Evidence map›Paper›PMID 35634058›Full record

ArticleComputational intelligence and neuroscience2022

The Application of Digital Technology in the Complex Situation of News Dissemination from the Perspective of New Media Art.

Xunxun Jiang, Tong Mao, Jing Tian

RetractedOpen access · hybridAbstract readNewsRetracted Publication
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
2.6field-weighted citation impact, top 7% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Xunxun JiangSchool of Journalism and Communication, Jilin Normal University, Changchun 130021, Jilin, China.ORCID https://orcid.org/0000-0002-3168-1481
Tong MaoSchool of Journalism and Communication, Jilin Normal University, Changchun 130021, Jilin, China.ORCID https://orcid.org/0000-0001-5617-5510
Jing TianSchool of Journalism and Communication, Jilin Normal University, Changchun 130021, Jilin, China.
Jilin Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the continous innovation of new media technology, the media environment of the entire society has undergone profound changes. Digital technology has had a profound impact on the way news is disseminated. It has made a significant impact on the collecting, creation, and distribution of news, as well as the way viewers receive it. As a result, the news media's operation and management style is continually modified. However, in the process of news dissemination, the situations involved are complex and changeable, which leads to different digital technology applications. Aiming at different complex situations in news dissemination under the vision of new media art, this work designs a neural network to optimize the distribution for the required digital technology application schemes. The main work of this paper has the following two points. First, it systematically investigates the current research status of news communication based on digital technology and analyzes the research trends of digital technology and news communication in complex contexts under the vision of new media art. Second, a new neural network is proposed for the optimal application of digital technology for news propagation in different complex situations. This neural network uses an improved particle swarm optimization algorithm and an improved network training strategy to improve the BP network, which can effectively solve the shortcomings of the BP network. A large number of experiments have proved the effectiveness and correctness of this method.

Indexed as

Digital TechnologyNeural Networks, ComputerAlgorithmsCommunicationTechnology

Identifiers

PMID35634058
PMCPMC9142303
OpenAlexW4281251096

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.