English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  Neural topic modeling reveals German television’s climate change coverage

Schirmag, T., Wedemeyer, J., Stechemesser, A., Wenz, L. (in press): Neural topic modeling reveals German television’s climate change coverage. - Communications Earth and Environment.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_32306 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_32306_1
Genre: Journal Article

Files

show Files
hide Files
:
SchirmagWenzEtAl.pdf (Any fulltext), 620KB
 
File Permalink:
-
Name:
SchirmagWenzEtAl.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show
hide
Locator:
https://zenodo.org/records/15333784 (Supplementary material)
Description:
Code and Data

Creators

show
hide
 Creators:
Schirmag, Tatjana1, Author              
Wedemeyer, Jakob1, Author              
Stechemesser, Annika1, Author              
Wenz, Leonie1, 2, Author              
Affiliations:
1Potsdam Institute for Climate Impact Research, ou_persistent13              
2Submitting Corresponding Author, Potsdam Institute for Climate Impact Research, ou_29970              

Content

show

Details

show
hide
Language(s): eng - English
 Dates: 2025-05-19
 Publication Status: Accepted / In Press
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: MDB-ID: No MDB - stored outside PIK (see locators/paper)
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
PIKDOMAIN: RD5 - Climate Economics and Policy - MCC Berlin
Organisational keyword: RD5 - Climate Economics and Policy - MCC Berlin
Organisational keyword: Lab - Societal Transition and Well-being
Organisational keyword: Lab - Policy Evaluation
Research topic keyword: Climate Policy
Research topic keyword: Climate impacts
Regional keyword: Germany
Model / method: Machine Learning
OATYPE: Gold - DEAL Springer Nature
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Communications Earth and Environment
Source Genre: Journal, SCI, Scopus, oa
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/communications-earth-environment
Publisher: Nature