Social media video analysis methodology for sarin exposure.
Ontology highlight
ABSTRACT:
SUBMITTER: Toprak S
PROVIDER: S-EPMC9246001 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:PURPOSE:Infertile couples increasingly turn to the internet for medical guidance. The aims of this study were: (1) to identify popular male infertility content on social media, and (2) to assess the accuracy and quality of this content. We hypothesized that inaccurate/misleading information proliferates online. MATERIALS AND METHODS:We used the analytics module BuzzSumo to identify article links that were most shared on Facebook, Pinterest, Reddit, and Twitter related to male infertility during September 2018 to August 2019. We excluded articles with <100 engagements, defined as "likes," "comments," and "shares." Two researchers graded content as accurate, misleading, or inaccurate by comparing content to references cited and contemporary research. Inter-rater reliability was determined with Cohen's κ. Binary logistic regression was performed to compare user engagement with accurate versus inaccurate/misleading articles. RESULTS:Fifty-two unique article links were identified, with 421,004 total engagements. Thirty-four articles referenced 15 scientific studies; no reference was available for 18 links. Fifty-six percent of articles were accurate and 44% misleading/inaccurate (κ=0.743). No significant difference was found in total engagement between accurate vs. misleading/inaccurate links (p=0.805). Twenty-four percent of engagements referenced studies using non-human models, and 26% of studies had sample sizes <100. CONCLUSIONS:Social media platforms foster engagement with male infertility information. However, sensationalism predominates, as patients are highly likely to encounter misleading/inaccurate information, articles that overstate implications of animal research, and conclusions made based on limited sample sizes. Urologists should consider adding social media to their armamentarium to stave off misinformation and engage proactively with patients.
| S-EPMC7502321 | biostudies-literature
Project description:Today, a considerable proportion of the public political discourse on nationwide elections proceeds in Online Social Networks. Through analyzing this content, we can discover the major themes that prevailed during the discussion, investigate the temporal variation of positive and negative sentiment and examine the semantic proximity of these themes. According to existing studies, the results of similar tasks are heavily dependent on the quality and completeness of dictionaries for linguistic preprocessing, entity discovery and sentiment analysis. Additionally, noise reduction is achieved with methods for sarcasm detection and correction. Here we report on the application of these methods on the complete corpus of tweets regarding two local electoral events of worldwide impact: the Greek referendum of 2015 and the subsequent legislative elections. To this end, we compiled novel dictionaries for sentiment and entity detection for the Greek language tailored to these events. We subsequently performed volume analysis, sentiment analysis, sarcasm correction and topic modeling. Results showed that there was a strong anti-austerity sentiment accompanied with a critical view on European and Greek political actions.
| S-EPMC5663401 | biostudies-other
Project description:Deep learning has become a key tool for the automated monitoring of animal populations with video surveys. However, obtaining large numbers of images to train such models is a major challenge for rare and elusive species because field video surveys provide few sightings. We designed a method that takes advantage of videos accumulated on social media for training deep-learning models to detect rare megafauna species in the field. We trained convolutional neural networks (CNNs) with social media images and tested them on images collected from field surveys. We applied our method to aerial video surveys of dugongs (Dugong dugon) in New Caledonia (southwestern Pacific). CNNs trained with 1303 social media images yielded 25% false positives and 38% false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) in the training data set resulted in a nearly 50% decrease in false negatives. Our results highlight how and the extent to which images collected on social media can offer a solid basis for training deep-learning models for rare megafauna detection and that the incorporation of a few images from the study site further boosts detection accuracy. Our method provides a new generation of deep-learning models that can be used to rapidly and accurately process field video surveys for the monitoring of rare megafauna.
