Evidence map›Paper›PMID 27227152›Full record

ArticleJMIR public health and surveillance

Leveraging Social Media to Promote Public Health Knowledge: Example of Cancer Awareness via Twitter.

Songhua Xu, Christopher Markson, Kaitlin L Costello, Cathleen Y Xing, Kitaw Demissie, Adana Am Llanos

Abstract read
In one paragraph

Article in JMIR public health and surveillance. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 2 pooled it
–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

64 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  15. Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter?Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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4 more citing papers are in PubMed but not listed here.

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.

Songhua Xu *College of Computing SciencesDepartment of Information SystemsNew Jersey Institute of TechnologyNewark, NJUnited States.ORCID 0000-0002-6715-7745
Christopher Markson *College of Computing SciencesDepartment of Information SystemsNew Jersey Institute of TechnologyNewark, NJUnited States.ORCID 0000-0003-2047-1769
Kaitlin L CostelloRutgers School of Communication and InformationDepartment of Library and Information ScienceNew Brunswick, NJUnited States.ORCID 0000-0002-1589-7418
Cathleen Y XingSchool of Public HealthEpidemiologyRutgers UniversityPiscataway, NJUnited States.ORCID 0000-0002-9874-4141
Kitaw DemissieSchool of Public Health and Cancer Institute of New JerseyEpidemiologyRutgers UniversityPiscataway, NJUnited States.ORCID 0000-0002-8777-5583
Adana Am LlanosSchool of Public Health and Cancer Institute of New JerseyEpidemiologyRutgers UniversityPiscataway, NJUnited States.ORCID 0000-0001-9954-9121

Funding

TRANSCRIPTIONAL PROFILINGP30CA072720 · NCI · UNIV OF MED/DENT NJ-R W JOHNSON MED SCH · PI Chang S Chan · 1997 to 2026
$94.5M
A Cyber-Informatics Approach to Studying Migration and Environmental Cancer RiskR01CA170508 · NCI · UT-BATTELLE, LLC-OAK RIDGE NATIONAL LAB · PI TOURASSI, GEORGIA, XU, SONGHUA · 2012 to 2015
$1.6M
NCI NIH HHS P30 CA072720NCI NIH HHS R01 CA170508
6 · The paper itself

Abstract

backgroundAs social media becomes increasingly popular online venues for engaging in communication about public health issues, it is important to understand how users promote knowledge and awareness about specific topics.

objectiveThe aim of this study is to examine the frequency of discussion and differences by race and ethnicity of cancer-related topics among unique users via Twitter.

methodsTweets were collected from April 1, 2014 through January 21, 2015 using the Twitter public streaming Application Programming Interface (API) to collect 1% of public tweets. Twitter users were classified into racial and ethnic groups using a new text mining approach applied to English-only tweets. Each ethnic group was then analyzed for frequency in cancer-related terms within user timelines, investigated for changes over time and across groups, and measured for statistical significance.

resultsObservable usage patterns of the terms "cancer", "breast cancer", "prostate cancer", and "lung cancer" between Caucasian and African American groups were evident across the study period. We observed some variation in the frequency of term usage during months known to be labeled as cancer awareness months, particularly September, October, and November. Interestingly, we found that of the terms studied, "colorectal cancer" received the least Twitter attention.

conclusionsThe findings of the study provide evidence that social media can serve as a very powerful and important tool in implementing and disseminating critical prevention, screening, and treatment messages to the community in real-time. The study also introduced and tested a new methodology of identifying race and ethnicity among users of the social media. Study findings highlight the potential benefits of social media as a tool in reducing racial and ethnic disparities.

Indexed as

awarenessbreast cancercolorectal cancerdisparitieslung cancerprostate cancersocial mediaTwitter

Identifiers

PMID27227152
PMCPMC4869239

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.