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The COVID-19 pandemic has severely affected people's daily lives and caused tremendous economic loss worldwide. However, its influence on people's mental health conditions has not received as much attention. To study this subject, we choose…
Social networking sites such as Twitter have provided a great opportunity for organizations such as public libraries to disseminate information for public relations purposes. However, there is a need to analyze vast amounts of social media…
The debates on minority issues are often dominated by or held among the concerned minority: gender equality debates have often failed to engage men, while those about race fail to effectively engage the dominant group. To test this…
This study explores the dynamic relationship between online discourse, as observed in tweets, and physical hate crimes, focusing on marginalized groups. Leveraging natural language processing techniques, including keyword extraction and…
The COVID-19 pandemic has disproportionately impacted the lives of minorities, such as members of the LGBTQ community (lesbian, gay, bisexual, transgender, and queer) due to pre-existing social disadvantages and health disparities. Although…
The global increase in mental illness requires innovative detection methods for early intervention. Social media provides a valuable platform to identify mental illness through user-generated content. This systematic review examines machine…
The combination of clinical and personal health and wellbeing data can tell us much about our behaviors, risks and overall status. The way this data is visualized may affect our understanding of our own health. To study this effect, we…
Online dating and hookup platforms have fundamentally changed people's day-to-day practices of sex and love-but exist in tension with older social and medicolegal norms. This is particularly the case for people with HIV, who are frequently…
Researchers use Twitter and sentiment analysis to predict Cardiovascular Disease (CVD) risk. We developed a new dictionary of CVD-related keywords by analyzing emotions expressed in tweets. Tweets from eighteen US states, including the…
Compared to physical health, population mental health measurement in the U.S. is very coarse-grained. Currently, in the largest population surveys, such as those carried out by the Centers for Disease Control or Gallup, mental health is…
In the light of increasing clues on social media impact on self-harm and suicide risks, there is still no evidence on who are and how factually engaged in suicide-related online behaviors. This study reports new findings of high-performance…
The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share…
Social networks are rich source of data to analyze user habits in all aspects of life. User's behavior is decisive component of a health system in various countries. Promoting good behavior can improve the public health significantly. In…
Textual data from social platforms captures various aspects of mental health through discussions around and across issues, while users reach out for help and others sympathize and offer support. We propose a comprehensive framework that…
The unprecedented growth of Internet users in recent years has resulted in an abundance of unstructured information in the form of social media text. A large percentage of this population is actively engaged in health social networks to…
We present our experience with a data science problem in Public Health, where researchers use social media (Twitter) to determine whether the public shows awareness of HIV prevention measures offered by Public Health campaigns. To help the…
Social media is interactive, and interaction brings misinformation. With the growing amount of user-generated data, fake news on online platforms has become much frequent since the arrival of social networks. Now and then, an event occurs…
Exploiting the large amount of available data for addressing relevant social problems has been one of the key challenges in data mining. Such efforts have been recently named "data science for social good" and attracted the attention of…
The exoskeleton technology has been rapidly advancing in the recent past due to its multitude of applications and diverse use-cases in assisted living, military, healthcare, firefighting, and industry 4.0. The exoskeleton market is…
Social media platforms have been exploited to disseminate misinformation in recent years. The widespread online misinformation has been shown to affect users' beliefs and is connected to social impact such as polarization. In this work, we…