Multilinguals and Wikipedia Editing

This article analyzes one month of edits to Wikipedia in order to examine the role of users editing multiple language editions (referred to as multilingual users). Such multilingual users may serve an important function in diffusing information across different language editions of the encyclopedia, and prior work has suggested this could reduce the level of self-focus bias in each edition. This study finds multilingual users are much more active than their single-edition (monolingual) counterparts. They are found in all language editions, but smaller-sized editions with fewer users have a higher percentage of multilingual users than larger-sized editions. About a quarter of multilingual users always edit the same articles in multiple languages, while just over 40% of multilingual users edit different articles in different languages. When non-English users do edit a second language edition, that edition is most frequently English. Nonetheless, several regional and linguistic cross-editing patterns are also present

Modeling the Rise in Internet-based Petitions

Contemporary collective action, much of which involves social media and other Internet-based platforms, leaves a digital imprint which may be harvested to better understand the dynamics of mobilization. Petition signing is an example of collective action which has gained in popularity with rising use of social media and provides such data for the whole population of petition signatories for a given platform. This paper tracks the growth curves of all 20,000 petitions to the UK government over 18 months, analyzing the rate of growth and outreach mechanism. Previous research has suggested the importance of the first day to the ultimate success of a petition, but has not examined early growth within that day, made possible here through hourly resolution in the data. The analysis shows that the vast majority of petitions do not achieve any measure of success; over 99 percent fail to get the 10,000 signatures required for an official response and only 0.1 percent attain the 100,000 required for a parliamentary debate. We analyze the data through a multiplicative process model framework to explain the heterogeneous growth of signatures at the population level. We define and measure an average outreach factor for petitions and show that it decays very fast (reducing to 0.1% after 10 hours). After 24 hours, a petition's fate is virtually set. The findings seem to challenge conventional analyses of collective action from economics and political science, where the production function has been assumed to follow an S-shaped curve.Comment: Submitted to EPJ Data Scienc

Role of the Thrombospondin - CD36 - Histidine Rich Glycoprotein Pathway in Tumor Growth and Angiogenesis

Cancer is typically thought of as an uncommon disease, in which solid tumors require a blood supply in order to grow and metastasize. Interestingly, upon autopsy a large portion of elderly individuals display numerous non-vascularized lesions throughout their bodies. Thus, the angiogenic switch in the development of cancer presents an important therapeutic target. Previous work by our laboratory has established an interaction between CD36, Histidine Rich Glycoprotein (HRGP) and Thrombospondin 1 (TSP-1) in the modulation of angiogenesis. Briefly, endothelial cell receptor CD36 interaction with soluble or cell bound TSP-1 leads to the induction of an apoptotic signaling cascade in vascular endothelial cells resulting in decreased proliferation, migration and tube formation, thereby inhibiting angiogenesis. Presence of soluble HRGP leads to inhibition of the anti-angiogenic potential of the CD36-TSP-1 pathway through a decoy receptor function whereby TSP-1is bound and sequestered. Previous studies have focused on this pathway with regards to wound healing. However, pathologically relevant modulation of angiogenesis is also observed in tumors. In the current work we evaluate the role of the CD36-TSP-HRGP pathway in tumor growth and angiogenesis. Further, we examine a possible processing mechanism by which TSP function may be modulated by a matrix metalloprotease, ADAMTS1.Chapters two through five will outline the role of the TSP-CD36 axis in tumor biology, namely angiogenesis and growth. We will also address modulation of this pathway via HRGP. Further we will describe a matrix metalloprotease mechanism by which TSP function may be regulate

FlashLight: A Dynamic Detector of Shared State, Race Conditions, and Locking Models in Concurrent Java Programs

Concurrent Java programs are difficult to understand and implement correctly. This difficultly leads to code faults that are the source of many real-world reliability and security problems. Many factors contribute to concurrency faults in Java code; for example, programmers may not understand Java language semantics or, when using a Java library or framework, may not understand that their resulting program is concurrent. This thesis describes a dynamic analysis tool, named FlashLight, that detects shared state and possible race conditions within a program. FlashLight illuminates the concurrency within a program for programmers who are wholly or partially in the dark about their software\u27s concurrency. FlashLight also works in concert with the Fluid assurance tool to propose Greenhouse-style lock policy models based on a program\u27s observed locking behavior. After review by a programmer to ensure reasonableness, these models can be verified by the Fluid assurance tool. The author\u27s combination of a dynamic tool with a program verification system focused on concurrency fault detection and repair is the primary contribution of this research. He applied FlashLight to several concurrent Java programs, including a large commercial web application server. His case study experiences induced him to improve FlashLight to do the following: (1) allow the programmer to specify interesting time quantums (e.g., this is the start-up phase of the program), and (2) support the common Java programming idiom of not locking shared state during object construction. Both improvements help to reduce false positives. FlashLight introduces an overhead of roughly 1.7 times the original execution time of the program. The most significant limitation of FlashLight is that it is not fully integrated into the Fluid assurance tool with respect to the user experience

