a key role in the convention's evolution. Any analysis must take place in the presence of these two issues. In this work we study a setting in which we can cleanly track the competition among conventions. Our analysis is based on the spread of low-level authoring conventions in the eprint arXiv over 24 years: by tracking the spread of macros and other author-defined conventions, we are able to study conventions that vary even as the underlying meaning remains constant. We find that the interaction among co-authors over time plays a crucial role in the selection of them; the distinction between more and less experienced members of the community, and the distinction between conventions with visible versus invisible effects, are both central to the underlying processes. Through our analysis we make predictions at the population level about the ultimate success of different synonymous conventions over time--and at the individual level about the outcome of "fights" between people over convention choices.Comment: To appear in Proceedings of WWW 2017, data at https://github.com/CornellNLP/Macro

Perspectives of the Apiaceae Hepatoprotective Effects - A Review

The liver has the crucial role in the regulation of various physiological processes and in the excretion of endogenous waste metabolites and xenobiotics. Liver structure impairment can be caused by various factors including microorganisms, autoimmune diseases, chemicals, alcohol and drugs. The plant kingdom is full of liver protective chemicals such as phenols, coumarins, lignans, essential oils, monoterpenes, carotenoids, glycosides, flavonoids, organic acids, lipids, alkaloids and xanthenes. Apiaceae plants are usually used as a vegetable or as a spice, but their other functional properties are also very important. This review highlights the significance of caraway, dill, cumin, aniseed, fennel, coriander, celery, lovage, angelica, parsley and carrot, which are popular vegetables and spices, but possess hepatoprotective potential. These plants can be used for medicinal applications to patients who suffer from liver damage

Stabilite et conditionnement de problemes de points-selles et loi des grands nombres en analyse epi/hypographique

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : T 81284 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

iPhone's Digital Marketplace

With mobile shopping surging in popularity, people are spending ever more money on digital purchases through their mobile devices and phones. However, few large-scale studies of mobile shopping exist. In this paper we analyze a large data set consisting of more than 776M digital purchases made on Apple mobile devices that include songs, apps, and in-app purchases. We find that 61% of all the spending is on in-app purchases and that the top 1% of users are responsible for 59% of all the spending. These big spenders are more likely to be male and older, and less likely to be from the US. We study how they adopt and abandon individual app, and find that, after an initial phase of increased daily spending, users gradually lose interest: the delay between their purchases increases and the spending decreases with a sharp drop toward the end. Finally, we model the in-app purchasing behavior in multiple steps: 1) we model the time between purchases; 2) we train a classifier to predict whether the user will make a purchase from a new app or continue purchasing from the existing app; and 3) based on the outcome of the previous step, we attempt to predict the exact app, new or existing, from which the next purchase will come. The results yield new insights into spending habits in the mobile digital marketplace.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM 2017), Cambridge, UK. 9 pages, 12 figure

Main Polymorphisms in Aspirin-Exacerbated Respiratory Disease

Aspirin exacerbated respiratory disease (AERD) is a condition caused by increased bronchoconstriction in people with asthma after taking aspirin or another NSAID. Molecular analysis of the human genome has opened up new perspectives on human polymorphisms and disease. This study was conducted to identify the genetic factors that influence this disease due to its unknown genetic factors. We evaluated research studies, letters, comments, editorials, eBooks, and reviews. PubMed/MEDLINE, Web of Sciences, Cochrane Library, and Scopus were searched for information. We used the keywords polymorphisms, aspirin-exacerbated respiratory disease, asthma, allergy as search terms. This study included 38 studies. AERD complications were associated with polymorphisms in ALOX15, EP2, ADRB2, SLC6A12, CCR3, CRTH2, CysLTs, DPCR1, DPP10, FPR2, HSP70, IL8, IL1B, IL5RA, IL-13, IL17RA, ILVBL, TBXA2R, TLR3, HLA-DRB and HLA-DQ, HLA-DR7, HLA-DP. AERD was associated with heterogeneity in gene polymorphisms, making it difficult to pinpoint specific gene changes. Therefore, diagnosing and treating AERD may be facilitated by examining common variants involving the disease