Suchergebnisse

This book offers a rich collection of re- search papers on very important top- ics: the much discussed revolution in military affairs (RMA), and the less dis- cussed diffusions of new military tech- nology and the accompanying changes in military doctrine to other countries. The authors were carefully chosen ex- perts in history, political science, and sociology, who address the very impor- tant factors of national culture as they affect the application of new military technologies.

Recent commentary points to clear increases in ideological polarization between the major American political parties. We review the theoretical & empirical literature on party polarization & partisan change. We begin by comparing the current period both to earlier political eras & to theories of partisan change. We argue that in the current period the parties have grown increasingly divided on all the major policy dimensions in American politics -- a process that we term conflict extension. We discuss various perspectives on increases in polarization between the parties in government, the parties in the electorate, & the parties' activists, & we consider the causal links between polarization at each of these levels. We consider whether American society itself, & not just the parties & their identifiers, has become increasingly polarized. Finally, we discuss the consequences of growing party polarization for American political life. Figures, References. Adapted from the source document.

Microblog service (such as Twitter and Sina Weibo) have become an important platform for Internet content sharing. As the information in Microblog are widely used in public opinion mining, viral marketing and political campaigns, understanding how information diffuses over Microblogs, and explaining the process through which some tweets become popular, are important.The analysis of the information diffusion in Microblogs involves the data collection from Microblog, the modeling on information spreading and using the resulting models. Dealing with the huge amount of data flowing through microblogs is by itself a challenge. Designing an efficient and unbiased sampling algorithm for Microblog is therefore essential. Besides, the retweeting process in Microblog is complex because of the ephemerality of information, the topology of Microblog network and the particular features (such as number of followers) of publisher and retweeters.Two traditional models have been used for information diffusion : Independent Cascades and Linear Threshold models. However no one of them can describe completely the retweeting process in Microblog accurately. The analysis and design of new models to characterize the information diffusion in Microblog is therefore necessary. Moreover, a comprehensive description of the correlation between the information diffusion in Microblog and the searching trends of keywords on search engines is lacking although some work has been found some preliminary relationships.This work presnets a complete analysis of information diffusion in Microblog from. The contributions and innovations of this thesis are as follows:1)There are two popular unbiased Online Social Network (OSN) sampling algorithms,Metropolis-Hastings Random Walk (MHRW) and Unbiased Sampling for Directed Social Graph (USDSG) method. However they are both likely to yield considerable self-sampling probabilities when applied to Microblogs where there is local. To solve this problem, I have modelled the process of OSN sampling as a Markov process and have deduced the sufficient and necessary conditions of unbiased sampling. Based on this unbiased conditions, I proposed an efficient and unbiased sampling algorithms, Unbiased Sampling method with Dummy Edges (USDE), which reduces strongly the self-sampling probabilities of MHRW. The experimental evaluation demonstrate thats the average node degree of samples of MHRW and USDSG is 2 - 4 times as high as the ground truth while USDE can provide the approximation of ground truth when the sampling repetitions are removed. Moreover the average sampling time per node in USDE is only a half of MHRW and USDSG one.2)A second contribution targets the shortages of Independent Cascades (IC) and Linear Threshold (LT) models in characterizing the retweeting process in Microblogs. I achieve this by introducing a Galton Watson with Killing (GWK) model which considers all the three important factors including the ephemerality of information, the topology of network and the features of publisher and retweeters accurately. We have validated the applicability of the of GWK model over two datasets from Sina Weibo and Twitter and showed that GWK model can fit 82% of information receivers and 90% of the maximum numbers of hops in the real retweeting process. Besides, the GWK model is useful for revealing the endogenous and exogenous factors which affect the popularity of tweets.3) Motivated by the correlation between popularity and trendiness of topicsin Microblog and search trends, I have developed an economic analysis of the market involving a third-party ad broker, which is a popular market in current SEM, and finds that the adwords augmenting strategy with the trending and popular topics in Twitter enables the broker to achieve, on average, four folds larger return on investment than with a non-augmented strategy, while still maintaining the same level of risk. ; Les services de microblogging (comme Twitter ou Sina Weibo) sont devenu ces dernières années des plateformes très importantes de partage d'information sur l'Internet. Les microblogs sont fréquemment utilisé pour l'analyse de l'opinion, le marketing viral, et les campagnes politiques. Comprendre les mécanismes sous-jacents de la diffusion d'information sur les microblogs et comment des contenus deviennent populaires est important.L'analyse de la diffusion d'information dans les microblogs nécessite la collecte de donnée des microblogs, la modélisation de la diffusion d'information et l'application des modèles résultants. Traiter les données massives issues des microblogs est un défi en soi. Concevoir des algorithmes efficaces et sans biais afin d'échantillonner les microblogs est ainsi fondamental. Ceci doit prendre en compte la complexité du phénomène de « retweet » qui dépend de la valeur éphémère de l'information, de la topologie du réseau de microblogging et des caractéristiques particulières des éditeurs et retweeteurs.Deux modèles ont été traditionnellement appliqués à la diffusion d'information : les cascades indépendantes et modèle à seuil linéaire. Aucun de ces deux modèles n'est à même de décrire le processus du retweeting de façon correcte. Il devient donc nécessaire de de caractériser la diffusion d'information. De plus, une description complète de la relation entre la diffusion d'information dans les microblogs et de popularité des termes recherchés sur Internet serait utile.Ces travaux de thèse présentent une analyse complète de la diffusion d'information dans les microblogs. Les contributions ce cette thèse sont les suivantes :1) Il y'a deux technique d'échantillonnage sans biais pour les réseaux sociaux : la marche aléatoire de Métropolis-Hastings (MHRW), et la méthode d'échantillonnage sans biais de graphes dirigés (USDSG). Néanmoins ces deux méthodes peuvent aboutit à un taux important d'auto-échantillonnage quand elles sont appliquées à des microblogs. Pour résoudre ce problème, j'ai modélisé l'échantillonnage d'un OSN par un processus de Markov et j'en ai déduit les conditions nécessaires et suffisantes d'un échantillonnage sans biais. Ces conditions m'ont permis de proposer un algorithme d'échantillonnage sans biais et efficace que j'ai nommé : échantillonnage sans biais par liens vide (USDE). Cette nouvelle méthode d'échantillonage réduit fortement l'auto-échantillonnage du MHRW. L 'évaluation empirique montre que la moyenne des dégrées des nœuds échantillonnés est proche de la vérité terrain alors que pour MHRW et USDSG elle est 2 à 4 fois supérieure.2) La seconde contribution de cette thèse vise les lacunes des modèles en cascades indépendantes et de seuils linéaires. J'ai développé un modèle fondé sur les processus de Galton-Watson avec mort (GWK) qui prennent en compte tous les facteurs importants du processus de retweet. Ce nouveau modèle est validé par une application sur des données issues de Twitter et de Weibo.3) La troisième contribution est relative au développement d'un modèle économique du marché des acteurs actifs dans le domaine du marketing sur les mots clés dans les sites de recherches. J'ai développé des méthodes de gestion de portfolios de mots clés et montrés que ces portfolios permettent d'améliorer fortement les rendements sans augmenter le niveau de risque.

