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Dietary intake data are routinely drawn upon to explore diet-health relationships. However, these data are often subject to measurement error, distorting the true relationships. Beyond measurement error, there are likely complex synergistic…
Mental disorders such as depression and suicidal ideation are hazardous, affecting more than 300 million people over the world. However, on social media, mental disorder symptoms can be observed, and automated approaches are increasingly…
Mental illness affects a significant portion of the worldwide population. Online mental health forums can provide a supportive environment for those afflicted and also generate a large amount of data which can be mined to predict mental…
Due to the worldwide accessibility to the Internet along with the continuous advances in mobile technologies, physical and digital worlds have become completely blended, and the proliferation of social media platforms has taken a leading…
Background: The COVID-19 outbreak has left many people isolated within their homes; these people are turning to social media for news and social connection, which leaves them vulnerable to believing and sharing misinformation.…
Depression detection from user-generated content on the internet has been a long-lasting topic of interest in the research community, providing valuable screening tools for psychologists. The ubiquitous use of social media platforms lays…
Food communities on online platforms enjoy great popularity among social media users. Due to the far-reaching consequences of food-related content on user eating behavior, recent research has studied the factors that drive user online…
To use social media for health-related analysis, one key step is the detection of health-related labels for users. But unlike transient conditions like flu, social media users are less vocal about chronic conditions such as obesity, as…
While outdoor advertisements are common features within towns and cities, they may reinforce social inequalities in health. Vulnerable populations in deprived areas may have greater exposure to fast food, gambling and alcohol advertisements…
National Eating Disorders Association conducts a NEDAwareness week every year, during which it publishes content on social media and news aimed to raise awareness of eating disorders. Measuring the impact of these actions is vital for…
Users of social platforms often perceive these sites as supportive spaces to post about their mental health issues. Those conversations contain important traces about individuals' health risks. Recently, researchers have exploited this…
Amid the pandemic COVID-19, the world is facing unprecedented infodemic with the proliferation of both fake and real information. Considering the problematic consequences that the COVID-19 fake-news have brought, the scientific community…
Crop diseases are a major threat to food security, but their rapid identification remains difficult in many parts of the world due to the lack of the necessary infrastructure. The combination of increasing global smartphone penetration and…
Food image analysis is the groundwork for image-based dietary assessment, which is the process of monitoring what kinds of food and how much energy is consumed using captured food or eating scene images. Existing deep learning-based methods…
Eating disorders are complex mental health conditions that affect millions of people around the world. Effective interventions on social media platforms are crucial, yet testing strategies in situ can be risky. We present a novel LLM-driven…
Social Media websites have disseminated digital devices to the public, making information sharing easier and faster. Exchanging textual data is the most popular communication among social media users. It has become a necessity for…
A drastic rise in potentially life-threatening misinformation has been a by-product of the COVID-19 pandemic. Computational support to identify false information within the massive body of data on the topic is crucial to prevent harm.…
For preventing youth suicide, social media platforms have received much attention from researchers. A few researches apply machine learning, or deep learning-based text classification approaches to classify social media posts containing…
The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social media, such as Twitter, Facebook, and WeChat.Unlike the previous studies which focused on how to detect the misinformation or fake…
Considering the raising socio-economic burden of autism spectrum disorder (ASD), timely and evidence-driven public policy decision making and communication of the latest guidelines pertaining to the treatment and management of the disorder…