Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Computational methods for querying and sampling the Twitter disinformation datasets

Holmberg, Nils LU orcid (2020) The Carnegie Partnership for Countering Influence Operations
Abstract
This study attempts to apply computational methods to the Twitter Election Integrity Datasets in order to derive a basic descriptive overview of this disinformation data, and to suggest some possible routes for developing these methods to address future research questions. The results indicate substantial variations in tweet frequency over time and geographical regions, as well as differences in relative importance of tweet words across regions. Aggregated tweet measures provide basic descriptive statistics for the datasets.
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to conference
publication status
unpublished
subject
keywords
social media, disinformation, computational methods, text analysis, content analysis, R package
conference name
The Carnegie Partnership for Countering Influence Operations
conference location
United Kingdom
conference dates
2020-11-17 - 2020-11-24
project
Web-based influence campaigns - computational content analysis and user gaze interaction
language
English
LU publication?
yes
id
73f6cdff-b51c-454e-b035-a8467ca3946d
date added to LUP
2021-03-11 10:28:28
date last changed
2021-03-31 13:26:38
@misc{73f6cdff-b51c-454e-b035-a8467ca3946d,
  abstract     = {{This study attempts to apply computational methods to the Twitter Election Integrity Datasets in order to derive a basic descriptive overview of this disinformation data, and to suggest some possible routes for developing these methods to address future research questions. The results indicate substantial variations in tweet frequency over time and geographical regions, as well as differences in relative importance of tweet words across regions. Aggregated tweet measures provide basic descriptive statistics for the datasets.}},
  author       = {{Holmberg, Nils}},
  keywords     = {{social media; disinformation; computational methods; text analysis; content analysis; R package}},
  language     = {{eng}},
  month        = {{11}},
  title        = {{Computational methods for querying and sampling the Twitter disinformation datasets}},
  url          = {{https://lup.lub.lu.se/search/files/96140407/teid_report.pdf}},
  year         = {{2020}},
}