Microblog service (such as Twitter and Sina Weibo) have become an important platform for Internet content sharing. As the information in Microblog are widely used in public opinion mining, viral marketing and political campaigns, understanding how information diffuses over Microblogs, and explaining the process through which some tweets become popular, are important.The analysis of the information diffusion in Microblogs involves the data collection from Microblog, the modeling on information spreading and using the resulting models. Dealing with the huge amount of data flowing through microblogs is by itself a challenge. Designing an efficient and unbiased sampling algorithm for Microblog is therefore essential. Besides, the retweeting process in Microblog is complex because of the ephemerality of information, the topology of Microblog network and the particular features (such as number of followers) of publisher and retweeters.Two traditional models have been used for information diffusion : Independent Cascades and Linear Threshold models. However no one of them can describe completely the retweeting process in Microblog accurately. The analysis and design of new models to characterize the information diffusion in Microblog is therefore necessary. Moreover, a comprehensive description of the correlation between the information diffusion in Microblog and the searching trends of keywords on search engines is lacking although some work has been found some preliminary relationships.This work presnets a complete analysis of information diffusion in Microblog from. The contributions and innovations of this thesis are as follows:1)There are two popular unbiased Online Social Network (OSN) sampling algorithms,Metropolis-Hastings Random Walk (MHRW) and Unbiased Sampling for Directed Social Graph (USDSG) method. However they are both likely to yield considerable self-sampling probabilities when applied to Microblogs where there is local. To solve this problem, I have modelled the process of OSN sampling as a Markov process and have deduced the sufficient and necessary conditions of unbiased sampling. Based on this unbiased conditions, I proposed an efficient and unbiased sampling algorithms, Unbiased Sampling method with Dummy Edges (USDE), which reduces strongly the self-sampling probabilities of MHRW. The experimental evaluation demonstrate thats the average node degree of samples of MHRW and USDSG is 2 - 4 times as high as the ground truth while USDE can provide the approximation of ground truth when the sampling repetitions are removed. Moreover the average sampling time per node in USDE is only a half of MHRW and USDSG one.2)A second contribution targets the shortages of Independent Cascades (IC) and Linear Threshold (LT) models in characterizing the retweeting process in Microblogs. I achieve this by introducing a Galton Watson with Killing (GWK) model which considers all the three important factors including the ephemerality of information, the topology of network and the features of publisher and retweeters accurately. We have validated the applicability of the of GWK model over two datasets from Sina Weibo and Twitter and showed that GWK model can fit 82% of information receivers and 90% of the maximum numbers of hops in the real retweeting process. Besides, the GWK model is useful for revealing the endogenous and exogenous factors which affect the popularity of tweets.3) Motivated by the correlation between popularity and trendiness of topicsin Microblog and search trends, I have developed an economic analysis of the market involving a third-party ad broker, which is a popular market in current SEM, and finds that the adwords augmenting strategy with the trending and popular topics in Twitter enables the broker to achieve, on average, four folds larger return on investment than with a non-augmented strategy, while still maintaining the same level of risk. ; Les services de microblogging (comme Twitter ou Sina Weibo) sont devenu ces dernières années des plateformes très importantes de partage d'information sur l'Internet. Les microblogs sont fréquemment utilisé pour l'analyse de l'opinion, le marketing viral, et les campagnes politiques. Comprendre les mécanismes sous-jacents de la diffusion d'information sur les microblogs et comment des contenus deviennent populaires est important.L'analyse de la diffusion d'information dans les microblogs nécessite la collecte de donnée des microblogs, la modélisation de la diffusion d'information et l'application des modèles résultants. Traiter les données massives issues des microblogs est un défi en soi. Concevoir des algorithmes efficaces et sans biais afin d'échantillonner les microblogs est ainsi fondamental. Ceci doit prendre en compte la complexité du phénomène de « retweet » qui dépend de la valeur éphémère de l'information, de la topologie du réseau de microblogging et des caractéristiques particulières des éditeurs et retweeteurs.Deux modèles ont été traditionnellement appliqués à la diffusion d'information : les cascades indépendantes et modèle à seuil linéaire. Aucun de ces deux modèles n'est à même de décrire le processus du retweeting de façon correcte. Il devient donc nécessaire de de caractériser la diffusion d'information. De plus, une description complète de la relation entre la diffusion d'information dans les microblogs et de popularité des termes recherchés sur Internet serait utile.Ces travaux de thèse présentent une analyse complète de la diffusion d'information dans les microblogs. Les contributions ce cette thèse sont les suivantes :1) Il y'a deux technique d'échantillonnage sans biais pour les réseaux sociaux : la marche aléatoire de Métropolis-Hastings (MHRW), et la méthode d'échantillonnage sans biais de graphes dirigés (USDSG). Néanmoins ces deux méthodes peuvent aboutit à un taux important d'auto-échantillonnage quand elles sont appliquées à des microblogs. Pour résoudre ce problème, j'ai modélisé l'échantillonnage d'un OSN par un processus de Markov et j'en ai déduit les conditions nécessaires et suffisantes d'un échantillonnage sans biais. Ces conditions m'ont permis de proposer un algorithme d'échantillonnage sans biais et efficace que j'ai nommé : échantillonnage sans biais par liens vide (USDE). Cette nouvelle méthode d'échantillonage réduit fortement l'auto-échantillonnage du MHRW. L 'évaluation empirique montre que la moyenne des dégrées des nœuds échantillonnés est proche de la vérité terrain alors que pour MHRW et USDSG elle est 2 à 4 fois supérieure.2) La seconde contribution de cette thèse vise les lacunes des modèles en cascades indépendantes et de seuils linéaires. J'ai développé un modèle fondé sur les processus de Galton-Watson avec mort (GWK) qui prennent en compte tous les facteurs importants du processus de retweet. Ce nouveau modèle est validé par une application sur des données issues de Twitter et de Weibo.3) La troisième contribution est relative au développement d'un modèle économique du marché des acteurs actifs dans le domaine du marketing sur les mots clés dans les sites de recherches. J'ai développé des méthodes de gestion de portfolios de mots clés et montrés que ces portfolios permettent d'améliorer fortement les rendements sans augmenter le niveau de risque.