Numerical investigation of a binary solidification design problem

This exposition presents the development and application of a methodology for control of unidirectional solidification of a binary alloy. In particular, it is desired to produce a casting that has a uniform cast structure throughout its entire length. Furthermore, the methodology allows the specification, a priori, of the cast structure with respect to both scale, i.e., fine or coarse, and mor- phology, i.e., dentritic or cellular. This specification is in the form of a map that relates solidification characteristics, i.e., scale and morphology, to the solidification velocity and liquid-side interfacial temperature gradient. Thus design is accomplished by controlling these two parameters during the solidification process. With this in mind, the goal of what is termed the binary solidification design problem is the prediction of a set of boundary temperatures and heat fluxes which when applied will result in the desired interfacial motion and temperature gradient and therefore cast structure. Mathematical models for problems of this type lead to what are termed ill-posed systems in that they may not exhibit existence, uniqueness, or continuous dependence on boundary data. The resolution of this class of problems requires advanced techniques to overcome the instabilities encountered due to their ill-posed nature. The methodology developed herein employs the classical weight residual approach in a innovative manner. Normally, in the solution of a parabolic partial differential equation, such as the heat equation, a spatial series expansion with time varying coefficients is utilized along with a minimiza- tion technique to reduce the partial differential equation to a set of first order ordinary differential equations. This set can be solved using any number of numerical technique, i.e, Runge-Kutta, to obtain the temporal variation of the coefficientsThese types of time stepping techniques eventually lead to the onset of instability when employed for the resolution of ill-posed problems due to the build-up of round-off errors. In this exposition, time stepping is replaced by the further expansion of the time varying expansion coefficients into a series unto itself. Minimization in both space and time is simultaneously applied leading to a set of algebraic equations whose solution leads to the resolution of the entire space-time domain. This treatment of time in an elliptic fashion stabilizes the solution of the ill-posed problem and forms the basis of what is termed the Global Time Method, GTM. The results obtained for the control boundaries indicate that the control measures required to accomplish the design solidification are not only physically realistic but relatively undemanding to implement. Furthermore, under the design solidification conditions, it was observed that once formed, a mushy zone of constant thickness was maintained throughout the transient. This observation gave rise to a quasi-steady state analysis of the mushy zone which lead to the development of a set of design tools

Measuring relative opinion from location-based social media: A case study of the 2016 U.S. presidential election

Social media has become an emerging alternative to opinion polls for public opinion collection, while it is still posing many challenges as a passive data source, such as structurelessness, quantifiability, and representativeness. Social media data with geotags provide new opportunities to unveil the geographic locations of users expressing their opinions. This paper aims to answer two questions: 1) whether quantifiable measurement of public opinion can be obtained from social media and 2) whether it can produce better or complementary measures compared to opinion polls. This research proposes a novel approach to measure the relative opinion of Twitter users towards public issues in order to accommodate more complex opinion structures and take advantage of the geography pertaining to the public issues. To ensure that this new measure is technically feasible, a modeling framework is developed including building a training dataset by adopting a state-of-the-art approach and devising a new deep learning method called Opinion-Oriented Word Embedding. With a case study of the tweets selected for the 2016 U.S. presidential election, we demonstrate the predictive superiority of our relative opinion approach and we show how it can aid visual analytics and support opinion predictions. Although the relative opinion measure is proved to be more robust compared to polling, our study also suggests that the former can advantageously complement the later in opinion prediction

Does Campaigning on Social Media Make a Difference? Evidence from candidate use of Twitter during the 2015 and 2017 UK Elections

Social media are now a routine part of political campaigns all over the world. However, studies of the impact of campaigning on social platform have thus far been limited to cross-sectional datasets from one election period which are vulnerable to unobserved variable bias. Hence empirical evidence on the effectiveness of political social media activity is thin. We address this deficit by analysing a novel panel dataset of political Twitter activity in the 2015 and 2017 elections in the United Kingdom. We find that Twitter based campaigning does seem to help win votes, a finding which is consistent across a variety of different model specifications including a first difference regression. The impact of Twitter use is small in absolute terms, though comparable with that of campaign spending. Our data also support the idea that effects are mediated through other communication channels, hence challenging the relevance of engaging in an interactive fashion