61 citations · 107 across the 12 of their papers we have counts for
12 papers
Using Language Models on Low-end Hardware
Fabian Ziegner, Janos Borst, Andreas Niekler +1
This paper evaluates the viability of using fixed language models for training text classification networks on low-end hardware. We combine language models with a CNN architecture…
Using Text Classification with a Bayesian Correction for Estimating Overreporting in the Creditor Reporting System on Climate Adaptation Finance
Janos Borst, Thomas Wencker, Andreas Niekler
Development funds are essential to finance climate change adaptation and are thus an important part of international climate policy. % However, the absence of a common reporting pr…
Application of the interactive Leipzig Corpus Miner as a generic research platform for the use in the social sciences
Christian Kahmann, Andreas Niekler, Gregor Wiedemann
This article introduces to the interactive Leipzig Corpus Miner (iLCM) - a newly released, open-source software to perform automatic content analysis. Since the iLCM is based on th…
Small-Text: Active Learning for Text Classification in Python
Christopher Schröder, Lydia Müller, Andreas Niekler +1
We introduce small-text, an easy-to-use active learning library, which offers pool-based active learning for single- and multi-label text classification in Python. It features nume…
Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers
Christopher Schröder, Andreas Niekler, Martin Potthast
Active learning is the iterative construction of a classification model through targeted labeling, enabling significant labeling cost savings. As most research on active learning h…
Supporting Land Reuse of Former Open Pit Mining Sites using Text Classification and Active Learning
Christopher Schröder, Kim Bürgl, Yves Annanias +7
Open pit mines left many regions worldwide inhospitable or uninhabitable. To put these regions back into use, entire stretches of land must be renaturalized. For the sustainable su…
A Survey of Active Learning for Text Classification using Deep Neural Networks
Christopher Schröder, Andreas Niekler
Natural language processing (NLP) and neural networks (NNs) have both undergone significant changes in recent years. For active learning (AL) purposes, NNs are, however, less commo…
iLCM - A Virtual Research Infrastructure for Large-Scale Qualitative Data
Andreas Niekler, Arnim Bleier, Christian Kahmann +5
The iLCM project pursues the development of an integrated research environment for the analysis of structured and unstructured data in a "Software as a Service" architecture (SaaS)…
Detecting and assessing contextual change in diachronic text documents using context volatility
Christian Kahmann, Andreas Niekler, Gerhard Heyer
Terms in diachronic text corpora may exhibit a high degree of semantic dynamics that is only partially captured by the common notion of semantic change. The new measure of context…
Modeling the dynamics of domain specific terminology in diachronic corpora
Gerhard Heyer, Cathleen Kantner, Andreas Niekler +2
In terminology work, natural language processing, and digital humanities, several studies address the analysis of variations in context and meaning of terms in order to detect sema…
Leipzig Corpus Miner - A Text Mining Infrastructure for Qualitative Data Analysis
Andreas Niekler, Gregor Wiedemann, Gerhard Heyer
This paper presents the "Leipzig Corpus Miner", a technical infrastructure for supporting qualitative and quantitative content analysis. The infrastructure aims at the integration…
Document Retrieval for Large Scale Content Analysis using Contextualized Dictionaries
Gregor Wiedemann, Andreas Niekler
This paper presents a procedure to retrieve subsets of relevant documents from large text collections for Content Analysis, e.g. in social sciences. Document retrieval for this pur…