Tag Archives: IRWS

Grounded Theory

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Maike Andresen (Otto-Friedrich University of Bamberg)

Date: 03.10.2012, 09:30 – 17:30

Room: n.s.

Max. number of participants: 25

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

The workshops aims at establishing a theoretical and practical understanding about the key concepts, strategies and steps in Grounded-Theory-Research, i.e. the constant comparative method, open, axial and selective coding, theoretical sampling, theoretical saturation, and theoretical sensitivity. In addition, common pitfalls in grounded theory research will be discussed.

Current research projects and materials of participants can be considered and discussed in case of interest.

Literature
Glaser, B., & Strauss, A. (1967). The discovery of grounded theory: Strategies for qualitative research. New York: Aldine de Gruyter.
Strauss, A., & Corbin, J. (1998). Basics of qualitative research: Grounded theory procedures and techniques (2. Aufl.). Thousand Oaks, CA: Sage.

You have to register for the 6th International Research Workshop to participate in this course.

Network Analysis

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Anja Iseke (University of Paderborn)

Date: 03.10.2012, 09:30 – 17:30

Room: n.s.

Max. number of participants: 25

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

This course will familiarize students with basic concepts in social network analysis. Topics include handling network data, introduction to network analysis software (UCINET and Netdraw), centrality and prestige in networks, subgroup analysis, and roles and positions. This is an applied course that will require students to test and analyze social networks of employees in a high-tech organization.

References:
Wasserman, S., & Faust, K. 1997. Social Network Analysis: Methods and Applications. Cambridge, New York: Cambridge University Press.
Borgatti, S. P., & Foster, P. C. 2003. The Network Paradigm in Organizational Research: A Review and Typology. Journal of Management, 29(6): 991–1013.

You have to register for the 6th International Research Workshop to participate in this course.

Structural Equation Modeling with Amos

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Katja Spanier (Hannover Medical School)

Date: 03.10.2012, 09:30 – 17:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: German

Contents:

Structural equation modeling (SEM) is a statistical methodology that takes a confirmatory approach to the analysis of a strucutral theory bearing on some phenomenon. Typically, the structural relations can be modeled pictorially to enable a clearer conceptualization of the theory under study. The course introduces into the basic concepts of SEM and into the program package AMOS, which is widely used to graph and to analyze strucutral models. Data of different social areas will be used as examples.

Preconditions: Basic knowledge of SPSS

You have to register for the 6th International Research Workshop to participate in this course.

Sequential Analysis

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Michael Stegmann (Research Data Centre of the German Pension Insurance)

Date:

03.10.2012, 09:30 – 17:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents: n.s.

You have to register for the 6th International Research Workshop to participate in this course.

From Words to Networks: Information and Relation Extraction from Text Data and Analysis of Socio-technical Networks

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Jana Diesner (The iSchool at the University of Illinois at Urbana-Champaign)

Date:

01.10.2012, 14:00 – 17:30
02.10.2012, 14:00 – 17:30
04.10.2012, 14:00 – 17:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

1. What is covered in the workshop, what will you learn?

In this workshop, you will learn how to extract information about socio-technical networks from unstructured, natural language text data, how to analyze network data, and how to use the results for practical purposes. We will discuss practical applications from academia, administration and business, such as answering substantive questions about online and offline networks, designing policies and interventions, and tracking trends and opinions.

Socio-technical networks represent interactions between people and organizations, infrastructures and information in systems such as corporations, countries and communities of practice. The functioning and dynamics of these networks involve the continuous production, processing and flow of information. This information is often available as text data and can serve as a single or complementary source of information about networks. Examples for data sources include communication data such as conversations transcripts and emails, news wire data, scientific information such as publications and patents, self-presentations such as mission statements and annual reports, and social media data such as blogs and wikis. Using text data to construct or enhance network data has helped people to answer questions like:

  • Who talks to whom, and about what?
  • What are the mental models of individuals or groups about certain topics?
  • How do memes and innovations emerge, spread, change and vanish in society?
  • Who are the key players in a network? What tasks, resources and knowledge are they linked to?
  • What benefits and risks result from an observed network structure for the network and its wider context?

In this workshop, you will learn how to do the following:

  • Put the network analysis process into action to answer questions and solve problems.
  • Extract relevant information and network data from text data in an informed, systematic and efficient fashion.
  • Use network analysis software to visualize and analyze network data, inlcuding grouping and simulating what-if scenarios.
  • Develop actionable interpretations of text analysis and network analysis results.

