Veranstaltungen

Veranstaltungsort:
BITZ
Fahrenheitstraße 1
28359 Bremen
Uhrzeit:
31. Mai: 14.00-18.15 Uhr; 1. Juni: 9.00-16.30 Uhr
Ansprechpartner/in:
Kooperation:
Friedrich-Schiller-Universität Jena; Ludwig-Maximilians-Universität München; Technische Universität Chemnitz; Universität zu Köln

Download: Programm "5. pairfam-Nutzerkonferenz"

Weitere Informationen:
Beziehungs- und Familienpanel pairfam („Panel Analysis of Intimate Relationships and Family Dynamics“)

28.03.2017Methoden Workshop

Data Mining mit R

Holger Döring (Universität Bremen)
Veranstaltungsort:
SOCIUM Forschungszentrum Ungleichheit und Sozialpolitik
Raum: 9.3120
Mary-Somerville-Straße 9
28359 Bremen
Uhrzeit:
9.15 - 12.30 Uhr
Ansprechpartner/in:
Semester:
WiSe 2016/17

Sozialwissenschaftler sind zunehmend mit anspruchsvollen Analyseverfahren, „heterogenen Daten“ und hohen Anforderungen an die Visualisierung ihrer Erkenntnisse und Befunde konfrontiert. Die Programmiersprache R hat sich dabei zu einer „lingua franca“ in den Sozialwissenschaften entwickelt. R wird vielfältig verwendet: für fortgeschrittene statistische Verfahren, für Text- und Netzwerkanalysen, für das Datenmanagement, sowie für die grafische Präsentation von Ergebnissen. Viele neuere Pakete erleichtern die Umsetzung dieser Aufgaben.

In dem für Einsteiger gedachten Workshop beschäftigen wir uns vorrangig mit Techniken des Data Minings (u.a. Datenbanken, Daten sozialer Netzwerke, ‘record linkage’, Nutzung von APIs (Programmierschnittstelle), „Crawling“ von Internetseiten). Außerdem gehen wir auf die Aufbereitung dieser Daten und einiger Visualisierungsverfahren mit R ein. Der Kurs richtet sich an alle Einsteigerinnen und Einsteiger, jedoch werden basale Kenntnisse in R vorausgesetzt.

Veranstaltungsort:
SOCIUM Forschungszentrum Ungleichheit und Sozialpolitik
Raum: 9.3120
Mary-Somerville-Straße 9
28359 Bremen
Uhrzeit:
9.00 - 12.00 Uhr
Semester:
WiSe 2016/17

In der Veranstaltung soll es um eine Einführung in die Sequenzanalyse gehen. Nach einer kurzen Darstellung der Methode wird das 'Sequence Analysis with Stata'-Modul von Ulrich Kohler, Magdalena Luniak, und Christian Brzinsky-Fay kurz vorgestellt und es werden Anwendungsmöglichkeiten der Sequenzanalyse in der sozialwissenschaftlichen Forschung aufgezeigt. Diese Veranstaltung ist als Einführung verstanden, nicht als Expertenworkshop.

Veranstaltungsort:
Bremen International Graduate School of Social Sciences (BIGSSS)
Raum: 7.3280
Mary-Somerville-Straße 7
28359 Bremen
Uhrzeit:
16.15 Uhr
Ansprechpartner/in:
Veranstaltungsreihe:
Methodenveranstaltungen der Brückenprofessur
Semester:
WiSe 2016/17

Tom A.B. Snijders is Professor of Statistics and Methodology at the Dept. of Sociology, University of Groningen, Emeritus Fellow, Nuffield College, University of Oxford and an Associate Member at the Dept. of Statistics, University of Oxford.

Abstract:
Homophily is a basic feature of social networks. For numerical actor variables, its specification in statistical network models is usually done by means of the absolute difference between ego and alter on the variable under consideration; sometimes, as an alternative, by the ego-alter interaction. It is argued that such specifications are incomplete for continuous actor variables and for ordinal numerical variables with three or more categories. The reason is that ego is not necessarily attracted mostly to others with the same value as ego; often the attraction is to some value between ego's value and the 'social norm'. (Attraction here is to be understood not necessarily as a preference, but rather as an empirical tendency.) Therefore, the usual representation will often amount to a misspecification. This is elaborated in an extension of the usual specification of effects of actor variables in stochastic actor-oriented models for network dynamics. This new specification may have consequences for results of studies of social selection. An example is given.

01.07.2016Bridge-Lecture

Communicating Friendship: Relational Enactments and Relational Perceptions

Prof. Daniel A. McFarland (Stanford University)
Veranstaltungsort:
SOCIUM Forschungszentrum Ungleichheit und Sozialpolitik
Raum: 9.73280
Mary-Somerville-Straße 9
28359 Bremen
Uhrzeit:
10:15 Uhr
Ansprechpartner/in:
Kooperation:
Veranstaltungsreihe:
Methodenveranstaltungen der Brückenprofessur
Semester:
SoSe 2016

Dan McFarland is Professor of Sociology and Organizational Behavior at Stanford University. His research focuses on the social and organizational dynamics of educational systems like schools, classrooms and universities. In particular, Dan has performed a series of studies on classroom organization and interaction; on the formation of adolescent relationships, social structures, and identities; on interdisciplinary collaboration and intellectual innovation; and on relational sociology. His interdisciplinary collaborations with linguists and computer scientists are cutting-edge studies of big data and methodological advances in social networks and language modeling.

Abstract:
This paper attempts to directly consider the nature of relationships and the role of interaction dynamics more deeply. To this end, relationships are reconceptualized as a story between persons that is perceived (labeled), agreed upon, and enacted in interaction. From this perspective, types of ties like friendship are relational frameworks that are mutually recognized and enacted via certain interactional footings. To identify the effect of interactional footings over and above previously identified network mechanisms, we rely on systematic social observations of hundreds of settings that extend across one hundred thousand turns of social interaction, as well as longitudinally collected sociometric surveys and institutional records. With these data, interactions are not only coded for a variety of qualities, but they are situated in various social contexts and institutional framing efforts. For example, a particular interactional event, like the act of agreement between i and j at time t, can be embedded in a particular setting, a task (or sequence), a role-relation, and a reported friendship relation. Since most interactions are guided by any one or more of these framing efforts machine learning is employed to identify the interactions associated with each one while taking into account their overlap. Ultimately, the goal is to identify the interactional signal of a perceived and agreed upon reports of friendship. In such a fashion, we identify the interactional footings or ³friendship script² that actors employ to signal the relational frame of ³friendship². This signal - as a latent dimension - is then tested for its predictive capacity on friendship formation to ascertain if it has an effect over and above previously held mechanisms of tie formation.