DIFFERENCES IN SOCIAL STRATIFICATION COMMUNITY PERCEPTIONS OF POST-TRUTH MANAGEMENT

The post-truth phenomenon that is developing in society is having very powerful social impacts. Many lower levels of society believe in information that seems to be true, but is not supported by sufficient evidence and relative facts. The emergence of information that is not balanced with the reality of what is happening makes all groups consisting of; among students/akademics, entrepreneur, and the public in responden to the post-truth phenomenon in social life. The reasearch is aim at how society manages post-truth correctly and in a balanced manner. This research is included in the category of explanatory research, which uses hypoteses (hypothesis testing). The data sources used are nominal and primary data obtained through distributing questionnaires using a likert scale. Sampling was carried out using a purposive sampling model with certain criteria based on the sosial strata of the community, totaling 180 respondents. Dat analysis uses multivariate variance (Manova). The risearch results show that: 1) student, entrepreneurs, and public can manage post-truth by thinking critically, understanding digital literacy, and knowing social media algoritms well and wisely; 2) There is a significant difference in perspective between them (students, entrepreneurs, and public) regarding good and wise post-truth management.

Authors

Institutions

Publication Details

Journal
Moestopo International Review on Social Humanities and Sciences
Published
2025-04-17
DOI
https://doi.org/10.32509/mirshus.v5i1.109
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

DIFFERENCES IN SOCIAL STRATIFICATION COMMUNITY PERCEPTIONS OF POST-TRUTH MANAGEMENT

Jubery Marwan, Aji Yoga Sekar
Moestopo International Review on Social Humanities and Sciences
Opinion Dynamics and Social Influence
article

DIFFERENCES IN SOCIAL STRATIFICATION COMMUNITY PERCEPTIONS OF POST-TRUTH MANAGEMENT

Jubery Marwan, Aji Yoga Sekar
article en

Abstract

The post-truth phenomenon that is developing in society is having very powerful social impacts. Many lower levels of society believe in information that seems to be true, but is not supported by sufficient evidence and relative facts. The emergence of information that is not balanced with the reality of what is happening makes all groups consisting of; among students/akademics, entrepreneur, and the public in responden to the post-truth phenomenon in social life. The reasearch is aim at how society manages post-truth correctly and in a balanced manner. This research is included in the category of explanatory research, which uses hypoteses (hypothesis testing). The data sources used are nominal and primary data obtained through distributing questionnaires using a likert scale. Sampling was carried out using a purposive sampling model with certain criteria based on the sosial strata of the community, totaling 180 respondents. Dat analysis uses multivariate variance (Manova). The risearch results show that: 1) student, entrepreneurs, and public can manage post-truth by thinking critically, understanding digital literacy, and knowing social media algoritms well and wisely; 2) There is a significant difference in perspective between them (students, entrepreneurs, and public) regarding good and wise post-truth management.

Moestopo International Review on Social Humanities and SciencesVol. 5(1)
Police Department (LT), Universitas Prof Dr Moestopo (ID)
Openalex Percentile: Top 93%
Opinion Dynamics and Social Influence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.