Detecting Connectivity Patterns in Nordic Twittersphere by Cluster Analysis
Approved
Classifications
MinEdu publication type
A1 Journal article (peer-reviewed)
Definition
Article
Target group
Scientific
Peer reviewed
Peer-reviewed
Article type
Journal article
Host publication type
Journal
Publication channel information
Title of journal/series
SN computer science
ISSN (print)
2662-995X
ISSN (electronic)
2661-8907
ISSN (linking)
2661-8907
Publication forum ID
89308
Publication forum level
1
Internationality
Yes
Detailed publication information
Publication year
2025
Reporting year
2025
Journal/series volume number
6
Journal/series issue number
7
Article number
815
DOI
10.1007/s42979-025-04353-y
Language of publication
English
Co-publication information
International co-publication
Yes
Co-publication with a company
No
Availability
Link to online publication
Link to self-archived version
Classification and additional information
MinEdu field of science classification
113 Computer and information sciences
Keywords
Clustering; Community detection; Graph clustering; Nordic countries; Social networks; Twitter users
Additional information
Correction: https://doi.org/10.1007/s42979-025-04443-x
Funding information
Funding information in the publication
This project has received funding from the European Union – NextGenerationEU instrument and is funded by the Research Council of Finland under grant numbers 345640, 358725, 367757 (FIRI 2022–29) and 364048 (COMET Academy project for 2024–2028). We also would like to thank CSC – IT Center for Science for providing access to their supercomputers, which were essential for data storage and code execution required for this project. The project also received early stage funding from the Center for Data Intensive Sciences and Application (DISA) at Linnaeus University.
Source database ID
Scopus ID
2-s2.0-105015490229