Evidence map›Paper›PMID 37089901›Full record

ArticleJournal of big data2023

Free trade as domestic, economic, and strategic issues: a big data analytics approach.

Moch Faisal Karim, Reza Rahutomo, Ida Bagus Kerthyayana Manuaba, Kartika Purwandari, Tirta Nugraha Mursitama, Bens Pardamean

Abstract read
In one paragraph

Article in Journal of big data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Moch Faisal KarimDepartment of International Relations, Bina Nusantara University, Jakarta, Indonesia.
Reza RahutomoInformation System Department, School of Information Systems, Bina Nusantara University, Jakarta, 11480 Indonesia.
Ida Bagus Kerthyayana ManuabaComputer Science Program, Bina Nusantara University International, Jakarta, Indonesia.
Kartika PurwandariBioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, 11480 Indonesia.
Tirta Nugraha MursitamaDepartment of International Relations, Bina Nusantara University, Jakarta, Indonesia.
Bens PardameanBioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, 11480 Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article examines the engagement of domestic actors in public conversation surrounding free trade negotiations with a focus on the framing of these negotiations as economic, strategic or domestic issues. To analyse this topic, this article utilises the use of Twitter as a barometer of public sentiment toward the Regional Comprehensive Economic Partnership (RCEP). We employ topic classification and sentiment analysis to understand how RCEP is discussed in 345,015 tweets. Our findings show that the overall sentiment score towards RCEP is neutral. However, we find that when RCEP is discussed as a strategic issue, the sentiment is slightly more negative than when discussed as a domestic or economic issue. This article further suggests that discussion of RCEP is driven by the fear of China's geopolitical ambitions, domestic protectionist agendas, and impact of RCEP on the domestic economy. This article contributes to the growing use of big data in understanding trade negotiations. Furthermore, it contributes to the study of free trade negotiation by examining how domestic political actors frame free trade negotiations.

Indexed as

Big data analyticsFree tradeFTAInternational relationsMachine learningPolitical economyRCEP

Identifiers

PMID37089901
PMCPMC10104431

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.