Predicting Information Diffusion on Twitter - Analysis of predictive features

Information propagation on online social network focuses much attention in various domains as varied as politics, fact checking, or marketing. Modeling information diffusion in such growing communication media is crucial in order both to understand information propagation and to better control it. Our research aims at predicting whether a post is going to be forwarded or not. Moreover, we aim at predicting how much it is going to be diffused. Our model is based on three types of features: user-based, time-based and content-based. Using three collections corresponding to a total of about 16 millions of tweets, we show that our model improves of about 5% F-measure compared to the state of the art, both when predicting if a tweet is going to be re-tweeted and when predicting how popular it will be. F-measure in our model is between 70% and 82%, depending on the collection. We also show that some features we introduced are very important to predict retweetability such as the numbers of followers and number of communities that a user belongs to. Our contribution in this paper is twofold: firstly we defined new features to represent tweets in order to predict their possible propagation; secondly we evaluate the model we built on top of both features from the literature and features we defined on three collections and show the usefulness of our features in the prediction

Influences of the compressibility on aerodynamic characteristics of profile under the transonic flow theory

Transonic flows are complex problems. At certain Mach numbers, in gas flows there are local transitions from the subsonic into the supersonic and reciprocally, especially the discontinuity throughout shock waves. Subsonic flows and supersonic flows have very different properties, thus calculation methods are also different-the subsonic equation is elliptic and the supersonic equation is hyperbolic. Using established programs (based on the incompressible theory, the compressible theory and the transonic theory), we studied sub-transonic flow characteristics with variations of the Mach number. Our studies are also carried out with variations of incidence, which impact on t he transonic effect. Numerical results show that the local compressibility depends on not only the speed but also the incidence. At a rather great angle of attack, local supersonic regions can appear with free Mach numbers in the order of 0.3 - the Mach number is normally considered as a speed of incompressible flows. According to these results, we can recognize for which regime the local compressibility of flow is considerable and then it is necessary to consider the problem under the transonic flow theory

Types of momentum defect diffusion at the begining of the wake and wake establishment zone for the coupled wake and comparison with the isolated wake

The article [10] has presented the necessity of the classification into two types: Isolated wakes and coupled wakes. In this report, different types of momentum defect diffusion at the beginning of wake are analyzed for the two types of coupled wake and isolated wake. According to ·numerical results obtained, we analyses the existence - long or short - of the wake establishment zone before the wake established zone, and this zone is very different between isolated wake and coupled wake

Predicting Information Diffusion on Twitter - Analysis of predictive features

Information propagation on online social network focuses much attention in various domains as varied as politics, fact checking, or marketing. Modeling information diffusion in such growing communication media is crucial in order both to understand information propagation and to better control it. Our research aims at predicting whether a post is going to be forwarded or not. Moreover, we aim at predicting how much it is going to be diffused. Our model is based on three types of features: user-based, time-based and content-based. Using three collections corresponding to a total of about 16 millions of tweets, we show that our model improves of about 5% F-measure compared to the state of the art, both when predicting if a tweet is going to be re-tweeted and when predicting how popular it will be. F-measure in our model is between 70% and 82%, depending on the collection. We also show that some features we introduced are very important to predict retweetability such as the numbers of followers and number of communities that a user belongs to. Our contribution in this paper is twofold: firstly we defined new features to represent tweets in order to predict their possible propagation; secondly we evaluate the model we built on top of both features from the literature and features we defined on three collections and show the usefulness of our features in the prediction

Extraction de Localisations dans les MicroBlogs

La circulation de l’information est de plus en plus rapide. Les applications comme WhatsApp ou Twitter permettent d’échanger des informations sur des évènements de façon quasi instantanée. Il s’agit de ressources précieuses desquelles peuvent être extraites des informations sur des événements (temps, localisation ou entité concernée). Nous nous centrons ici sur l’aspect localisation qui a de nombreuses applications aussi bien dans le cadre d’outils géospatialisés que pour des recommandations personnalisées. Dans le contexte de microblogs, les outils développés en traitement du langage naturel ne sont pas suffisants compte tenu de la forme des messages; par exemple les tweets ne sont pas linguistiquement corrects. Par ailleurs, le nombre important de messages à traiter est également un challenge. Dans ce article, nous présentons un modèle pour prédire si un microblog (tweet) contient une localisation ou non et nous montrons que cette prédiction améliore l’efficacité de l’extraction de localisations des tweets

Calculation of transonic flows around profiles with blunt and angled leading edges

Transonic flow is a mixed flow of subsonic and supersonic regions. Because of this mixture, the solution of transonic flow problems is obtained only when solving the differential equations of motion with special treatments for the transition from subsonic region to supersonic region and vice versa. We built codes solving the full potential equation and Euler equations by applying the finite difference method and finite volume method, and also associated with software Fluent to consider the viscous effects. The analysis of results calculated for cases of transonic flow over profiles with blunt and angled leading edges shows more clearly the physical nature of the gas - solid interaction at leading edges in the mixed flow and the optimal application of each profile in transonic flows

