Dataset Information

Evaluating Scholars' Impact and Influence: Cross-sectional Study of the Correlation Between a Novel Social Media-Based Score and an Author-Level Citation Metric.

ABSTRACT:

Background

The development of an author-level complementary metric could play a role in the process of academic promotion through objective evaluation of scholars' influence and impact.

Objective

The objective of this study was to evaluate the correlation between the Healthcare Social Graph (HSG) score, a novel social media influence and impact metric, and the h-index, a traditional author-level metric.

Methods

This was a cross-sectional study of health care stakeholders with a social media presence randomly sampled from the Symplur database in May 2020. We performed stratified random sampling to obtain a representative sample with all strata of HSG scores. We manually queried the h-index in two reference-based databases (Scopus and Google Scholar). Continuous features (HSG score and h-index) from the included profiles were summarized as the median and IQR. We calculated the Spearman correlation coefficients (ρ) to evaluate the correlation between the HSG scores and h-indexes obtained from Google Scholar and Scopus.

Results

A total of 286 (31.2%) of the 917 stakeholders had a Google Scholar h-index available. The median HSG score for these profiles was 61.1 (IQR 48.2), and the median h-index was 14.5 (IQR 26.0). For the 286 subjects with the HSG score and Google Scholar h-index available, the Spearman correlation coefficient ρ was 0.1979 (P<.001), indicating a weak positive correlation between these two metrics. A total of 715 (78%) of 917 stakeholders had a Scopus h-index available. The median HSG score for these profiles was 57.6 (IQR 46.4), and the median h-index was 7 (IQR 16). For the 715 subjects with the HSG score and Scopus h-index available, ρ was 0.2173 (P<.001), also indicating a weak positive correlation.

Conclusions

We found a weak positive correlation between a novel author-level complementary metric and the h-index. More than a chiasm between traditional citation metrics and novel social media-based metrics, our findings point toward a bridge between the two domains.

SUBMITTER: Oliveira J E Silva L

PROVIDER: S-EPMC8204234 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:IntroductionThere is growing interest in whether social media can capture patient-generated information relevant for medicines safety surveillance that cannot be found in traditional sources.ObjectiveThe aim of this study was to evaluate the potential contribution of mining social media networks for medicines safety surveillance using the following associations as case studies: (1) rosiglitazone and cardiovascular events (i.e. stroke and myocardial infarction); and (2) human papilloma virus (HPV) vaccine and infertility.MethodsWe collected publicly accessible, English-language posts on Facebook, Google+, and Twitter until September 2014. Data were queried for co-occurrence of keywords related to the drug/vaccine and event of interest within a post. Messages were analysed with respect to geographical distribution, context, linking to other web content, and author's assertion regarding the supposed association.ResultsA total of 2537 posts related to rosiglitazone/cardiovascular events and 2236 posts related to HPV vaccine/infertility were retrieved, with the majority of posts representing data from Twitter (98 and 85%, respectively) and originating from users in the US. Approximately 21% of rosiglitazone-related posts and 84% of HPV vaccine-related posts referenced other web pages, mostly news items, law firms' websites, or blogs. Assertion analysis predominantly showed affirmation of the association of rosiglitazone/cardiovascular events (72%; n = 1821) and of HPV vaccine/infertility (79%; n = 1758). Only ten posts described personal accounts of rosiglitazone/cardiovascular adverse event experiences, and nine posts described HPV vaccine problems related to infertility.ConclusionsPublicly available data from the considered social media networks were sparse and largely untrackable for the purpose of providing early clues of safety concerns regarding the prespecified case studies. Further research investigating other case studies and exploring other social media platforms are necessary to further characterise the usefulness of social media for safety surveillance.

Project description:IntroductionSocial media listening (SML) is an approach to assess patient experience in different indications. This is the first study to report the results of using SML to understand patients' experiences of living with dry eye disease (DED).MethodsPublicly available, English-language social media content between December 2016 and August 2017 was searched employing pre-defined criteria using Social Studio®, an online aggregator-tool for posts from social media channels. Using natural language processing (NLP), posts were indexed using patient lexicon and disease-related keywords to derive a set of patient posts. NLP was used to identify relevance, followed by further manual evaluation and analysis to generate patient insights.ResultsIn all, 2279 possible patient records were identified following NLP, which were filtered for relevance to disease area by analysts, resulting in a total of 1192 posts which formed the basis of this study. Of these, 77% (n = 915) were from the USA. Symptoms, causes, diagnosis and treatments were the most commonly discussed themes. Most common symptoms mentioned were eye dryness (138/901), pain (114/901) and blurry vision (110/901). Pharmaceutical drugs (prescription and over-the-counter; 55%; 764/1393), followed by medical devices (20%; 280/1393), were mentioned as major options for managing symptoms. Of the pharmaceutical drugs, eye drops (33%; 158/476) and artificial tears (10%; 49/476) were the most common over-the-counter options reported, and Restasis® (22%; 103/476) and Xiidra® (6%; 27/476) were the most common prescription drugs. Patients voiced a significant impact of DED on their daily activities (4%; 9/224), work (23%; 51/224) and driving (12%; 26/224). Lack of DED specialists, standard diagnostic procedures, effective treatment options and need to increase awareness of DED among patients were identified as the key unmet needs.ConclusionsInsights revealed using SML strengthen our understanding about patient experiences and their unmet needs in DED. This study illustrates that an SML approach contributed effectively in generating patient insights, which can be utilised to inform early drug development process, market access strategies and stakeholder discussions.FundingNovartis Pharma AG, Basel, Switzerland. Plain language summary available for this article.