| S-EPMC9291111 | biostudies-literature
Project description:There is mounting concern that social media sites contribute to political polarization by creating "echo chambers" that insulate people from opposing views about current events. We surveyed a large sample of Democrats and Republicans who visit Twitter at least three times each week about a range of social policy issues. One week later, we randomly assigned respondents to a treatment condition in which they were offered financial incentives to follow a Twitter bot for 1 month that exposed them to messages from those with opposing political ideologies (e.g., elected officials, opinion leaders, media organizations, and nonprofit groups). Respondents were resurveyed at the end of the month to measure the effect of this treatment, and at regular intervals throughout the study period to monitor treatment compliance. We find that Republicans who followed a liberal Twitter bot became substantially more conservative posttreatment. Democrats exhibited slight increases in liberal attitudes after following a conservative Twitter bot, although these effects are not statistically significant. Notwithstanding important limitations of our study, these findings have significant implications for the interdisciplinary literature on political polarization and the emerging field of computational social science.
| S-EPMC6140520 | biostudies-other
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.
| 2332186 | ecrin-mdr-crc
Project description:Organophosphorus nerve agents irreversibly inhibit acetylcholinesterase, causing a toxic buildup of acetylcholine at muscarinic and nicotinic receptors. Current medical countermeasures to nerve agent intoxication increase survival if administered within a short period of time following exposure but may not fully prevent neurological damage. Therefore, there is a need to discover drug treatments that are effective when administered after the onset of seizures and secondary responses that lead to brain injury. Methods To determine potential therapeutic targets for such treatments, we analyzed gene expression changes in the rat piriform cortex following sarin (O-isopropyl methylphosphonofluoridate) exposure. Male Sprague-Dawley rats were challenged with 1.0 x LD50 sarin and subsequently treated with atropine sulfate, 2-pyridine aldoxime methylchloride (2-PAM), and the anticonvulsant diazepam. Control animals received an equivalent volume of vehicle and drug treatments. The piriform cortex, a brain region particularly sensitive to neural damage from sarin-induced seizures, was extracted at 0.25, 1, 3, 6, and 24 h after seizure onset, and total RNA was processed for microarray analysis. Principal component analysis identified sarin-induced seizure occurrence and time point following seizure onset as major sources of variability within the dataset. Based on these variables, the dataset was filtered and analysis of variance was used to determine genes significantly changed in seizing animals at each time point. The calculated p-value and geometric fold change for each probeset identifier were subsequently used for gene ontology analysis to identify canonical pathways, biological functions, and networks of genes significantly affected by sarin-induced seizure over the 24-h time course. Results A multitude of biological functions and pathways were identified as being significantly altered following sarin-induced seizure. Inflammatory response and signaling pathways associated with inflammation were among the most significantly altered across the five time points examined. Conclusions This analysis of gene expression changes in the rat brain following sarin-induced seizure and the molecular pathways involved in sarin-induced neurodegeneration will allow a better identification of potential therapeutic targets for the development of effective neuroprotectants to treat nerve agent exposure.
2011-12-31 | GSE28435 | GEO
Project description:ObjectivesTo explore the nature of images tagged as self-harm on popular social media sites and what this might tell us about how these sites are used.DesignA visual content and thematic analysis of a sample of 602 images captured from Twitter, Instagram and Tumblr.ResultsOver half the images tagged as self-harm had no explicit representation of self-harm. Where there was explicit representation, self-injury was the most common; none of these portrayed images of graphic or shocking self-injury. None of the images we captured specifically encouraged self-harm or suicide and there was no image that could be construed as sensationalising self-harm.Four themes were found across the images: communicating distress, addiction and recovery, gender and the female body, identity and belonging.ConclusionsFindings suggest that clinicians should not be overly anxious about what is being posted on social media. Although we found a very few posts suggesting self-injury was attractive, there were no posts that could be viewed as actively encouraging others to self-harm. Rather, the sites were being used to express difficult emotions in a variety of creative ways, offering inspiration to others through the form of texts or shared messages about recovery.
