Evidence map›Paper›PMID 35034997›Full record

ArticleJournal of business research2022

Sociocultural factors during COVID-19 pandemic: Information consumption on Twitter.

Maximiliano Perez-Cepeda, Leopoldo G Arias-Bolzmann

Abstract read
In one paragraph

Article in Journal of business research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Maximiliano Perez-CepedaUniversidad Católica de Santiago de Guayaquil, Address Av. Pdte. Carlos Julio Arosemena Tola, Guayaquil, Ecuador.
Leopoldo G Arias-BolzmannCENTRUM Graduate Business School, Pontificia Universidad Católica del Perú, Address Jirón Daniel Alomía Robles 125 Urbanización Los Álamos de Monterrico, Santiago de Surco, Lima 33, Peru.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of the research is to describe the sociocultural factors that emerged during the COVID-19 pandemic. Twitter is used as an instrument for data collection. The study is qualitative and uses the netnographic method. To analyze the flow of messages posted on Twitter, the model proposed by Perez-Cepeda and Arias-Bolzmann (2020), which describes sociocultural factors, is taken as a basis. The semantics that people use are a type of functional knowledge that reveals sociocultural factors. Sentiments were analyzed through lexicon-based methods, which are the most suitable. The categorization and classification of the data are performed based on the information that users post on Twitter. The tweets related to COVID-19 describe the sociocultural issues and the level of sentiment around the pandemic. The discussion centers on the COVID-19 pandemic, information consumption, lexicon, sociocultural factors and sentiment analysis. The study was limited to the social media Twitter; another limitation was not to consider the social group of the users who interact with @pandemic_Covid-19, official account of the World Health Organization (WHO). This research contributes to the social sciences, focusing on sociocultural interaction through the use of the social network Twitter. It describes the link between sociocultural factors and the level of sentiment on issues related to the COVID-19 pandemic.

Indexed as

COVID-19NetnographySentiment analysisSociocultural factorsTwitter

Identifiers

PMID35034997
PMCPMC8743443

What OpenQuestion holds

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Registered trials

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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.