You are introduced to a selected set of theories, concepts and methods from text analysis and network analysis. You gain practical, hands-on experience in working text mining and network analysis software. You will perform basic natural language processing techniques on the lexical, syntactic and semantic level including:

  • Identification of key concepts and themes from single documents and text collections.
  • Creation and application of codebooks and thesauri.
  • Identification and classification of entities. We will move beyond the classic set of named entities to facilitate the detection of nodes that represent categories that are also relevant for studying socio-technical network, such as tasks, resources and knowledge.
  • Filtering and pre-processing techniques such as stemming, parts of speech tagging, and N-gram detection.
  • Relation Extraction, i.e. distilling socio-technical networks from text data.

Going from texts to networks involves basic some principles and strategies originating from computer science that are not only applicable to the task at hand, but to a wide range of problems. These principles and strategies are referred to as Computational Thinking – a basic skill like reading, writing and arithmetic that is essential for solving problems and understanding human behavior (Wing 2006). You are introduced to the concept of Computational Thinking and learn how to apply this way of thinking to the problems addressed in the workshop.

Summary of learning goals:

1. Information and Relation Extraction: Gain theoretical, methodological and practical experience in distilling relevant information and network data from text data. Learn how this process can be used for practical purposes in academia and business.

2. Network Analysis: Gain theoretical, methodological and practical experience in visualizing, analyzing and interpreting network data. Learn how the results can be used for practical purposes in academia and business.

3. Computational Thinking: Be introduced to a fundamental approach to problem solving and actively apply your expertise.

2. Schedule

Day 1 – 01.10.2012:

Introduction:

  • Analysis of socio-technical networks
  • Semantic Networks and Information Networks
  • Intersection of Text Analysis and Network Analysis

Hands-on training:

  • Information Extraction
  • Relation Extraction
  • Network Visualization

Day 2 – 02.10.2012:

Hands-on training:

  • Network Analysis
  • Node-level and graph-level analysis
  • Grouping
  • Simulation of what-if scenarios
  • One-mode and multi-mode networks

Introduction and hands-on exercises:

  • Interpretation and actionable use of results
  • Evaluation of data and results
  • Data privacy and data security issues related to network analysis

3. Who should attend?

This is an interdisciplinary and interactive workshop designed to benefit from the participation of people from different backgrounds. The material, exercises and mode of delivery are suitable for researchers and practitioners alike. No specific prior knowledge or computational skills are required. The delivery is driven towards forming an understanding of fundamental concepts and gaining hands-on experience with relational data analysis methods and tools.

We will email you additional material prior to the workshop.

4. What to bring to the workshop?

Software: The software used in this workshop runs on Windows. Please download and install the following tools prior to the workshop:

Data: You can work with the sample data that we provide for the workshop and/or bring your own data. We provide two small sample datasets; one with email data and one with news articles. If you bring your own text data, we recommend a sample of not more than 20 texts that are not longer than 5 pages each. If you bring your own network data, we recommend data with not more than 200 nodes. The tools we use scale up to larger data sets, but those might not be practical for training purposes.

5. Readings

For everybody:

Overview on the concepts and methods addressed in the workshop:

Diesner, J., & Carley, K. M. (2010) Extraktion relationaler Daten aus Texten. In C. Stegbauer & R. Häußling (Eds.), Handbuch Netzwerkforschung (pp. 507 -524) Vs Verlag. (We will email regisrered participants a copy).

For more/ specialized information:

New to Information Extraction/text mining?

McCallum, A. (2005). Information extraction: distilling structured data from unstructured text. ACM Queue, 3(9), 48-57. URL: http://www.cs.umass.edu/~mccallum/papers/acm-queue-ie.pdf

New to Social Network Analysis?

Hanneman, RA & Riddle, M. (2005). Introduction to social network methods. Riverside, CA: University of California. URL: http://www.faculty.ucr.edu/~hanneman/nettext/

Easley, D. & Kleinberg, J. (2010). Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge University Press. URL: http://www.cs.cornell.edu/home/kleinber/networks-book/

New to Computational Thinking?

Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33 – 35. URL: http://www.cs.cmu.edu/afs/cs/usr/wing/www/publications/Wing06.pdf

6. Information about the instructor

Jana Diesner is an Assistant Professor at the University of Illinois at Urbana-Champaign, The iSchool/Graduate School of Library and Information Science. She conducts research at the nexus of machine learning, natural language processing and network analysis. She develops and analyzes methods and technologies for extracting information about networks from text data and considering the content of information for network analysis. Her goal is to contribute to a better understanding and rigorous computational analysis of the interplay and co-evolution of information and the structure and functioning of socio-technical networks. In her empirical work, Jana studies networks from the geopolitical, business and science domain. She is particularly interested in covert information and covert networks.

7. Questions?

Contact Jana with any questions about the course at jdiesner@illinois.edu.

You have to register for the 6th International Research Workshop to participate in this course.

Data Analysis with Stata (Intermediates)

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Andrea Schäfer (University of Bremen)

Date:

01.10.2012, 14:00 – 17:30
02.10.2012, 14:00 – 17:30
04.10.2012, 14:00 – 17:30

Room: n.s.

Max. number of participants: 25

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

The course is designed to provide a more advanced knowledge of Stata 11. Those who are already experienced in using Stata for data analysis and attended the ‘Introduction to Stata’ course or be familiar with the contents will benefit most from the course. Further, it is assumed that participants will have a working knowledge of basic statistics. However, the course is not focussed on statistical content, but on data management skills. By the end of the course, students should be able to use Stata 11 efficiently through using a broader range of complex commands, understanding and using matrices, scalars and macros and produce formatted outputs.

Teaching practice will consist of tutorials and practical sessions (exercises).

Course outline:

  • Short review on basics
  • How to reshape and create data sets
  • Advanced functions and commands: using egen, _N, _n
  • Structure of loopings: while, foreach and forvalues
  • Managing and creating matrices
  • Understanding and using: scalars, macros and arguments
  • Fancy graphs
  • Know how to export results: estout, outreg, tabout
  • Very first steps: writing programs

References
Ulrich Kohler and Frauke Kreuter (2009): Data Analysis Using Stata, Second Edition. Stata Press
Christopher F. Baum (2009): An Introduction to Stata Programming. Stata Press
H. Joseph Newton and N. J. Cox (editors) (2010): Seventy-six Stata Tips, Second Edition Stata Press

You have to register for the 6th International Research Workshop to participate in this course.

Analysing Panel Data

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Toben Dall Schmidt, Nisar Ahmad (SDU Sonderburg/Denmark)

Date:

04.10.2012, 14:00 – 17:30

Room: n.s.

Max. number of participants: 25

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

Panel data has become popular due to their very specific structure and associated advantages. This module will introduce these basic structures and offer some first insights into the different standard estimation methods available to use panel data for analysis – the most two most common being the fixed effects models and the random effects models. In terms of advantages, the module will offer a discussion of the properties of panel data in allowing for unobservable heterogeneity, but it will also point to some of the caveats of using panel data, e.g. attrition problem in survey data. A final issue in the module will be testing procedures to allow for a selection between different estimation methods for panel data. The module will therefore offer a basic introduction into the essence of panel data analysis.

You have to register for the 6th International Research Workshop to participate in this course.

Questionnaire Design

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Prof. Dr. Juergen H. P. Hoffmeyer-Zlotnik (University of Gießen)
Prof. Dr. Dagmar Krebs (University of Gießen)
Dr. Natalja Menold (GESIS)

Date:

01.10.2012, 09:00 – 12:30
02.10.2012, 09:00 – 12:30
04.10.2012, 09:00 – 12:30
05.10.2012, 09:00 – 12:30

Room: n.s.

Max. number of participants: n.s.

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English/German (depending on participants)

Contents:

The lectures deal with the basic principles which have been established in the best practice of questionnaire design. The theoretical background and current state of research will be demonstrated on examples and practical exercises.

1. Cognitive process and cognitive pretests: Monday

For the beginning the cognitive process in survey responding, including comprehension, retrieval, judgement and formatting response will be presented. For each of these phases the demands for questionnaire design related to the questions about attitudes, opinions and behavior will be explicated. It will be shown, how cognitive pretest techniques (think aloud, probing, confidence rating, paraphrasing) can help to detect the problems in questionnaires, which were related to the cognitive burden of the respondents.

