ArticleScientific reports2024
Analyzing LinkedIn data to explore the relationships between sustainable development goals, circular economy, and electoral dynamics.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
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Who cites it
2 citing papers in PubMed.
- Mutual benefits of social learning and algorithmic mediation for cumulative culture.Journal of the Royal Society, Interface · 2025Article
- Sustainable communities: we are the world.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In 2015, all United Nations Member States adopted 17 Sustainable Development Goals (SDGs) for the 2030 agenda. Addressing the issue of employing alternative data sources for exploring aspects of utilizing said goals, this paper explores the Circular Economy dimension within the SDG12 score, focusing on responsible production and consumption and the broader SDG index. Data from LinkedIn are collected, examining profiles, companies, job postings, and services using the keywords 'Sustainable Development Goals' and 'Circular Economy'. Furthermore, the SDG index (including the SDG12 score) for the United States is integrated in the analysis; SDG is a published metric evaluating the progress of sustainable communities within each state. Finally, data on the past five US general elections are retrieved, in order to explore the relationship between SDGs, Circular Economy, and voting behavior. Regression analyses incorporating PCA components and state election data reveal that the LinkedIn-derived SDG and circular economy components exhibit positive impacts on the corresponding indices. Notably, a state's political inclination toward the Republican or the Democratic parties highlights contrasting effects on the SDG and SDG12 indices, indicating divergent trends based on electoral choices. Overall, this study underscores LinkedIn's potential as a valuable source for assessing SDG and Circular Economy position in the US, and highlights the interplay between political factors and sustainable communities at state level.
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Registered trials
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.