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Gregor Wiedemann

Biographic Data

ID9303735
NAMEGregor Wiedemann
GIVEN NAMESGregor
FAMILY NAMEWiedemann
SIGNATUREWIEDEMANN G
AFFILIATIONSUniversität Hamburg
VERIFIEDNo
TOTAL WORKS12
TOTAL CITATIONS73
WORKS AS AUTHOR11
WORKS AS EDITOR1
FIRST PUBLICATION YEAR2015
LATEST PUBLICATION YEAR2023
H-INDEX2
  • Telegram in der politischen Öffentlichkeit. Zur Einführung in das Themenheft

    Open Access•Günter Wiedemann, Gregor Wiedemann et al.•ARTICLE•Medien & Kommunikationswissenschaft•2023

    Telegram ist in den vergangenen Jahren zu einem relevanten Bestandteil der politischen Öffentlichkeit geworden. Der Instant-Messaging-Dienst unterstützt sowohl den interpersonalen Austausch als auch die Informationsverteilung an nahezu beliebig große Publika. Zugleich entzieht er sich bislang vergleichsweise erfolgreich allen Regulierungsversuchen, die Verbreitung von Desinformationen, Hassrede oder anderen problematischen Inhalten einzuschränken…

  • The World of Topic Modeling in R

    Open Access•Günter Wiedemann, Gregor Wiedemann•ARTICLE•Medien & Kommunikationswissenschaft•2022

    This software review provides a systematic overview of R packages for topic modeling. These packages facilitate the application of computational text analysis to conduct research compatible with a wide variety of methodological frameworks employed in the social and communication sciences. For this overview, the analysis process is divided into four steps: preprocessing, inference, evaluation, and interpretation of topic models. The summary shows …

  • Proportional Classification Revisited

    Open Access•Günter Wiedemann, Gregor Wiedemann•ARTICLE•Social Science Computer Review•2018•Cited by: 9•References: 7

    Supervised machine learning is a promising methodological innovation for content analysis (CA) to approach the challenge of ever-growing amounts of text in the digital era. Social scientists have pointed to accurate measurement of category proportions and trends in large collections as their primary goal. Proportional classification, for example, allows for time-series analysis of diachronic data sets or correlation of categories with text-extern…

  • Integrating Text Mining Applications for Complex Analysis

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Exemplary Study

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • V-TM – A Methodological Framework for Social Science

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Introduction

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Summary

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Computer-Assisted Text Analysis in the Social Sciences

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Text Mining for Qualitative Data Analysis in the Social Sciences

    Open Access•Günter Wiedemann, Gregor Wiedemann•BOOK•Text Mining for Qualitative Data…•2016•Cited by: 64

  • Text Mining in Den Sozialwissenschaften

    Gregor Wiedemann, Matthias Lemke•BOOK•Text Mining in Den Sozialwissenscha…•2015

  • Text Mining in Den Sozialwissenschaften

    Günter Wiedemann, Matthias Lemke et al.•EDITOR•BOOK•Text Mining in Den Sozialwissenscha…•2015

  • Text Mining for Qualitative Data Analysis in the Social Sciences

    Open Access•Günter Wiedemann, Gregor Wiedemann•BOOK•Text Mining for Qualitative Data…•2016•Cited by: 64

  • Proportional Classification Revisited

    Open Access•Günter Wiedemann, Gregor Wiedemann•ARTICLE•Social Science Computer Review•2018•Cited by: 9•References: 7

    Supervised machine learning is a promising methodological innovation for content analysis (CA) to approach the challenge of ever-growing amounts of text in the digital era. Social scientists have pointed to accurate measurement of category proportions and trends in large collections as their primary goal. Proportional classification, for example, allows for time-series analysis of diachronic data sets or correlation of categories with text-extern…

  • Text Mining in Den Sozialwissenschaften

    Gregor Wiedemann, Matthias Lemke•BOOK•Text Mining in Den Sozialwissenscha…•2015

  • Text Mining in Den Sozialwissenschaften

    Günter Wiedemann, Matthias Lemke et al.•EDITOR•BOOK•Text Mining in Den Sozialwissenscha…•2015

  • Integrating Text Mining Applications for Complex Analysis

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Exemplary Study

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • V-TM – A Methodological Framework for Social Science

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Introduction

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Summary

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Computer-Assisted Text Analysis in the Social Sciences

    Open Access•Günter Wiedemann, Gregor Wiedemann•CHAPTER•Text Mining for Qualitative Data…•2016

  • Text Mining for Qualitative Data Analysis in the Social Sciences

    Open Access•Günter Wiedemann, Gregor Wiedemann•BOOK•Text Mining for Qualitative Data…•2016•Cited by: 64

  • Proportional Classification Revisited

    Open Access•Günter Wiedemann, Gregor Wiedemann•ARTICLE•Social Science Computer Review•2018•Cited by: 9•References: 7

    Supervised machine learning is a promising methodological innovation for content analysis (CA) to approach the challenge of ever-growing amounts of text in the digital era. Social scientists have pointed to accurate measurement of category proportions and trends in large collections as their primary goal. Proportional classification, for example, allows for time-series analysis of diachronic data sets or correlation of categories with text-extern…

  • The World of Topic Modeling in R

    Open Access•Günter Wiedemann, Gregor Wiedemann•ARTICLE•Medien & Kommunikationswissenschaft•2022

    This software review provides a systematic overview of R packages for topic modeling. These packages facilitate the application of computational text analysis to conduct research compatible with a wide variety of methodological frameworks employed in the social and communication sciences. For this overview, the analysis process is divided into four steps: preprocessing, inference, evaluation, and interpretation of topic models. The summary shows …

  • Telegram in der politischen Öffentlichkeit. Zur Einführung in das Themenheft

    Open Access•Günter Wiedemann, Gregor Wiedemann et al.•ARTICLE•Medien & Kommunikationswissenschaft•2023

    Telegram ist in den vergangenen Jahren zu einem relevanten Bestandteil der politischen Öffentlichkeit geworden. Der Instant-Messaging-Dienst unterstützt sowohl den interpersonalen Austausch als auch die Informationsverteilung an nahezu beliebig große Publika. Zugleich entzieht er sich bislang vergleichsweise erfolgreich allen Regulierungsversuchen, die Verbreitung von Desinformationen, Hassrede oder anderen problematischen Inhalten einzuschränken…

Computational and Text Analysis Methods (8 works) · Computer Science (8 works) · Data science (7 works) · Sociology (5 works) · Political science (4 works) · Artificial Intelligence (3 works) · Engineering (3 works) · Management science (3 works) · Qualitative analysis (3 works) · Qualitative research (3 works)

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