2. Context effects and question wording: Tuesday

This section deals with the impact of situational context given in questionnaires on judgements/answers. Regarding the principles of question wording topics such as to phrase the questions, usage of terms and problems with hypothetical, suggestive, negative and double-barreled questions were attended. For each of the principles examples of problems and their solutions will be given.

3. Constructing of optimal answer formats: Thursday

Constructing of optimal answer formats due the reliability and validity of questions includes topics such as number of scale points, midpoint, usage of unipolare and bipolare scales, labels of scale points, ascending and descending sequences. Related topics are handling of open and closed questions and usage of non-opinion filters. The problems and their solutions are demonstrated with help of examples and exercises.

4. Collection of sociodemographic data: Friday

The fourth part of this lesson demonstrate how to harmonise demographic and socio-economic variables in cross-national comparative survey research. Demographic and socio-economic variables describe the context in which a person is acting. In cross-national comparable research standardised instruments or indices exist only for a very small group of variables. Aside from these instruments there are rules for developing further measurement instruments for measuring socio-demographic variables in cross-national research.

Literature

Bortz, J., & Döring, N. (2002). Forschungsmethoden und Evaluation für Human- und Sozialwissenschaftler. Berlin et al.: Springer.

Christian, Leah. M., Parsons, N. L., & Dillman, Don. A. (2009). Designing Scalar Questions for Web Surveys. Sociological Methods and Research, 37(393), 423.

Christian, Leah. M., & Dillman, Don. A. (2004). The Influence of Graphical and Symbolic Language Manipulations on Responses to Self-Administered Questions. Public Opinion Quarterly, 68(1), 57-80.

Christian, L. M., Dillman, D. A., & Smyth, J. D. (2007). Helping Respondents Get it Right the First Time: The Influenece of Words, Symbols, and Graphics in Web Surveys. Public Opinion Quarterly, 71(1), 113-125.

Couper, M. P., Conrad, F. G., & Tourangeau, R. (2007). Visual Context Effects in Web Surveys. Public Opinion Quarterly, 71(4), 623-634.

Dillman, D. A., Smyth, J. D., & Christian, L. M. (2009). Internet, mail, and mixed-mode surveys. The tailored design method. Wiley: New Jersey.

Dillman, D. A. (2007). Mail and Internet Surveys. The Tailored Design Method. Wiley: New Jersey.

Groves, R. M; Fowler, F. J.; Couper, M.P.; Lepkowski, J. M.; Singer, E. & Tourangeau, R. (2004). Survey Methodology. New Jersey: Wiley.

Hippler, Hans-J. (1988). Methodische Aspekte schriftlicher Befragungen: Probleme und Forschungsperspektiven. Planung und Analyse, 6, S. 244-248.

Holbrook, A. L., & Krosnick, J. A. (2010a). Social desirability bias in voter turnout reports: Tests using the item count technique. Public Opinion Quarterly, 74, 37-67.

Holbrook, A. L., & Krosnick, J. A. (2010b). Measuring voter turnout by using the randomized response technique: Evidence calling into question the method’s validity. Public Opinion Quarterly, 74, 328-343.

Krosnick, J. A., & Fabrigar, L. R. (1997). Designing rating scales for effective measurement in surveys. In L. Lyberg, P. Biemer, M. Collins, E. de Leeuw, C. Dippo, N. Schwarz, & D. Trewin, (Eds.), Survey measurement and process quality (pp. 141-164). New York: Wiley.

Krosnick, J. A., & Presser, S. (2010). Questionnaire design. In J. D. Wright & P. V. Marsden (Eds.), Handbook of Survey Research (Second Edition). West Yorkshire, England: Emerald Group.

Krosnick, J. A., Holbrook, A. L., Berent, M. K., Carson, R. T., Hanemann, W. M., Kopp, R. J., Mitchell, R. C., Presser, S., Ruud, P. A., Smith, V. K., Moody, W. R., Green, M. C., & Conaway, M. (2002). The impact of “no opinion” response options on data quality: Non-attitude reduction or an invitation to satisfice? Public Opinion Quarterly, 66, 371-403.

Krosnick, J. A., Judd, C. M. & Wittenbrink, B. (2005). The measurement of attitudes. In D. Albarracin, B. T. Johnson & M. P. Zanna (Hrsg.). The Handbook of Attitudes (S. 21-75). Mahwah, NJ: Lawrence Erlbaum Associates, Inc.

