Using social media to estimate Zika's impact on tourism: #babymoon, 2014-2017.
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ABSTRACT:
SUBMITTER: Gallivan M
PROVIDER: S-EPMC6383918 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The number of social media users has increased substantially in the past decade, creating an opportunity for health-care professionals and patients to leverage social media for health communication. This study examines the recent use and predictors of social media for health communication in a nationally representative sample of US adults over time. We used 2013, 2014, and 2017 National Cancer Institute's Health Information National Trends Survey to identify respondents' use of social media for sharing health information or exchanging medical information with a health-care professional. We conducted bivariate analysis using the Pearson χ2 test to assess the association of respondents' basic demographic characteristics as well as health status and the use of social media for health communication. We performed multivariable logistic regression models to examine factors associated with the use of social media for health communication. We identified 4242 respondents (weighted sample size: 343 465 241 [2-year pooled sample]) who used social media for sharing health information and 4834 respondents (weighted sample size: 354 419 489 [2-year pooled sample]) who used social media for exchanging medical information. Multivariable analyses indicated the proportion of respondents who used social media for sharing health information has decreased (odds ratio [OR], 0.65; 95% confidence interval [CI], 0.49-0.85, P = .002), while the use of social media for exchanging medical information with a health-care professional has increased (OR, 1.88; 95% CI, 1.09-3.26, P = .025). The younger population had significantly higher odds of using social media for health communication. The study found no racial/ethnic disparities in the use of social media for health communication. Use of social media for sharing health information has declined, while exchanging medical information with health-care professionals has increased. Future research is needed to determine how to engage the population in social media-based health interventions, particularly for older adults.
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Project description:The social impact of research has usually been analysed through the scientific outcomes produced under the auspices of the research. The growth of scholarly content in social media and the use of altmetrics by researchers to track their work facilitate the advancement in evaluating the impact of research. However, there is a gap in the identification of evidence of the social impact in terms of what citizens are sharing on their social media platforms. This article applies a social impact in social media methodology (SISM) to identify quantitative and qualitative evidence of the potential or real social impact of research shared on social media, specifically on Twitter and Facebook. We define the social impact coverage ratio (SICOR) to identify the percentage of tweets and Facebook posts providing information about potential or actual social impact in relation to the total amount of social media data found related to specific research projects. We selected 10 projects in different fields of knowledge to calculate the SICOR, and the results indicate that 0.43% of the tweets and Facebook posts collected provide linkages with information about social impact. However, our analysis indicates that some projects have a high percentage (4.98%) and others have no evidence of social impact shared in social media. Examples of quantitative and qualitative evidence of social impact are provided to illustrate these results. A general finding is that novel evidences of social impact of research can be found in social media, becoming relevant platforms for scientists to spread quantitative and qualitative evidence of social impact in social media to capture the interest of citizens. Thus, social media users are showed to be intermediaries making visible and assessing evidence of social impact.
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Project description:Big data can be used to assess perceptions about public health issues. This study assessed social media data from Twitter to inform communication campaigns to promote HIV testing and reduce discrimination related to HIV/AIDS or towards key populations to the HIV epidemic, and its potential utility to evaluate such campaigns through HIV testing uptake. Tweets from Brazil were collected from January 2014 to March 2015 and filtered by four categories of keywords including discrimination, HIV prevention, HIV testing, and HIV campaigns. In total over 100,000 geo-located tweets were extracted and analyzed. A dynamic online dashboard updated daily allowed mapping trends, anomalies and influencers, and enabled its use for feedback to campaigns, including correcting misconceptions. These results encourage the use of social networking data for improved messaging in campaigns. Clinical HIV test data was collected monthly from the city of Curitiba and compared to the number of tweets mapped to the city showing a moderate positive correlation (r = 0.39). Results are limited due to the availability of the HIV testing data. The potential of social media as a proxy for HIV testing uptake needs further validation, which can only be done with higher frequency and higher spatial granularity of service delivery data, enabling comparisons with the social media data. Such timely information could empower early response immediate media messaging to support programmatic efforts, such as HIV prevention, testing, and treatment scale up.
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Project description:Cryptocurrencies have recently received large media interest. Especially the great fluctuations in price have attracted such attention. Behavioral sciences and related scientific literature provide evidence that there is a close relationship between social media and price fluctuations of cryptocurrencies. This particularly applies to smaller currencies, which can be substantially influenced by references on Twitter. Although these so-called "altcoins" often have smaller trading volumes they sometimes attract large attention on social media. Here, we show that fluctuations in altcoins can be predicted from social media. In order to do this, we collected a dataset containing prices and the social media activity of 181 altcoins in the form of 426,520 tweets over a timeframe of 71 days. The containing public mood was then estimated using sentiment analysis. To predict altcoin returns, we carried out linear regression analyses based on 45 days of data. We showed that short-term returns can be predicted from activity and sentiments on Twitter.
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Project description:Using social media for health promotion is an innovative and emerging approach but remains relatively unexplored in cancer screening. Uptake of colorectal cancer (CRC) screening remains low and standard methods of reaching out are expensive with limited impact. The objective of this study is to conduct a cluster randomized controlled trial (RCT) to test the effectiveness of social media messages for CRC screening on screening intention (primary outcome). The results of this trial will be of interest to Cancer Care Ontario and are likely to be taken up by other screening programs looking for innovative and novel ways to increase screening participation. The study results will be easily translatable identifying the most compelling CRC screening messages while the approach can easily be translated to other cancer disease sites with screening programs.
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