Migrants' assimilation is a major challenge for European societies, in part because of the sudden surge of refugees in recent years and in part because of long-term demographic trends. In this paper, we use Facebook's data for advertisers to study the levels of assimilation of Arabic-speaking migrants in Germany, as seen through the interests they express online. Our results indicate a gradient of assimilation along demographic lines, language spoken and country of origin. Given the difficulty to collect timely migration data, in particular for traits related to cultural assimilation, the methods that we develop and the results that we provide open new lines of research that computational social scientists are well-positioned to address.
Understanding migrant integration and the effectiveness of policy measures to favor assimilation is a longstanding challenge. A wide range of aspects such as civic integration policies' @cite_7 or multiculturalism @cite_5 have been analyzed. These studies developed evaluation metrics based on concepts such as political trust @cite_11 as well as lack of electoral participation or composite measures of civic integration @cite_5 . For a review of empirical and theoretical challenges see @cite_6 (2005).
@cite_5 @cite_6 @cite_7 @cite_11
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Several countries in Europe have recently adopted obligatory language and country-knowledge requirements for settlement, naturalisation and immigration. Integration tests, courses and contracts are only a few examples of the new ‘civic integration policies’ states are using to promote individual autonomy and common values for newcomers. Are these requirements in response to concrete problems of immigrant integration? Do they enable, or actually inhibit, integration? This paper examines the various pressures behind attaching mandatory integration requirements to status acquisition. To systematically examine these policies, I develop a civic integration index (CIVIX) to measure language, country-knowledge and value-commitment requirements across the EU-15. While there is a general shift toward civic requirements across Europe, evidence reveals important differences in the degree of policy change. Finally, I explore how new civic requirements complement or challenge existing citizenship practices, identifyin... This article engages debates about migrant integration by analyzing political trust and satisfaction in 24 European countries. The evidence suggests that first-generation migrants have the most positive attitudes, while native-origin and second-generation migrant-origin individuals have similar political trust and satisfaction scores. To explain these outcomes, I focus on the importance of subjective integration factors related to the stages of migration. I claim that first-generation migrants, who have gone through the disruptive process of changing countries, will have lower expectations and be more likely to have positive evaluations of the host society. In comparison, native-origin and second-generation migrant-origin individuals have been raised in the same society and are likely to share perspectives toward that society’s political institutions. [ABSTRACT FROM AUTHOR] This review examines research on the assimilation of immigrant groups. We review research on four primary benchmarks of assimilation: socioeconomic status, spatial concentration, language assimilation, and intermarriage. The existing literature shows that today's immigrants are largely assimilating into American society along each of these dimensions. This review also considers directions for future research on the assimilation of immigrant groups in new southern and midwestern gateways and how sociologists measure immigrant assimilation. We document the changing geography of immigrant settlement and review the emerging body of research in this area. We argue that examining immigrant assimilation in these new immigrant gateways is crucial for the development of theories about immigrant assimilation. We also argue that we are likely to see a protracted period of immigrant replenishment that may change the nature of assimilation. Studying this change requires sociologists to use both birth cohort and genera... Moving to a new country can be difficult, but relationships made there can ease the integration into the new environment. The social ties can be formed with different groups: compatriots from their home country, people originally from their new country (locals), and also immigrants from other countries. Yet very little research on immigration has addressed this important aspect, primarily because large-scale studies of social networks are impractical using traditional methods such as surveys. In this study we provide the first comprehensive view into the composition of immigrants' social networks in the United States using data from the social networking site Facebook. We measure the integration of immigrant populations through the structure of friendship ties, and contrast it with the spatial density of immigrant communities. Beyond friendships with compatriots and locals, we look at friendships between immigrant groups, deriving a map of cultural friendship affinities. The principle of self-government through political parties, the cornerstone of democracy, has come to be regarded as a solution to the problem of nationality. This is because the principle of nationality entails the acceptance of the idea of popular government. The importance of the principle of nationality is undeniable, and most of the national questions of Western Europe might be solved in accordance with this principle. Matters are complicated by geographical and strategical considerations, such as the difficulty of determining natural frontiers and the frequent need to establish strategic frontiers. Moreover, the principle of nationality cannot help us where nationalities barely exist or where they are entangled in inextricable confusion. The present work is a critical discussion of the problem of democracy. Michels believes that democracy, as an intellectual theory and as a practical movement, has entered upon a critical phase from which exit will be extremely difficult. In this book he analyzes the tendencies that oppose the realization of democracy, and claims that these tendencies can be classified in three ways: dependence upon the nature of the individual; dependence upon the nature of