Trajectories of Change: Approaches for Tracking Knowledge Evolution
원문 초록
We explore local vs. global evolution of knowledge systems through the framework of socio-epistemic networks (SEN), applying two complementary methods to a corpus of scientific texts. The framework comprises three interconnected layers-social, semiotic (material), and semantic-proposing a multilayered approach to understanding structural developments of knowledge. To analyse diachronic changes on the semantic layer, we first use information-theoretic measures based on relative entropy to detect semantic shifts, assess their significance, and identify key driving features. Second, variations in document embedding densities reveal changes in semantic neighbourhoods, tracking how concentration of similar documents increase, remain stable, or disperse. This enables us to trace document trajectories based on content (topics) or metadata (authorship, institution). Case studies of Joseph Silk and Hans-J\"urgen Treder illustrate how individual scholar's work aligns with broader disciplinary shifts in general relativity and gravitation research, demonstrating the applications, limitations, and further potential of this approach.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
QAEncoder: Towards Aligned Representation Learning in Question Answering System
ARAGOG: Advanced RAG Output Grading
HILL: Hierarchy-aware Information Lossless Contrastive Learning for Hierarchical Text Classification
Facilitating Interdisciplinary Knowledge Transfer with Research Paper Recommender Systems
Approach to Predicting News -- A Precise Multi-LSTM Network With BERT
BERTopic: Neural topic modeling with a class-based TF-IDF procedure
토론
이 논문과 연결된 포럼 글이 아직 없습니다.