Supporting Personalized Health Care With Social Media Analytics: An Application to Hypothyroidism

2022 ◽  
Vol 3 (1) ◽  
pp. 1-28
Author(s):  
Giorgio Grani ◽  
Andrea Lenzi ◽  
Paola Velardi

Social media analytics can considerably contribute to understanding health conditions beyond clinical practice, by capturing patients’ discussions and feelings about their quality of life in relation to disease treatments. In this article, we propose a methodology to support a detailed analysis of the therapeutic experience in patients affected by a specific disease, as it emerges from health forums. As a use case to test the proposed methodology, we analyze the experience of patients affected by hypothyroidism and their reactions to standard therapies. Our approach is based on a data extraction and filtering pipeline, a novel topic detection model named Generative Text Compression with Agglomerative Clustering Summarization ( GTCACS ), and an in-depth data analytic process. We advance the state of the art on automated detection of adverse drug reactions ( ADRs ) since, rather than simply detecting and classifying positive or negative reactions to a therapy, we are capable of providing a fine characterization of patients along different dimensions, such as co-morbidities, symptoms, and emotional states.

2019 ◽  
Author(s):  
Alden Bunyan ◽  
Swamy Venuturupalli ◽  
Katja Reuter

BACKGROUND Lupus is a complex autoimmune disease that is difficult to diagnose and treat. It is estimated that at least 5 million Americans have lupus, with more than 16,000 new cases of lupus being reported annually in the U.S. Social media provides a platform for patients to find rheumatologists, peers, and build awareness of the condition. Researchers suggested that the social network Twitter may serve as a rich avenue for exploring how patients communicate about their health issues. However, there is a lack of research about the characteristics of lupus patients on Twitter and their attitudes toward using Twitter for engaging them with their healthcare. OBJECTIVE This study has two objectives: (1) to conduct a content analysis of Twitter data published by users (in English) in the U.S. between 9/1/2017 and 10/31/2018 to identify patients who publicly discuss their lupus condition and to assess their expressed health themes, and (2) to conduct a cross-sectional survey among these lupus patients on Twitter to study their attitudes toward using Twitter for engaging them with their healthcare. METHODS This is a mixed-methods study that analyzes retrospective Twitter data and conducts a cross-sectional survey among lupus patients on Twitter. We will use Symplur Signals, a healthcare social media analytics platform, to access the Twitter data and analyze user-generated posts that include keywords related to lupus. We will use descriptive statistics to analyze the data and identify the most prevalent topics in the Twitter content among lupus patients. We will further conduct self-report surveys via Twitter by inviting all identified lupus patients who discuss their lupus condition on Twitter. The goal of the survey is to collect data about the characteristics of lupus patients (e.g., gender, race/ethnicity, educational level) and their attitudes toward using Twitter for engaging them with their healthcare. RESULTS This study has been funded by the National Center for Advancing Translational Science (NCATS) through a Clinical and Translational Science Award (CTSA) award. The Institutional Review Board at the University of Southern California (HS-19-00048) approved the study. Data extraction and cleaning are complete. We obtained 47,715 Twitter posts containing terms related to “lupus” from users in the U.S. published in English between 9/1/2017 and 10/31/2018. We will include 40,885 posts in the analysis. Data analysis will be completed by the end of 2019. CONCLUSIONS The data obtained in this pilot study will shed light on whether Twitter provides a promising data source for garnering health-related attitudes among lupus patients. The data will also help to determine whether Twitter might serve as a potential outreach platform for raising awareness of lupus among patients and healthcare providers and implementing related health education interventions. CLINICALTRIAL N/A


2021 ◽  
Vol 40 ◽  
pp. 03003
Author(s):  
Prasad Kulkarni ◽  
Suyash Karwande ◽  
Rhucha Keskar ◽  
Prashant Kale ◽  
Sumitra Iyer

Everyone depends upon various online resources for news in this modern age, where the internet is pervasive. As the use of social media platforms such as Facebook, Twitter, and others has increased, news spreads quickly among millions of users in a short time. The consequences of Fake news are far-reaching, from swaying election outcomes in favor of certain candidates to creating biased opinions. WhatsApp, Instagram, and many other social media platforms are the main source for spreading fake news. This work provides a solution by introducing a fake news detection model using machine learning. This model requires prerequisite data extracted from various news websites. Web scraping technique is used for data extraction which is further used to create datasets. The data is classified into two major categories which are true dataset and false dataset. Classifiers used for the classification of data are Random Forest, Logistic Regression, Decision Tree, KNN and Gradient Booster. Based on the output received the data is classified either as true or false data. Based on that, the user can find out whether the given news is fake or not on the webserver.


2016 ◽  
Vol 7 (4) ◽  
pp. 405-422 ◽  
Author(s):  
Seunghyun Brian Park ◽  
Jichul Jang ◽  
Chihyung Michael Ok

Purpose The purpose of this paper is to use Twitter analysis to explore diner perceptions of four types of Asian restaurants (Chinese, Japanese, Korean and Thai). Design/methodology/approach Using 86,015 tweets referring to Asian restaurants, this research used text mining and sentiment analysis to find meaningful patterns, popular words and emotional states in opinions. Findings Twitter users held mingled perceptions of different types of Asian restaurants. Sentiment analysis and ANOVA showed that the average sentiment scores for Chinese restaurants was significantly lower than the other three Asian restaurants. While most positive tweets referred to food quality, many negative tweets suggested problems associated with service quality or food culture. Research limitations/implications This research provides a methodology that future researchers can use in applying social media analytics to explore major issues and extract sentiment information from text messages. Originality/value Limited research has been conducted applying social media analysis in hospitality research. This study fills a gap by using social media analytics with Twitter data to examine the Twitter users’ thoughts and emotions for four different types of Asian restaurants.


2014 ◽  
Vol 35 (1) ◽  
pp. 7-43 ◽  
Author(s):  
Dick M. Carpenter ◽  
Jenifer Walsh Robertson ◽  
Michele E. Johnson ◽  
Scott Blum

Author(s):  
Admink Admink ◽  
Жанна Шкляренко

Стаття присвячена дослідженню шляхів вивчення перформансу як культурного явища. Зростаюча увага до цього феномену зумовлена відсутністю лінії розмежування його з життям, створенню особливої реальності, спроможністю викликати потужні емоційні стани та взаємоемпатії. Проблематичність у вивченні його полягає у складності архівування, хиткий своєрідний наратив, що вислизає зі сприйняття непідготовленого глядача, міграція з виставкових зал у соціальну сферу, супроводжувана жанровими новоутвореннями. Даним дослідженням зроблено спробу аналізу шляхів пізнання культурного явища перформансу, визначені особливості побутування, виявлено закономірності проявів та варіативність в сучасній культурі. The article is devoted to the study of ways to research performance study as a cultural phenomenon. The growing interest in the phenomenon of performance art is due to the lack of a dividing line with our life, the creation of a special reality, the ability to cause strong emotional states and mutual empathy. The difficulty of study is also in trouble archiving it, shaky kind of narrative which escapes the perception of the unprepared viewer, the migration of the exhibition halls and in the social media sphere, followed by the creation of new genres. This analyzes the ways of understanding the cultural phenomenon of performance art. The features of being are determined, patterns and a variety of its manifestations in modern culture are revealed.


2020 ◽  
Author(s):  
Jay Palmer ◽  
Kyle Revis ◽  
Yves Romain

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