Recovery Amid Pro-Anorexia: Analysis of Recovery in Social Media.
Ontology highlight
ABSTRACT:
SUBMITTER: Chancellor S
PROVIDER: S-EPMC5565731 | biostudies-other | 2016 May
REPOSITORIES: biostudies-other
Similar Datasets
Project description:Access to information via social media is one of the biggest differentiators of public health crises today. During the early stages of the Covid-19 outbreak in January 2020, we conducted an experiment in Wuhan, China to assess the impact of viral social media content on pro-social and trust behaviours and preferences towards risk taking with known and unknown probabilities. Prior to the experiment, participants viewed one of two videos that had been widely and anonymously shared on Chinese social media: a central government leader visiting a local hospital and supermarket, or health care volunteers transiting to Wuhan. In a control condition, participants watched a Neutral video, unrelated to the crisis. Viewing one of the leadership or volunteer videos leads to higher levels of pro-sociality and lesser willingness to take risks in an ambiguous situation relative to the control condition. The leadership video, however, induces lower levels of trust. We provide evidence from two post-experiment surveys that the video’s impact on pro-sociality is modulated by influencing the viewer’s affective emotional state. Supplementary Information The online version contains supplementary material available at 10.1007/s40881-021-00104-w.
| S-EPMC8409073 | 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:BackgroundSocial media sites are becoming an increasingly important source of information about mental health disorders. Among them, eating disorders are complex psychological problems that involve unhealthy eating habits. In particular, there is evidence showing that signs and symptoms of anorexia nervosa can be traced in social media platforms. Knowing that input data biases tend to be amplified by artificial intelligence algorithms and, in particular, machine learning, these methods should be revised to mitigate biased discrimination in such important domains.ObjectiveThe main goal of this study was to detect and analyze the performance disparities across genders in algorithms trained for the detection of anorexia nervosa on social media posts. We used a collection of automated predictors trained on a data set in Spanish containing cases of 177 users that showed signs of anorexia (471,262 tweets) and 326 control cases (910,967 tweets).MethodsWe first inspected the predictive performance differences between the algorithms for male and female users. Once biases were detected, we applied a feature-level bias characterization to evaluate the source of such biases and performed a comparative analysis of such features and those that are relevant for clinicians. Finally, we showcased different bias mitigation strategies to develop fairer automated classifiers, particularly for risk assessment in sensitive domains.ResultsOur results revealed concerning predictive performance differences, with substantially higher false negative rates (FNRs) for female samples (FNR=0.082) compared with male samples (FNR=0.005). The findings show that biological processes and suicide risk factors were relevant for classifying positive male cases, whereas age, emotions, and personal concerns were more relevant for female cases. We also proposed techniques for bias mitigation, and we could see that, even though disparities can be mitigated, they cannot be eliminated.ConclusionsWe concluded that more attention should be paid to the assessment of biases in automated methods dedicated to the detection of mental health issues. This is particularly relevant before the deployment of systems that are thought to assist clinicians, especially considering that the outputs of such systems can have an impact on the diagnosis of people at risk.
| S-EPMC10288345 | biostudies-literature
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:The challenge of nowcasting the effect of natural hazard events (e.g., earthquakes, floods, hurricanes) on assets, people and society is of primary importance for assessing the ability of such systems to recover from extreme events. Traditional recovery estimates, such as surveys and interviews, are usually costly, time consuming and do not scale. Here we present a methodology to indirectly estimate the post-emergency recovery status (downtime) of small businesses in urban areas looking at their online posting activity on social media. Analysing the time series of posts before and after an event, we quantify the downtime of small businesses for three natural hazard events occurred in Nepal, Puerto Rico and Mexico. A convenient and reliable method for nowcasting the post-emergency recovery status of economic activities could help local governments and decision makers to better target their interventions and distribute the available resources more effectively.
| S-EPMC7118130 | biostudies-literature
Project description:Despite heavy Internet regulations, government critics and political satires are not completely absent in the cyberspace of most authoritarian regimes. Some argue that these regimes deliberately tolerate somewhat critical online comments as a way to monitor mass sentiments. To counterbalance critics' influences, they often mobilize and amplify pro-regime voices. We empirically examine whether such pro-regime voices succeed in changing public opinions in favor of the authorities. Based on two online surveys and an embedded survey experiment that we implemented in China, we find that when given a choice, our Chinese respondents self-select to expose themselves to comments that deviate from the official discourses. In addition, exposure to diverse comments undermines individuals' policy support. The findings call into question the effectiveness of the "soft propaganda" that authoritarian regimes orchestrate in cyberspace.Supplementary informationThe online version contains supplementary material available at 10.1007/s11109-021-09744-4.
| S-EPMC8417687 | biostudies-literature
Project description:BackgroundCaregivers often use the internet to access information related to stroke care to improve preparedness, thereby reducing uncertainty and enhancing the quality of care.MethodSocial media communities used by caregivers of people affected by stroke were identified using popular keywords searched for using Google. Communities were filtered based on their ability to provide support to caregivers. Data from the included communities were extracted and analysed to determine the content and level of interaction.ResultsThere was a significant rise in the use of social media by caregivers of people affected by stroke. The most popular social media communities were charitable and governmental organizations with the highest user interaction-this was for topics related to stroke prevention, signs and symptoms, and caregiver self-care delivered through video-based resources.ConclusionFindings show the ability of social media to support stroke caregiver needs and practices that should be considered to increase their interaction and support.
| S-EPMC8791510 | biostudies-literature
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: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
Project description:The overall aim with this study is to get a deeper understanding of the potential benefits with a health platform for patients diagnosed with colorectal cancer.
| 2283132 | ecrin-mdr-crc