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Social media based digital epidemiology has the potential to support faster response and deeper understanding of public health related threats. This study proposes a new framework to analyze unstructured health related textual data via…

Social and Information Networks · Computer Science 2017-09-26 George Shaw , Amir Karami

Obesity and diabetes epidemics are affecting about a third and tenth of US population, respectively, capturing the attention of the nation and its institutions. Social media provides an open forum for communication between individuals and…

Social and Information Networks · Computer Science 2018-04-10 Yelena Mejova

Food is an integral part of our lives, cultures, and well-being, and is of major interest to public health. The collection of daily nutritional data involves keeping detailed diaries or periodic surveys and is limited in scope and reach.…

Computers and Society · Computer Science 2015-01-27 Sofiane Abbar , Yelena Mejova , Ingmar Weber

Social media are being increasingly used for health promotion, yet the landscape of users, messages and interactions in such fora is poorly understood. Studies of social media and diabetes have focused mostly on patients, or public agencies…

Social media analytics allows us to extract, analyze, and establish semantic from user-generated contents in social media platforms. This study utilized a mixed method including a three-step process of data collection, topic modeling, and…

Applications · Statistics 2018-12-11 George Shaw , Amir Karami

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…

Human-Computer Interaction · Computer Science 2016-02-24 Ingmar Weber , Yelena Mejova

Twitter data has been shown broadly applicable for public health surveillance. Previous public health studies based on Twitter data have largely relied on keyword-matching or topic models for clustering relevant tweets. However, both…

Computation and Language · Computer Science 2019-12-04 Xiaoyi Zhang , Rodoniki Athanasiadou , Narges Razavian

Nowadays social media is a huge platform of data. People usually share their interest, thoughts via discussions, tweets, status. It is not possible to go through all the data manually. We need to mine the data to explore hidden patterns or…

Computation and Language · Computer Science 2020-12-21 Tunazzina Islam

An increasing number of people use wearables and other smart devices to quantify various health conditions, ranging from sleep patterns, to body weight, to heart rates. Of these Quantified Selfs many choose to openly share their data via…

Social and Information Networks · Computer Science 2016-03-01 Yafei Wang , Ingmar Weber , Prasenjit Mitra

With the widespread adoption of social media sites like Twitter and Facebook, there has been a shift in the way information is produced and consumed. Earlier, the only producers of information were traditional news organizations, which…

Social and Information Networks · Computer Science 2017-10-19 Juhi Kulshrestha , Muhammad Bilal Zafar , Lisette Espin-Noboa , Krishna P. Gummadi , Saptarshi Ghosh

A lack of information exists about the health issues of lesbian, gay, bisexual, transgender, and queer (LGBTQ) people who are often excluded from national demographic assessments, health studies, and clinical trials. As a result, medical…

Social and Information Networks · Computer Science 2018-03-28 Frank Webb , Amir Karami , Vanessa Kitzie

Motivations: People are generating an enormous amount of social data to describe their health care experiences, and continuously search information about diseases, symptoms, diagnoses, doctors, treatment options and medicines. The…

Computers and Society · Computer Science 2019-02-19 Andrea Lenzi , Marianna Maranghi , Giovanni Stilo , Paola Velardi

We describe a strategy for the acquisition of training data necessary to build a social-media-driven early detection system for individuals at risk for (preventable) type 2 diabetes mellitus (T2DM). The strategy uses a game-like quiz with…

Computation and Language · Computer Science 2016-03-15 Dane Bell , Daniel Fried , Luwen Huangfu , Mihai Surdeanu , Stephen Kobourov

We present a large-scale analysis of Instagram pictures taken at 164,753 restaurants by millions of users. Motivated by the obesity epidemic in the United States, our aim is three-fold: (i) to assess the relationship between fast food and…

Computers and Society · Computer Science 2015-03-26 Yelena Mejova , Hamed Haddadi , Anastasios Noulas , Ingmar Weber

We propose and develop a Lexicocalorimeter: an online, interactive instrument for measuring the "caloric content" of social media and other large-scale texts. We do so by constructing extensive yet improvable tables of food and activity…

Purpose: Although elevated BMI is a well-known risk factor for type 2 diabetes, the disease's presence in some lean adults and absence in others with obesity suggests that detailed body composition may uncover abdominal phenotypes of type 2…

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…

Computers and Society · Computer Science 2020-10-13 Yelena Mejova , Víctor Suarez-Lledó

Obesity is a major health problem, increasing the risk of various major chronic diseases, such as diabetes, cancer, and stroke. While the role of obesity identified by cross-sectional BMI recordings has been heavily studied, the role of BMI…

Machine Learning · Computer Science 2024-12-03 Md Mozaharul Mottalib , Jessica C Jones-Smith , Bethany Sheridan , Rahmatollah Beheshti

This paper investigates the relationship between social media and eating practices amongst 42 internet users aged 18-26. We conducted an ethnography in the US and India to observe how they navigated eating and health information online. We…

Human-Computer Interaction · Computer Science 2024-03-01 Rachel Xu , Nhu Le , Rebekah Park , Laura Murray

We investigate the predictive power behind the language of food on social media. We collect a corpus of over three million food-related posts from Twitter and demonstrate that many latent population characteristics can be directly predicted…

Computation and Language · Computer Science 2016-11-15 Daniel Fried , Mihai Surdeanu , Stephen Kobourov , Melanie Hingle , Dane Bell
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