Maitland, A. (2009 a). Should I label all scale points or just the end points for attitudinal questions? Survey Practice, 04. AAPOR e-journal.

Maitland, A. (2009 b). How many scale points should I include for attitudinal questions? Survey Practice, 06. AAPOR e-journal.

Porst, R. (2000). Question Wording – Zur Formulierung von Fragebogen-Fragen. Gesis How-to Reihe, Nr. 22; http://www.gesis.org/fileadmin/upload/forschung/publikationen/gesis_reihen/howto/how-to2rp.pdf.

Porst, R. (2008). Fragebogen. Ein Arbeitsbuch. Wiesbaden: VS Verlag für Sozialwissenschaften.

Saris, W. E., & Gallhofer, I. N. (2007). Design, evaluation, and analysis of questionnaires for survey research. Hoboken, New Jersey: John Wiley & Sons, Inc.

Saris, W., Revilla, M., Krosnick, J. A., & Shaeffer, E. (2010). Comparing questions with agree/disagree response options to questions with item-specific response options. Survey Research Methods, 4, 61-79.

Schuman, H., & Presser, S. (1981). Questions and answers in attitude surveys: Experiments in question form, wording, and context. New York: Academic Press.

Schwarz, N., Strack, F., & Mai, H. P. (1991). Assimilation and contrast effects in part-whole question sequences: A conversational logic analysis. Public Opinion Quarterly, 55, 3-23.

Stadtmüller, S. & Porst, R. Wie man die Rücklaufquote bei postalischen Befragungen erhöht. http://www.gesis.org/fileadmin/upload/forschung/publikationen/gesis_reihen/howto/how-to14rp.pdf

Sudman, S., Bradburn, N. M. & Schwarz, N. (1996). Thinking about answers: The application of cognitive processes to survey methodology. San Francisco: Jossey-Bass.

Tourangeau, R., Rips, L. J. & Rasinski, K. (Druck 2006, Auflage 2000). The psychology of survey response. Cambridge: Cambridge University Press.

You have to register for the 6th International Research Workshop to participate in this course.

Introduction to MaxQDA for Case Studies

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Heiko Grunenberg (Leuphana University Lüneburg)

Date:

04.10.2012, 14:00 – 17:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: English

Contents:

This workshop is directly affiliated to the course “Case Study Research”. We want to see, how the ideas and approaches of “Case Study Research” could be transacted with a software of qualitative research like MAXqda.

It is not necessary to have deep knowledge about MAXqda, but please have a look at http://www.maxqda.com to understand the basic steps of computer assisted qualitative research.

References
Lewins, Ann/ Silver, Christina (2007): Using Software in Qualitative Research: A Step-By-Step Guide. SAGE: London.
Gerring, John (2006): Case Study Research: Principles and Practices. Cambridge University Press: Cambridge.

You have to register for the 6th International Research Workshop to participate in this course.

Qualitative Inquiry and Content Analysis with MAXQDA

Institution: see Organisers & Acknowledgements

Program of study: International Research Workshop

Lecturer: Heiko Grunenberg (Leuphana University Lüneburg)

Date:

04.10.2012, 09:00 – 12:30
05.10.2012, 09:00 – 12:30

Room: n.s.

Max. number of participants: 20

Semester periods per week: n.s.

Credit Points: 5 CP for participating in the whole IRWS

Language of instruction: German

Contents:

MAXqda is a software to analyze textual data in a qualitative (but also quantitative) way. The course provides a basic introduction into the logic of the program and its broad possibilities. The goal is to enable you to use this tool accordingly to your own method of analysis. For this reason, everybody can practice our working-steps at an own Computer. We will start at the very beginning and learn about the basic features of the program such as preparation and import of texts, basic analysis strategies and creation of codes, memos and variables. After this, we will focus on analysis strategies, simple and complex text retrievals. At the end, we will take a short excursion into the quantitative content analysis of counting and numbers.

References
Kuckartz, Udo (2010): Einführung in die computergestützte Analyse qualitativer Daten. VS-Verlag Wiesbaden.
Lewins, Ann/ Silver, Christina (2007): Using Software in Qualitative Research: A Step-By-Step Guide. SAGE: London.

You have to register for the 6th International Research Workshop to participate in this course.