Evidence map›Paper›PMID 36311478›Full record

ArticleInformation systems frontiers : a journal of research and innovation2022

Digital Resilience in Dealing with Misinformation on Social Media during COVID-19: A Web Application to Assist Users in Crises.

Stefka Schmid, Katrin Hartwig, Robert Cieslinski, Christian Reuter

Open access · hybridAbstract read
In one paragraph

Article in Information systems frontiers : a journal of research and innovation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
4.7field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Stefka SchmidTU Darmstadt, Science and Technology for Peace and Security (PEASEC), Pankratiusstraße 2, 64289 Darmstadt, Germany.ORCID 0000-0003-0948-8893
Katrin HartwigTU Darmstadt, Science and Technology for Peace and Security (PEASEC), Pankratiusstraße 2, 64289 Darmstadt, Germany.ORCID 0000-0003-4875-0110
Robert CieslinskiTU Darmstadt, Science and Technology for Peace and Security (PEASEC), Pankratiusstraße 2, 64289 Darmstadt, Germany.
Christian ReuterTU Darmstadt, Science and Technology for Peace and Security (PEASEC), Pankratiusstraße 2, 64289 Darmstadt, Germany.ORCID 0000-0003-1920-038X
Technische Universität Darmstadt · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In crises such as the COVID-19 pandemic, it is crucial to support users when dealing with social media content. Considering digital resilience, we propose a web app based on Social Network Analysis (SNA) to provide an overview of potentially misleading vs. non-misleading content on Twitter, which can be explored by users and enable foundational learning. The latter aims at systematically identifying thematic patterns which may be associated with misleading information. Additionally, it entails reflecting on indicators of misleading tweets which are proposed to approach classification of tweets. Paying special attention to non-expert users of social media, we conducted a two-step

Indexed as

COVID-19Crisis communicationFake newsNetwork analysisUser-centered

Identifiers

PMID36311478
PMCPMC9589652
OpenAlexW4307298426

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.