the political structure; and dependence upon the nature of organization. This edition, described by Morris Janowitz as a "classic of modern social science" and by Melvin Tumin as "the beginning of a tradition", offers a landmark study in political science. Following its original publication in 1910, the study and analysis of political parties was established as a new branch of science. "Political Parties" continues to be a foundation work in the literature and is a necessary addition to the libraries of contemporary political scientists, sociologists and historians. Abstract During the process of knowledge acquisition from different experts it is usual that contradictions occur. Therefore strategies are needed for dealing with divergent statements and conflicts. We provide a formal framework to represent, process and combine distributed knowledge. The representation formalism is many-valued logic, which is a widely accepted method for expressing uncertainty, vagueness, contradictions and lack of information. Combining knowledge as proposed here makes use of the bilattice approach, which turns out to be very flexible and suggestive in the context of combining divergent information. We give some guidelines for choosing truth value spaces, assigning truth values and defining global operators to encode integration strategies. The state of Singapore operates a national public housing program, accounting for over @math of its residential real estate. Singapore uses its housing allocation program to promote ethnic diversity in its neighborhoods; it does so by imposing ethnic quotas: every ethnic group must not own more than a certain percentage in a housing project, thus ensuring that every neighborhood contains members from each ethnic group. However, imposing diversity constraints naturally results in some welfare loss. Our work studies the tradeoff between diversity and (utilitarian) social welfare from the perspective of computational economics. We model the problem as an extension of the classic assignment problem, with additional diversity constraints. While the classic assignment program is poly-time computable, we show that adding diversity constraints makes the problem computationally intractable; however, we identify a 1 2-approximation algorithm, as well as reasonable agent utility models which admit poly-time algorithms. In addition, we study the price of diversity: this is the loss in welfare incurred by imposing diversity constraints; we provide upper bounds on the price of diversity as functions of natural problem parameters. Finally, we use recent, public demographic and real-estate data from Singapore to create a simulated framework testing the welfare loss due to diversity constraints in realistic large-scale scenarios. The American Voter - a seminal work in political science - uncovered the multifaceted nature of voting behavior which has been corroborated in electoral research for decades since. In this paper, we leverage The American Voter as an analysis framework in the realm of computational political science, employing the factors of party, personality, and policy to structure the analysis of public discourse on online social media during the 2016 U.S. presidential primaries. Our analysis of 50 million tweets reveals the continuing importance of these three factors; our understanding is also enriched by the application of sentiment analysis techniques. The overwhelmingly negative sentiment of conversations surrounding 10 major presidential candidates reveals more "crosstalk" from Democratic leaning users towards Republican candidates, and less vice-versa. We uncover the lack of moderation as the most discussed personality dimension during this campaign season, as the political field becomes more extreme - Clinton and Rubio are perceived as moderate, while Trump, Sanders, and Cruz are not. While the most discussed issues are foreign policy and immigration, Republicans tweet more about abortion than Democrats who tweet more about gay rights than Republicans. Finally, we illustrate the importance of multifaceted political discourse analysis by applying regression to quantify the impact of party, personality, and policy on national polls. Display Omitted ContextNumerous open source software projects are based on volunteers collaboration and require a continuous influx of newcomers for their continuity. Newcomers face barriers that can lead them to give up. These barriers hinder both developers willing to make a single contribution and those willing to become a project member. ObjectiveThis study aims to identify and classify the barriers that newcomers face when contributing to open source software projects. MethodWe conducted a systematic literature review of papers reporting empirical evidence regarding the barriers that newcomers face when contributing to open source software (OSS) projects. We retrieved 291 studies by querying 4 digital libraries. Twenty studies were identified as primary. We performed a backward snowballing approach, and searched for other papers published by the authors of the selected papers to identify potential studies. Then, we used a coding approach inspired by open coding and axial coding procedures from Grounded Theory to categorize the barriers reported by the selected studies. ResultsWe identified 20 studies providing empirical evidence of barriers faced by newcomers to OSS projects while making a contribution. From the analysis, we identified 15 different barriers, which we grouped into five categories: social interaction, newcomers' previous knowledge, finding a way to start, documentation, and technical hurdles. We also classified the problems with regard to their origin: newcomers, community, or product. ConclusionThe results are useful to researchers and OSS practitioners willing to investigate or to implement tools to support newcomers. We mapped technical and non-technical barriers that hinder newcomers' first contributions. The most evidenced barriers are related to socialization, appearing in 75 (15 out of 20) of the studies analyzed, with a high focus on interactions in mailing lists (receiving answers and socialization with other members). There is a lack of in-depth studies on technical issues, such as code issues. We also noticed that the majority of the studies relied on historical data gathered from software repositories and that there was a lack of experiments and qualitative studies in this