Evidence map›Paper›PMID 36246340›Full record

ArticleInternational journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management2023

Predicting opinion evolution based on information diffusion in social networks using a hybrid fuzzy based approach.

Samson Ebenezar Uthirapathy, Domnic Sandanam

Abstract read
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In one paragraph

Article in International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Samson Ebenezar UthirapathyDepartment of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu 620015 India.ORCID 0000-0002-4194-0600
Domnic SandanamDepartment of Computer Applications, National Institute of Technology, Tiruchirappalli, Tamil Nadu 620015 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Social media plays an important role in disseminating information and analysing public and government opinions. The vast majority of previous research has examined information diffusion and opinion analysis separately. This study proposes a new framework for analysing both information diffusion and opinion evolution. The change in opinion over time is known as opinion evolution. To propose a new model for predicting information diffusion and opinion analysis in social media, a forest fire algorithm, cuckoo search, and fuzzy c-means clustering are used. The forest fire algorithm is used to determine the diffuser and non-diffuser of information in social networks, and fuzzy c-means clustering with the cuckoo search optimization algorithm is proposed to cluster Twitter content into various opinion categories and to determine opinion change. On different Twitter data sets, the proposed model outperformed the existing methods in terms of precision, recall, and accuracy.

Indexed as

Cuckoo searchForest fire algorithmFuzzy C-means clusteringInformation diffusionOpinion analysisSocial network

Identifiers

PMID36246340
PMCPMC9554852

What OpenQuestion holds

Textmetadata
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.