Semantics - Advances in Theories, Mathematical Mdls.

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Affiliation networks have long been formulated and analyzed as two-mode networks conceived as linking, for example, persons and the organizations to which they belong. However, very few network researchers have noticed that the structure of position-generated networks could also be conceived as a form of two-mode network data. In this chapter, we employ a two-mode network formulation to map the classification systems that under- lie the processes by which actors categorize their social contacts into different occupational positions.

In other words, we exploit the embedding of posi- tion-generated networks within a two-mode formulation. We therefore see the two-mode network formulation as, in certain respects, capable of unify- ing the study of position-generated networks how actors classify their social contacts and networks of voluntary associations how actors choose different associations.

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The institutional logics of these classification and affiliation sys- tems indicate the collective and structural characteristics of social capital. More info The concept of "social capital" refer to the ways in which people make use of their social networks in "getting ahead. The purpose of this volume is to focus on the mesolevel analysis of social capital--or how social capital interacts with social institutions, beyond individual dynamics yet beneath the surface of entire societies.

More info Distinctive combinations of attributes and behaviors lead us to improve on existing representations of terrorist organizations within a space of group properties. We review and extend a four-step procedure that discovers statistical interaction effects among relevant variables based on clusters of organizations derived from group properties.

Application of this procedure to terrorist groups in the period identifies distinctive patterns of unconventional weapons activity and improves prediction of the groups that use or pursue chemical, biological, radiological, or nuclear CBRN weapons. More info Spinoza reception in the work of Durkheim and Simmel.

More info No single profile fits all CBRN-active groups, and therefore it is important to identify multiple profiles. In the analysis of terrorist organizations, linear and generalized regression modeling provide a set of tools to apply to data that is in the form of cases named groups by variables traits and behaviors of the groups. We show that a network of profile similarity among the cases is built in to standard regression modeling, and that the exploitation of this aspect leads to new insights helpful in the identification of multiple profiles for actors.

Our application builds on a study of Islamic jihadist organizations that predicts use or pursuit of CBRN weapons. More info This book presents relational sociology ago as an innovative theory and research approach for current sociological discussions.

Semantics #4 - Prototype Theory

In this approach network structure is intertwined with cultural patterns and meanings. The international contributions to this volume show theoretical and empirical directions with which pure structuralism network research can be overcome. In this chapter, I build on one of the foundations of QCA: the duality of cases and variables. At the same time, variables may be seen as configurations of cases.

This idea, I believe, is fundamental to QCA, although it is not as prominently articulated as the other side of the duality.

Les séminaires de la modélisation

In this chapter I will illustrate some of the insight that results from thinking in this way, both for crisp sets and for fuzzy-set analysis of the sort that has been pioneered by Ragin in a way that allows powerful new modeling of qualitative case variation Ragin , in press. More info The study of social relationships among actors — whether individual human beings or animals of other species, small groups or economic organizations, occupations or social classes, nations or world military alliances — is fundamental to the social sciences.

Social network analysis may be defined as the disciplined inquiry into the patterning of relations among social actors, as well as the patterning of relationships among actors at different levels of analysis such as persons and groups. Following an introduction to data analysis issues in social networks research and to the basic forms of network representation, three broad topics are treated under this chapter's main headings: types of equivalence, statistical models emphasizing a new class of logistic regression models for networks , and culture and cognition.

Each section emphasizes data-analytic strategies used in exemplary research studies of social networks.

Computer programs and related issues are briefly treated at the end of the chapter. More info Progress in theorizing networks and events requires formulating a greater diversity of networks, and, in particular, enabling network analysis to exploit relations between events and the attributes, actions, and variables that characterize them. One productive way to analyze an insurgency is to view it as a network of sequenced events across stages periods of conflict. We explore this formulation, identify limitations, and present illustrative analysis demonstrating how new and useful insights can be obtained by combining our formal approach with one grounded in the comparative analysis of case studies.

More info In this article we consider some low-tech approaches to text mining. Our goal is to articulate a RiCH Reader in Control of Hermeneutics style of text analysis that takes advantage of the digital affordances of modern reading practices and easily deployable computational tools while also preserving the primacy of the interpretive lens of the human reader.

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All three analytical interventions provide a productive tracking of various modes and degrees of strategic decisiveness, contradiction, uncertainty and indeterminacy in a corpus of recent U. National Security Strategy reports. More info In the last two decades researchers have examined the practices of online forums operating markets for the sale of stolen credit card data. Participants cannot rely on traditional legal system regulations in the event of disputes between buyers and sellers.

Thus, this analysis focuses on two forms of monitoring within these forums: one based on an emergent social network of transactions among community members second-party monitoring , and the other consisting of regulatory third-party monitoring by forum administrators. Using social network analyses of a series of posts from a data market forum, the findings demonstrate that governance of these forums is enabled by their functioning as a particular kind of market that economists characterize as a platform, or two-sided market. Specifically, second- and third-party trust creating mechanisms are vital in establishing sustainability in illicit markets by increasing perceived market trustworthiness, which in turn leads to increased market demand.