area. Most people associate with people like themselves, a process called homophily. Exposure to diversity, however, makes us more informed as individuals and as a society. In this paper, we investigate political disagreements on Facebook to explore the conditions under which diverse opinions can coexist online. Via a mixed methods approach comprising 103 survey responses and 13 interviews with politically engaged American social media users, we found that participants who perceived more differences with their friends engaged less on Facebook than those who perceived more homogeneity. Weak ties were particularly brittle to political disagreements, despite being the ties most likely to offer diversity. Finally, based on our findings we suggest potential design opportunities to bridge across ideological difference: 1) support exposure to weak ties; and 2) make common ground visible while friends converse. In online social networks, people tend to connect with like-minded people and read agreeable information. Direct recommendation of challenging content has not worked well because users do not value diversity and avoid challenging content. In this poster, we investigate the possibility of an indirect approach by introducing intermediary topics, which are topics that are common to people having opposing views on sensitive issues, i.e., those issues that tend to divide people. Through a case study about a sensitive issue discussed in Twitter, we show that such intermediary topics exist, opening a path for future work in recommendation promoting diversity of content to be shared. A series of progressive demasking and lexical decision experiments investigated how the recognition of target words exclusively belonging to one language is affected by the existence of orthographic neighbors from the same or the other language of bilingual participants. Increasing the number of orthographic neighbors in Dutch systematically slowed response times to English target words in Dutch English bilinguals, while an increase in target language neighbors consistently produced inhibitory effects for Dutch and facilitatory effects for English target words. Monolingual English speakers also showed facilitation due to English neighbors, but no effect of Dutch neighbors. The experiments provide evidence for parallel activation of words in an integrated Dutch English lexicon. An implemented version of such a model making these assumptions, the Bilingual Interactive Activation (BIA) model, is shown to account for the overall pattern of results. © 1998 Academic Press One of the striking features of bilingual language performance is the apparent ease with which the bilingual manages to keep interference from the non-target language at a minimal level. The fact remains, however, that interference from one language to the other does occur and is observable with respect to both language structure and linguistic processing. For example, in language production, interference from the first language can be noticed both at the phonological level (foreign accents) and at the sentence level (borrowed syntax), as well as in intrusions of words from the other language (accidental lexical borrowings). The process of integrating knowledge coming from different sources has been widely investigated in the literature. Three distinct conceptual approaches to this problem have been most succesful: belief revision, merging and update. In this paper we present a framework that integrates these three approaches. In the proposed framework all three operations can be performed. We provide an example that can only be solved by applying more than one single style of knowledge integration and, therefore, cannot be addressed by anyone of the approaches alone. The framework has been implemented, and the examples shown in this paper (as well as other examples from the belief revision literature) have been successfully tested. We present a new solution to the ecological inference'' problem, of learning individual-level associations from aggregate data. This problem has a long history and has attracted much attention, debate, claims that it is unsolvable, and purported solutions. Unlike other ecological inference techniques, our method makes use of unlabeled individual-level data by embedding the distribution over these predictors into a vector in Hilbert space. Our approach relies on recent learning theory results for distribution regression, using kernel embeddings of distributions. Our novel approach to distribution regression exploits the connection between Gaussian process regression and kernel ridge regression, giving us a coherent, Bayesian approach to learning and inference and a convenient way to include prior information in the form of a spatial covariance function. Our approach is highly scalable as it relies on FastFood, a randomized explicit feature representation for kernel embeddings. We apply our approach to the challenging political science problem of modeling the voting behavior of demographic groups based on aggregate voting data. We consider the 2012 US Presidential election, and ask: what was the probability that members of various demographic groups supported Barack Obama, and how did this vary spatially across the country? Our results match standard survey-based exit polling data for the small number of states for which it is available, and serve to fill in the large gaps in this data, at a much higher degree of granularity. This paper examines the system of Qualified Majority Voting, used by the Council of the European Union, from the perspective of enlargement of the Union. It uses an approach based on power indices due to Penrose (1946), Banzhaf (1965) and Coleman (1971) to make two analyses: (1) the question of the voting power of member countries from the point of view of fairness, and (2) the question of how the threshold number of votes required for QMV should be determined. It studies two scenarios for change from 2005 onwards envisaged by the Nice Treaty: (1) no enlargement, the EU comprising 15 member countries, and (2) full enlargement to 27 members by the accession of all the present twelve candidates. The proposal is made that fair weights be determined algorithmically as a technical or routine matter as the membership changes. The analysis of how the threshold affects power shows the trade-offs that countries face between their blocking power and the power of the Council to act. The