| S-EPMC6367987 | biostudies-literature
Project description:Huge citizens expose to social media during a novel coronavirus disease (COVID-19) outbroke in Wuhan, China. We assess the prevalence of mental health problems and examine their association with social media exposure. A cross-sectional study among Chinese citizens aged≥18 years old was conducted during Jan 31 to Feb 2, 2020. Online survey was used to do rapid assessment. Total of 4872 participants from 31 provinces and autonomous regions were involved in the current study. Besides demographics and social media exposure (SME), depression was assessed by The Chinese version of WHO-Five Well-Being Index (WHO-5) and anxiety was assessed by Chinese version of generalized anxiety disorder scale (GAD-7). multivariable logistic regressions were used to identify associations between social media exposure with mental health problems after controlling for covariates. The prevalence of depression, anxiety and combination of depression and anxiety (CDA) was 48.3% (95%CI: 46.9%-49.7%), 22.6% (95%CI: 21.4%-23.8%) and 19.4% (95%CI: 18.3%-20.6%) during COVID-19 outbroke in Wuhan, China. More than 80% (95%CI:80.9%-83.1%) of participants reported frequently exposed to social media. After controlling for covariates, frequently SME was positively associated with high odds of anxiety (OR = 1.72, 95%CI: 1.31-2.26) and CDA (OR = 1.91, 95%CI: 1.52-2.41) compared with less SME. Our findings show there are high prevalence of mental health problems, which positively associated with frequently SME during the COVID-19 outbreak. These findings implicated the government need pay more attention to mental health problems, especially depression and anxiety among general population and combating with "infodemic" while combating during public health emergency.
| S-EPMC7162477 | biostudies-literature
Project description:BackgroundOrganophosphorus nerve agents irreversibly inhibit acetylcholinesterase, causing a toxic buildup of acetylcholine at muscarinic and nicotinic receptors. Current medical countermeasures to nerve agent intoxication increase survival if administered within a short period of time following exposure but may not fully prevent neurological damage. Therefore, there is a need to discover drug treatments that are effective when administered after the onset of seizures and secondary responses that lead to brain injury.MethodsTo determine potential therapeutic targets for such treatments, we analyzed gene expression changes in the rat piriform cortex following sarin (O-isopropyl methylphosphonofluoridate)-induced seizure. Male Sprague-Dawley rats were challenged with 1 × LD50 sarin and subsequently treated with atropine sulfate, 2-pyridine aldoxime methylchloride (2-PAM), and the anticonvulsant diazepam. Control animals received an equivalent volume of vehicle and drug treatments. The piriform cortex, a brain region particularly sensitive to neural damage from sarin-induced seizures, was extracted at 0.25, 1, 3, 6, and 24 h after seizure onset, and total RNA was processed for microarray analysis. Principal component analysis identified sarin-induced seizure occurrence and time point following seizure onset as major sources of variability within the dataset. Based on these variables, the dataset was filtered and analysis of variance was used to determine genes significantly changed in seizing animals at each time point. The calculated p-value and geometric fold change for each probeset identifier were subsequently used for gene ontology analysis to identify canonical pathways, biological functions, and networks of genes significantly affected by sarin-induced seizure over the 24-h time course.ResultsA multitude of biological functions and pathways were identified as being significantly altered following sarin-induced seizure. Inflammatory response and signaling pathways associated with inflammation were among the most significantly altered across the five time points examined.ConclusionsThis analysis of gene expression changes in the rat brain following sarin-induced seizure and the molecular pathways involved in sarin-induced neurodegeneration will facilitate the identification of potential therapeutic targets for the development of effective neuroprotectants to treat nerve agent exposure.
| S-EPMC3199787 | biostudies-literature
Project description:Depression is a major public health concern in the U.S. and globally. While successful early identification and treatment can lead to many positive health and behavioral outcomes, depression, remains undiagnosed, untreated or undertreated due to several reasons, including denial of the illness as well as cultural and social stigma. With the ubiquity of social media platforms, millions of people are now sharing their online persona by expressing their thoughts, moods, emotions, and even their daily struggles with mental health on social media. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of depressive symptoms from tweets obtained, unobtrusively. Particularly, we examine and exploit multimodal big (social) data to discern depressive behaviors using a wide variety of features including individual-level demographics. By developing a multimodal framework and employing statistical techniques to fuse heterogeneous sets of features obtained through the processing of visual, textual, and user interaction data, we significantly enhance the current state-of-the-art approaches for identifying depressed individuals on Twitter (improving the average F1-Score by 5 percent) as well as facilitate demographic inferences from social media. Besides providing insights into the relationship between demographics and mental health, our research assists in the design of a new breed of demographic-aware health interventions.
| S-EPMC7147779 | biostudies-literature