Evidence map›Paper›PMID 42317634›Full record

ArticleData in brief2026

A cannabis use Reddit dataset for aspect-based sentiment analysis.

Tricia Park, Sahithi Lakamana, Aishwarya Alagappan, Catherine Diop Chalmers, Ege Gursel, Yuting Guo, Titilola Falasinnu, Abeed Sarker, Selen Bozkurt

Abstract read
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In one paragraph

Article in Data in brief, 2026. 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

9 authors.

Tricia ParkDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Sahithi LakamanaDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Aishwarya AlagappanStanford University School of Medicine, Stanford, CA 94305, USA.
Catherine Diop ChalmersDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Ege GurselDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Yuting GuoDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Titilola FalasinnuStanford University School of Medicine, Stanford, CA 94305, USA.
Abeed SarkerDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.
Selen BozkurtDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Using publicly accessible Reddit posts, we developed a manually annotated dataset for traditional and aspect-based sentiment analysis (ABSA) of cannabis-related discussions in the context of pain management. The dataset consists of 479 post-aspect pairs extracted from specific Reddit communities associated with autoimmune rheumatic diseases (ARDs). We filtered posts using a structured list of cannabis-related terms and extracted context using rule-based sentence segmentation. Subsequently, we manually annotated each post for both traditional and aspect-specific sentiment (positive, negative, neutral). Inter-annotator reliability was assessed using Krippendorff's ⍺, yielding ⍺ = 0.604 for traditional sentiment and ⍺ = 0.526 for aspect-based sentiment. The dataset offers valuable resources for training, benchmarking, and evaluating machine learning models for ABSA in health-related social media contexts. This dataset can support research in natural language processing, public health informatics, pain medicine, digital epidemiology, and social media-based health monitoring. All post identifiers are provided in compliance with platform policies, and annotations are included in tabular form. The final dataset is publicly available at https://zenodo.org/records/20214862.

Indexed as

Autoimmune rheumatic diseasesCannabisNatural language processingPain managementSentiment analysis

Identifiers

PMID42317634
PMCPMC13272552

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.