main findings are: (1) that the weights laid down in the Nice Treaty are close to being fair, the only significant discrepancies being the under-representation of Germany and Romania, and the over-representation of Spain and Poland; (2) the threshold required for a decision is set too high for the Council to be an effective decision making body. In this paper we describe an application of language technology to policy formulation, where it can support policy makers assess the acceptance of a yet-unpublished policy before the policy enters public consultation. One of the key concepts is that instead of relying on thematic similarity, we extract arguments expressed in support or opposition of positions that are general statements that are, themselves, consistent with the policy or not. The focus of this paper in this overall pipeline, is identifying arguments in text: we present and empirically evaluate the hypothesis that verbal tense and mood are good indicators of arguments that have not been explored in the relevant literature. Recently, there have been considerable efforts to use online data to investigate international migration. These efforts show that Web data are valuable for estimating migration rates and are relatively easy to obtain. However, existing studies have only investigated flows of people along migration corridors, i.e. between pairs of countries. In our work, we use data about "places lived" from millions of Google+ users in order to study migration "clusters", i.e. groups of countries in which individuals have lived. For the first time, we consider information about more than two countries people have lived in. We argue that these data are very valuable because this type of information is not available in traditional demographic sources which record country-to-country migration flows independent of each other. We show that migration clusters of country triads cannot be identified using information about bilateral flows alone. To demonstrate the additional insights that can be gained by using data about migration clusters, we first develop a model that tries to predict the prevalence of a given triad using only data about its constituent pairs. We then inspect the groups of three countries which are more or less prominent, compared to what we would expect based on bilateral flows alone. Next, we identify a set of features such as a shared language or colonial ties that explain which triple of country pairs are more or less likely to be clustered when looking at country triples. Then we select and contrast a few cases of clusters that provide some qualitative information about what our data set shows. The type of data that we use is potentially available for a number of social media services. We hope that this first study about migration clusters will stimulate the use of Web data for the development of new theories of international migration that could not be tested appropriately before. Migration estimates are sensitive to definitions of time interval and duration. For example, when does a tourist become a migrant? As a result, harmonizing across different kinds of estimates or data sources can be difficult. Moreover in countries like the United States, that do not have a national registry system, estimates of internal migration typically rely on survey data that can require over a year from data collection to publication. In addition, each survey can ask only a limited set questions about migration (e.g., where did you live a year ago? where did you live five years ago?). We leverage a sample of geo-referenced Twitter tweets for about 62,000 users, spanning the period between 2010 and 2016, to estimate a series of US internal migration flows under varying time intervals and durations. Our findings, expressed in terms of 'migration curves', document, for the first time, the relationships between short-term mobility and long-term migration. The results open new avenues for demographic research. More specifically, future directions include the use of migration curves to produce probabilistic estimates of long-term migration from short-term (and vice versa) and to nowcast mobility rates at different levels of spatial and temporal granularity using a combination of previously published American Community Survey data and up-to-date data from a panel of Twitter users. A central source of cultural differences is the communication of politeness, which can powerfully affect perception and behavior. Our computational adaptation of a universal theory of human politeness (from Brown and Levinson, 1987) combines culture-specific aspects of social context to generate expectations, score, interpret and recommend polite and impolite behaviors. Tests show this approach could reduce software development costs and increase an intelligent agent's behavior repertoire through the incorporation of modular, cross-cultural etiquette libraries. The right framework for studying normative issues in infosociety and MAS is that of deliberate or spontaneous social order, and intended or unintended, centralised or decentralised forms of social control. For effectively supporting human cooperation it is necessary to "incorporate" social and normative knowledge in intelligent technology; computers should deal with--and thus partially "understand"--permissions, obligations, power, roles, commitments, trust, etc. Here only one facet of this problem is considered: the spontaneous and decentralised norm creation, and normative monitoring and intervention. Cognitive aspects of spontaneous conventions, implicit commitments, tacit agreements, and the bottom-up issuing and spreading of norms are discussed. The transition from "face to face" normative relationships to some stronger constraints on agents' action, and to institutions and authority, and the possibility of a consequent increase of trust, are explored. In particular, I focus on the transition from two party trust, right, permission, and commitment, to three party relationships, where some witness or some enforcing authority is introduced. In this perspective of 'formalising the informal', i.e., the interpersonal unofficial normative matter, I discuss (also in order to stress dangers of computer-based formalisation and enforcement of rules) the important phenomenon of functional (collaborative) systematic violation of rules in organisation and cooperation, and the possible emergence of a "convention to violate".