Günter Wiedemann
Dados Biográficos
| ID | 1908183 |
|---|---|
| NOME | Günter Wiedemann |
| PRENOMES | Günter |
| SOBRENOME | Wiedemann |
| ASSINATURA | WIEDEMANN G |
| AFILIAÇÕES | Leipzig University |
| ORCID | 0000-0002-4239-295X |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 18 |
| TOTAL DE CITAÇÕES | 139 |
| OBRAS COMO AUTOR | 18 |
| OBRAS COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2000 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 3 |
A Community Data Trustee for Sensitive Data Sharing in Far-Right Online Research
Data sharing poses a major challenge for digital media and communication research, particularly in sensitive areas such as far-right online studies. This article introduces the innovative concept of a “community data trustee” (CDT), a research infrastructure aimed at fostering collaboration and the sharing of research data, such as digital account lists. Compiling these lists is a critical yet labor-intensive step in many research projects; shari…
Few-shot learning for automated content analysis
Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the coding of complex semantic categories in large datasets via supervised machine learning. However, three characteristics so far impeded the widespread adoption of the methods in the applying disciplines: the dom…
Telegram in der politischen Öffentlichkeit. Zur Einführung in das Themenheft
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
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 …
Applying LDA Topic Modeling in Communication Research
Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of…
Proportional Classification Revisited
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
Exemplary Study
V-TM – A Methodological Framework for Social Science
Introduction
Summary
Computer-Assisted Text Analysis in the Social Sciences
Text Mining for Qualitative Data Analysis in the Social Sciences
Text Mining in Den Sozialwissenschaften
A review of health hazards linked to the use of lasers for stone cleaning
Hazardous emissions and health risk during laser cleaning of natural stones
Assessment of laser cleaning rate on limestones and sandstones
Laser cleaning applied in the restoration of a medieval wooden panel chamber at Pirna
Applying LDA Topic Modeling in Communication Research
Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of…
Text Mining for Qualitative Data Analysis in the Social Sciences
Proportional Classification Revisited
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…
Assessment of laser cleaning rate on limestones and sandstones
Assessment of laser cleaning rate on limestones and sandstones
Laser cleaning applied in the restoration of a medieval wooden panel chamber at Pirna
A review of health hazards linked to the use of lasers for stone cleaning
Hazardous emissions and health risk during laser cleaning of natural stones
Text Mining in Den Sozialwissenschaften
Integrating Text Mining Applications for Complex Analysis
Exemplary Study
V-TM – A Methodological Framework for Social Science
Introduction
Summary
Computer-Assisted Text Analysis in the Social Sciences
Text Mining for Qualitative Data Analysis in the Social Sciences
Applying LDA Topic Modeling in Communication Research
Latent Dirichlet allocation (LDA) topic models are increasingly being used in communication research. Yet, questions regarding reliability and validity of the approach have received little attention thus far. In applying LDA to textual data, researchers need to tackle at least four major challenges that affect these criteria: (a) appropriate pre-processing of the text collection; (b) adequate selection of model parameters, including the number of…
Proportional Classification Revisited
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
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
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…
Few-shot learning for automated content analysis
Pre-trained language models (PLM) based on transformer neural networks developed in the field of natural language processing (NLP) offer great opportunities to improve automatic content analysis in communication science, especially for the coding of complex semantic categories in large datasets via supervised machine learning. However, three characteristics so far impeded the widespread adoption of the methods in the applying disciplines: the dom…
A Community Data Trustee for Sensitive Data Sharing in Far-Right Online Research
Data sharing poses a major challenge for digital media and communication research, particularly in sensitive areas such as far-right online studies. This article introduces the innovative concept of a “community data trustee” (CDT), a research infrastructure aimed at fostering collaboration and the sharing of research data, such as digital account lists. Compiling these lists is a critical yet labor-intensive step in many research projects; shari…
Computer Science (10 obras) · Computational and Text Analysis Methods (9 obras) · Data science (8 obras) · Engineering (6 obras) · Sociology (6 obras) · Political science (5 obras) · Laser (4 obras) · Laser Material Processing Techniques (4 obras) · Optics (4 obras) · Social science (4 obras)