Protocol for spatiotemporal analysis of climate-induced negative sentiment in social media.

Tareq Al-Ahdal, Sandra Barman, Barrak Alahmad, Joacim Rocklöv

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In one paragraph

Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in

0citing papers in PubMed

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Tareq Al-AhdalHeidelberg Institute of Global Health, Section for Oral Health, Faculty of Medicine and University Hospital, Heidelberg University, Heidelberg, Germany; Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany. Electronic address: tareq.al-ahdal@uni-heidelberg.de.

Sandra BarmanBioeconomy and Health, RISE Research Institutes of Sweden, Gothenburg, Sweden.

Barrak AlahmadDepartment of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.

Joacim RocklövInterdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany; Department of Public Health and Clinical Medicine, Section of Sustainable Health, Umeå University, Umeå, Sweden; Heidelberg Institute of Global Health (HIGH), Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany. Electronic address: joacim.rocklov@umu.se.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate-induced stressors are associated with population-level mental well-being, yet reproducible workflows linking environmental data to social media sentiment remain scarce. Here, we present a protocol for analyzing spatiotemporal associations between climate-induced stressors and negative sentiment from geotagged social media data. We describe steps for preprocessing large-scale geotagged X data, performing multilingual sentiment analysis with Linguistic Inquiry and Word Count (LIWC-22), integrating climate and health indicators, and fitting a Bayesian spatiotemporal Poisson model. This protocol supports analyses of associations across diverse climate stressors and European regions. For complete details on the use and execution of this protocol, please refer to Al-Ahdal et al.

Indexed as

Computer sciencesEnvironmental sciencesHealth Sciences

Identifiers

PMID42334922

DOI10.1016/j.xpro.2026.104656

PMCPMC13319716

What Socratic holds

Textmetadata

LicenceCC BY

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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 Socratic graph.