ArticleHeliyon2023
Analytical method to improve the decision-making criteria approach in managing digital social channels.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 14 citations in OpenAlex.
- A Method for Reducing Training Time of ML-Based Cascade Scheme for Large-Volume Data Analysis.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study explores the decision-making process involved in managing digital communities in the digital social channel ecosystem, specifically in the context of antagonistic digital communication and harmful content dissemination. The rise of digital communities in social media has changed the way people interact with each other, form communities, and participate in social activities. However, these interactions can also lead to conflicts, and the dissemination of harmful content can pose a risk to users' information security. This research proposes a method to mitigate these issues and optimize efficacy while minimizing potential hazards. The proposed method is based on the analysis of the information situation in the management of digital communities under conditions of complete uncertainty, antagonistic behaviour, and partial uncertainty. The study examines the decision-making process involved in antagonistic interaction among users of digital social channels. The methods proposed in this research were implemented to prevent the adverse consequences of community conflicts and the dissemination of potential risks to the security of users' information through prompt and efficacious decision-making. The proposed strategy optimizes efficacy through the implementation of the Wald criteria while minimizing potential hazards by adhering to the Savage criteria. Additionally, the Hurwitz criteria, which presents a balanced approach incorporating both the maximum and minimum criteria, was also employed. The methods were tested within the online community present on the social media platform, Facebook social networks, and the results demonstrate that the suggested technique improves the effectiveness and validity of managers' decisions in digital communities. The study also highlights the use of social networks and the virtual sphere as tools for hybrid warfare on the internet, which can be effective. Effective community management is necessary to mitigate the negative effects of online interactions, and the proposed method offers a valuable tool for managers to make informed decisions and prevent adverse consequences.
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What OpenQuestion holds
Registered trials
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.