Study of separation phenomenon in transonic flows produced by interaction between shock wave and boundary layer

For compressible flows, the transonic state depends on the geometry, Mach number and the incidence. This effect can produce shock wave. Some studies showed that the interaction between shock wave and boundary layer concerns separation phenomenon. Studies in this report demonstrate conditions of separation in transonic flow and that it is not any interaction between shock wave and boundary layer which can cause boundary layer separation. The studies also show that maximum Mach number in the local supersonic region is not a unique factor influencing the separation, and the separation in transonic flows can occur at the incidence of 0$^{\circ}$. For the calculation of viscous transonic flows, we use Fluent software with serious treatment of application operation based on the physical nature of phenomenon and the technique of numerical treatment. For the calculation of invicid transonic flows, we built a code solving the full potential equation with verification for accuracy. Results calculated from Fluent have been seriously compared with results of present program and published results in order to assure the accuracy of application operation in the domain of investigation. separation in transonic flows; shock wave and boundary laye

Corporate governance and firm performance: Evidence from Vietnamese listed companies

The research aims to provide empirical evidence on the relationship between corporate governance and firm performance in Vietnam – a developing economy in Asia. It focuses on the corporate governance of Vietnamese listed companies with a data-set of the five-year period from 2011 to 2015. Vietnamese listed companies are governed and controlled by two boards, Board of Directors and Supervisory Board. The research investigates the impacts of directors’ and supervisors’ characteristics and ownership structure on firm performance. The outcomes reveal that most governance mechanisms employed by Vietnamese listed companies were not effective and had no effect on the companies’ performance, except for managerial ownership and Supervisory Board size. Specifically, management ownership and firm performance were negatively correlated. Additional analyses show a positive relationship between the number of supervisors and firm performance, which was measured by market-based measurement

Musculoskeletal Pain and Work-related Risk Factors among Waste Collectors in Hanoi, Vietnam: A Cross-sectional Study

BACKGROUND: Musculoskeletal disorders (MSDs) are prevalent among waste collectors (WCs) in developing countries. AIM: This study aimed to investigate the prevalence of MSDs and the factors associated with the risk of persistent musculoskeletal pain among WCs in Hanoi, Vietnam. METHODS: A cross-sectional survey was utilized to study 468 WCs in 2017. The Örebro Musculoskeletal Pain Questionnaire and a questionnaire on demographic and work conditions were used to collect data. Descriptive and multivariate logistics regression analyzes were applied at a significance level of 0.05 to examine the factors related to the risk of persistent pain. FINDINGS: About 74.4% of the participants of this study experienced MSDs in at least one body region and 9.4% reported MSDs in all 10 body sites. The lower back was reported to be the most affected followed by the neck and shoulders. The risk of persistent musculoskeletal pain was significantly associated with age (odds ratio (OR) = 2.31, confidence interval (CI) = 1.05–5.09), gender (OR = 3.29, CI = 1.28–8.44), work hours (OR = 2.35, CI = 1.12–4.92), work shift (OR = 0.48, CI = 0.26–0.92), duration of poor postures of the neck (OR = 0.31, CI = 0.13–0.76), bent back (OR = 0.4 CI = 0.18–0.92) and for medial rotation (OR = 3.01, CI = 1.42–6.36), carrying heavy objects (OR = 2.94, CI = 1.15–7.48), and experience of work dissatisfaction (OR = 3.31, CI = 1.46-7.52), stress (OR = 7.14, CI = 3.14–16.24), or anxiety (OR = 6.37, CI = 3.07–13.21). CONCLUSIONS: High prevalence of MSDs among WCs and its association with self-assessed unfavorable work postures and work-related stress implies the need of mechanical and social support at work for WC to prevent the development of MSDs and persistent pain

Using Bioinformatics to predict potential targets of Microrna-144 in osteoarthritis

MicroRNAs are short endogenous non-coding RNA molecules, typically 19-25 nucleotides in length, which negatively regulate gene expression through binding to 3’UTR of target mRNAs, leading to repression of protein translation or target mRNA degradation. MicroRNA-144 (miR-144) was found as an abnormal expression in various diseases, including osteoarthritis (OA). We have identified increased microRNA-144 expression in early phase and end stage of OA. However, the molecular mechanism of this increase has not been yet to be determined yet. Using bioinformatics tools, we found more than 4,000 mRNAs that are predicted to be potential direct targets of miR-144, including mRNAs involved in the critical signaling pathways in OA e.g. TGFβ/Smad2/3 and WNT/β-catenin. Results from this research provide information for future ex periments to validate miR-144 potential targets