Unfortunately, despite its relative simplicity, even one-mode, unsigned, deterministic blockmodeling problems are NP-hard Chan et al.

MOHAMED NADIF

Understandably, the vast majority of blockmodeling methods employ heuristics to obtain good not necessarily globally optimal solutions in a reasonable amount of time. Nonetheless, the potential benefits of exact algorithms that generate globally optimal solutions are many, including assessing the quality of the results obtained with heuristics. With this in mind, clever methods that guarantee global optimality without examining the entire solution space are attractive alternatives. Although their method is efficient for solving problems of a non-trivial size, they claim its utility in exploratory fitting is limited by the need to examine all possible image matrices Brusco and Steinley, p.

More info The well-known theory of structural holes indicates that brokers, people connecting across clusters, have an advantage in the breadth, timing, and arbitrage of information they possess, and hence they are more likely to have innovative ideas and be major contributors.

Les anciens séminaires

We then find that most external brokers are information bridges, who only spread information across platforms, without actual participation in investigation, discussion, and innovation. More info The foundational research on blockmodeling focused on theorizing and identifying social roles and positions across multiple networks White et al.


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Generalized blockmodeling provided a breakthrough in theory and research by permitting ideal block types that implement a wider class of role equivalence within a network Doreian et al. Notwithstanding these successes and related progress that we discuss, a direct approach for the blockmodeling of multiple relations remains an open problem in the generalized blockmodeling literature Doreian, With this in mind, we propose a simple and novel means of formulating and fitting generalized blockmodels for multiple relations.

We make use of existing capabilities of the open-source network analysis software Pajek Batagelj and Mrvar, ; Mrvar and Batagelj, In particular, by constructing an appropriate augmented adjacency matrix and carefully crafted constraints and penalties, Pajek's criterion function can be simultaneously minimized over multiple relations. This technique is first described in detail using a hypothetical friendship network, and then its value is reinforced through reanalysis of a classic, real world example. Published by Elsevier B. More info Guest Editors: John W.


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  • This special theme explores how the conceptualization, methods, and research practices for working with and analyzing Big Data frequently contain implicit assumptions about the very nature of society, individuals, social institutions and scientific practice, as well as assumptions about how they operate.

    The commentaries collected here highlight these types of assumptions and describe some ways in which scholars in the social sciences and humanities can challenge, correct for and redefine how they use Big Data. More info We describe some of the ways that the field of content analysis is being transformed in an Era of Big Data. We argue that content analysis, from its beginning, has been concerned with extracting the main meanings of a text and mapping those meanings onto the space of a textual corpus. In contrast, we suggest that the emergence of new styles of text mining tools is creating an opportunity to develop a different kind of content analysis that we describe as a computational hermeneutics.


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    • Here the goal is to go beyond a mapping of the main meaning of a text to mimic the kinds of questions and concerns that have traditionally been the focus of a hermeneutically grounded close reading, a reading that focuses on what Kenneth Burke described as the poetic meanings of a text. We illustrate this approach by referring to our own work concerning the rhetorical character of US National Security Strategy documents.

      These emergent issues reflect the challenges, problems, and promises of working with Big Data to access and assess the social. They include puzzles about the locus and nature of human life, the nature of interpretation, the categorical constructions of individual entities and agents, the nature and relevance of contexts and temporalities, and the determinations of causality.

      More info We reformulate regression modeling so that ideas often associated with field theory and social network analysis can be brought to bear at every stage in the computation and interpretation of regression coefficients in studies of organizations. We formulate a dual to regression modeling based on using the variables to learn about the cases. We illustrate our ideas by applying the new approach to a database of hundreds of violent extremist organizations, focusing on understanding which groups use or pursue unconventional weapons chemical, biological, radiological, nuclear.

      More info We generalize a form of two-mode network analysis to make it applicable to a cases-by-variables data format, and apply our approach for the study of terrorist group engagement in the drug trade, emphasizing the implications of our approach for policy in a study of terrorist organizations. We also demonstrate a technique for assessing sampling variability in configurational models.

      More info We contend that clusters of cases co-constitute statistical interactions among variables.

      Les anciens séminaires

      Interactions among variables imply clusters of cases within which statistical effects differ. Regression coefficients may be productively viewed as sums across clusters of cases, and in this sense regression coefficients may be said to be "composed" of clusters of cases. We explicate a four-step procedure that discovers interaction effects based on clusters of cases in the data matrix, hence aiding in inductive model specification.

      We illustrate with two examples. One is a reanalysis of data from a published study of the effect of social welfare policy extensiveness on poverty rates across 15 countries. The second uses General Social Survey data to predict four different dimensions of ego-network homophily.