ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives

Hamed Rahimi, Hubert Naacke, Camelia Constantin, Bernd Amann
6/4/2023
cs.IRcs.AI

No confident code implementation found for this paper.

Abstract

This paper presents ATEM, a novel framework for studying topic evolution in scientific archives. ATEM is based on dynamic topic modeling and dynamic graph embedding techniques that explore the dynamics of content and citations of documents within a scientific corpus. ATEM explores a new notion of contextual emergence for the discovery of emerging interdisciplinary research topics based on the dynamics of citation links in topic clusters. Our experiments show that ATEM can efficiently detect emerging cross-disciplinary topics within the DBLP archive of over five million computer science articles.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

ANTM: An Aligned Neural Topic Model for Exploring Evolving Topics

86% match1 repo372023

Mapping the Evolution of Research Contributions using KnoVo

81% match2025

Exploring the evolution of research topics during the COVID-19 pandemic

81% match2023

The Rise of Open Science: Tracking the Evolution and Perceived Value of Data and Methods Link-Sharing Practices

81% match2023

Innovation and Word Usage Patterns in Machine Learning

81% match1 repo12023

Forgotten Knowledge: Examining the Citational Amnesia in NLP

80% match2023

Cite this paper

@article{rahimi2023atem,
  title  = {ATEM: A Topic Evolution Model for the Detection of Emerging Topics in Scientific Archives},
  author = {Hamed Rahimi and Hubert Naacke and Camelia Constantin and Bernd Amann},
  year   = {2023},
  eprint = {2306.02221},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2306.02221v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2306.02221.svg)](https://codeofpaper.com/paper/2306.02221)

Discussion