Evidence map›Paper›PMID 39773431›Full record

ArticleBMC public health2025

Health promotion campaigns using social media: association rules mining and co-occurrence network analysis of Twitter hashtags.

Atousa Ghahramani, Maria Prokofieva, Maximilian Pangratius de Courten

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

3 authors.

Atousa GhahramaniInstitute for Sustainable Industries & Liveable Cities, Business School, Victoria University, 370 Little Lonsdale St, Melbourne VIC 3000, Australia. atousa.ghahramani@live.vu.edu.au.
Maria ProkofievaInstitute for Sustainable Industries & Liveable Cities, Business School, Victoria University, 370 Little Lonsdale St, Melbourne VIC 3000, Australia.
Maximilian Pangratius de CourtenVictoria University, Institute for Health and Sport and Australian Health Policy Collaboration, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media hashtags play a significant role in increasing the visibility of health information by making it easier for people to explore health-related content. Health promotion campaigns use campaign-specific hashtags to disseminate health-related messages, enabling individuals to access accurate and timely resources and updates. The study aims to discover patterns of connection between hashtags and identify the most influential hashtags used on Twitter in the American Heart Month campaigns.

methodWe collected a total of 73,288 tweets containing #AmericanHeartMonth between January 2019 and March 2023 and retrieved 18,143 original tweets, 42,930 retweets, 2,519 quotes, and 20,846 likes related to the past five campaigns. We adapted co-occurrence network analysis to explore the patterns of relationships between hashtags and association rules mining to assess the quality and strength of association between the co-occurred hashtags.

resultWhile #AmericanHeartMonth, #OurHearts, and #HeartMonth play central roles in all hashtag co-occurrence networks, the results of association rules mining indicate a significant association of #OurHearts within the networks. The highest density of hashtags has been observed in the quoted tweets, introducing a new range of hashtags such as #GoRedForWomen, #WearRedDay, #HeartDisease, and #HeartHealth by Twitter users, indicating the positive correlation between co-occurring hashtags and users' engagement. The results of quality measurements of association rules (Lift > 1) indicate positive relationships between the co-occurred hashtags in the top 5 rules in all data subsets.

conclusionWe employed co-occurrence network analysis and association rules mining as powerful techniques to identify influential hashtags that may have a central role in health-related discussions and drive engagement within the co-occurrence hashtag network. In conclusion, we recommend additional hashtag structures in conjunction with heart health-related topics to improve community building and the effectiveness of disseminating messages in future heart health promotion campaigns. The study contributes to knowledge and practice by offering a structured and data-driven approach and providing practical guidance for public health practitioners, professionals, and organisations to optimise content, targeting, and messaging to reach and engage a broader audience with health-related information.

Indexed as

Health PromotionSocial MediaData MiningHumansUnited StatesAssociation rules miningCo-occurrence networksHashtag analysisHealth promotionTwitter

Identifiers

PMID39773431
PMCPMC11706027

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.