People have a tendency to disregard information that contradicts their partisan or ideological identity. This inclination can become especially striking when citizens reject notions that scientists would consider "facts" in the light of overwhelming scientific evidence and consensus. The resulting polarization over science has reached alarming levels in recent years. This theoretical review conceptualizes political polarization over science and argues that it is driven by two interrelated processes. Through psychological science rejection, people can implicitly disregard scientific facts that are inconsistent with their political identity. Alternatively, citizens can engage in ideological science rejection by adhering to a political ideology that explicitly contests science. This contestation can in turn be subdivided into four levels of generalization: An ideology can dispute either specific scientific claims, distinct research fields, science in general, or the entire political system and elite. By proposing this interdisciplinary framework, this article aims to integrate insights from various disciplines.

This book investigates recent public debates about the European Union (EU) in national parliaments, which have become the primary arena for public debate about the EU. Responding to claims about a politicization of European governance, the author investigates the link between two dimensions of debate - the discursive justification and party political contestation of decision-making in the EU. Embedded in a comparison between the legislatures of four Member States (Austria, France, Germany, and the United Kingdom), the main finding of the book is that generalizable links can be identified between the use of different argumentative frames and patterns of party political polarization. These insights help to clarify the context conditions in which patterns of left/right and government/opposition politics are replaced by more atypical forms of polarization. In a comparative perspective, the author demonstrates that party political factors are a more relevant factor for variation than thematic or country-specific cultural or institutional factors. Case studies include debates on EU Treaty Reform, the Eurozone crisis, and EU enlargement

This book investigates recent public debates about the European Union (EU) in national parliaments, which have become the primary arena for public debate about the EU. Responding to claims about a politicization of European governance, the author investigates the link between two dimensions of debate - the discursive justification and party political contestation of decision-making in the EU. Embedded in a comparison between the legislatures of four Member States (Austria, France, Germany, and the United Kingdom), the main finding of the book is that generalizable links can be identified between the use of different argumentative frames and patterns of party political polarization. These insights help to clarify the context conditions in which patterns of left/right and government/opposition politics are replaced by more atypical forms of polarization. In a comparative perspective, the author demonstrates that party political factors are a more relevant factor for variation than thematic or country-specific cultural or institutional factors. Case studies include debates on EU Treaty Reform, the Eurozone crisis, and EU enlargement.

What makes people affectively polarized? Affective polarization is based on the idea that partisanship can be a social identity leading to polarization in the form of intergroup distancing between the own party and the other parties. In this study, we argue that perceived threats from an outgroup can spur affective polarization. To investigate this, we use the issue of immigration, often framed as a threat by right-wing groups, to examine whether individual-level differences influence how sensititivity to the perception of immigration as a threat. One such factor is the trait right-wing authoritarianism (RWA), which is characterized by emphasis on submission to authority and upholding norms of social order. The emphasis among individuals with this trait on protecting the ingroup from threats means that negativity toward immigration is likely to extend toward political opponents, resulting in an increase in affective polarization. Thus, we hypothesize that the affective polarization is likely to increase when individuals interpret immigration as threatening, particularly for the individuals who are high in RWA aggression. We evaluate and find support for this claim using a large-scale survey performed in Sweden (N = 898). The results, showing a conditional effect of immigration attitudes on affective polarization, are consistent across three commonly used measures of affective polarization as follows: trait ratings, a social distance measure, and feeling thermometers. Overall, our results show that it is important to consider intergroup threats and intergroup differences in the context of sensitivity to such threats when explaining affective polarization.

AbstractSeveral phenomena which have been separately observed in Canada are linked: namely the diffusion of power within the executive-administrative branch, the proliferation and expanded role of pressure groups, and the increased attention parliament has been receiving from interest organizations. Suggesting that this last may reflect fundamental changes in the policy system as a whole, it is argued that a tendency toward bureaucratic pluralism has led agencies to develop extra-governmental support at the interest group level; and that both interest groups and agencies have found it useful to exploit the legitimating and publicizing capacities of parliament. In so doing they have contributed to the enhancement of parliament's role in the policy process.

The extension of voting rights is a central feature of democratization, but there is no systematic explanation of the enfranchisement process. Here, the magnitude of suffrage reform is examined. The historical pattern of enfranchisement is understood in terms of the elite demand for governmental legitimacy, which is supplied by the general population in return for suffrage. Elite demand for & popular supply of legitimacy are affected, in turn, by the historical expansion of the role of the state & the development of democratic expectations, respectively. The validity of this explanation is assessed mathematically through an examination of its analytical implications, & statistically through an estimation of the formal model against the experiences of 9 Western European countries. Results show that while the rate of diffusion (development) of democratic expectations is the same in all 9 countries, the process through which voting rights are extended does depend on variations in the initial conditions of democratization. 1 Table, 3 Figures, 1 Appendix. AA.

A diverse group of over 30 countries located all over the world—such as the UK, Colombia, and Ghana—introduced inflation targeting, which is a monetary policy that seeks to control inflation through a pre-announced target. Fully institutionalized democracies adopted the policy first because the core features of inflation targeting are consistent with the principles of a liberal democracy. But why was inflation targeting also introduced by less-democratic countries? This article develops the argument that decision makers of less-democratic countries became more likely to adopt inflation targeting when they observed that nearby countries increased the flexibility of the policy. The statistical analysis of data from 76 countries between 1989 and 2013 supports this hypothesis. The finding that the change of a policy toward a more flexible framework drives its global spread addresses a blind spot in the more recent policy diffusion literature.