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TeCoMiner: Topic Discovery Through Term Community Detection

Hamm, Andreas and Thelen, Jana and Beckmann, Rasmus and Odrowski, Simon (2021) TeCoMiner: Topic Discovery Through Term Community Detection. [Other]

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Official URL: https://arxiv.org/abs/2103.12882

Abstract

This note is a short description of TeCoMiner, an interactive tool for exploring the topic content of text collections. Unlike other topic modeling tools, TeCoMiner is not based on some generative probabilistic model but on topological considerations about co-occurrence networks of terms. We outline the methods used for identifying topics, describe the features of the tool, and sketch an application, using a corpus of policy related scientific news on environmental issues published by the European Commission over the last decade.

Item URL in elib:https://elib.dlr.de/141584/
Document Type:Other
Title:TeCoMiner: Topic Discovery Through Term Community Detection
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Hamm, AndreasAndreas.Hamm (at) dlr.dehttps://orcid.org/0000-0001-5854-851X
Thelen, JanaUNSPECIFIEDUNSPECIFIED
Beckmann, RasmusRasmus.Beckmann (at) dlr.deUNSPECIFIED
Odrowski, SimonSimon.Odrowski (at) dlr.dehttps://orcid.org/0000-0001-9050-1711
Date:23 March 2021
Journal or Publication Title:arXiv.org
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Number of Pages:8
Status:Published
Keywords:Information extraction, text mining, NLP, word communities, modularity, topic detection, topic modelling,topic visualization, environmental policy
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Köln-Porz
Institutes and Institutions:Think Tank
Deposited By: Hamm, Andreas
Deposited On:29 Mar 2021 12:39
Last Modified:29 Mar 2021 12:39

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