Amit Sheth

Amit Sheth
University of South Carolina | USC

Doctor of Philosophy

About

1,019
Publications
278,718
Reads
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39,593
Citations
Citations since 2016
152 Research Items
12534 Citations
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201620172018201920202021202205001,0001,5002,000
Additional affiliations
January 2007 - present
Wright State University
Position
  • LexisNexis Ohio Eminent Scholar
January 2007 - present
Wright State University
Position
  • Managing Director
Description
  • http://knoesis.org/amit
January 2007 - November 2015
Wright State University
Position
  • LexisNexis Ohio Eminent Scholar

Publications

Publications (1,019)
Preprint
Full-text available
The convenience of social media has also enabled its misuse, potentially resulting in toxic behavior. Nearly 66% of internet users have observed online harassment, and 41% claim personal experience, with 18% facing severe forms of online harassment. This toxic communication has a significant impact on the well-being of young individuals, affecting...
Preprint
Full-text available
Epidemiological models are the mathematical models that capture the dynamics of epidemics. The spread of the virus has two routes - exogenous and endogenous. The exogenous spread is from outside the population under study, and endogenous spread is within the population under study. Although some of the models consider the exogenous source of infect...
Article
Full-text available
Background The United States is facing a "triple wave" epidemic fueled by novel synthetic opioids. Cryptomarkets, anonymous marketplaces located on the deep web, play an increasingly important role in the distribution of illicit substances. This article presents the data collected and processed by the eDarkTrends platform concerning the availabilit...
Article
An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Preprint
BACKGROUND In Clinical Diagnostic Interviews, mental health professionals (MHPs) implement a care practice that involves open questions (e.g., What do you want from your life? What have you tried before to bring change in your life?) and listening to a patient. Further, MHPs need to gather critical insights from an interview with a patient concerni...
Preprint
Full-text available
Intelligent systems designed using machine learning algorithms require a large number of labeled data. Background knowledge provides complementary, real world factual information that can augment the limited labeled data to train a machine learning algorithm. The term Knowledge Graph (KG) is in vogue as for many practical applications, it is conven...
Article
Full-text available
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 ubiquit...
Article
Full-text available
THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. The presence of a significant amount of harassment in user-generated content and its negative impact calls for robust automatic detection approaches. This requires the identification of different types of harassment. Earlier work has classified har...
Preprint
Full-text available
Learning the underlying patterns in the data goes beyond instance-based generalization to some external knowledge represented in structured graphs or networks. Deep Learning (DL) has shown significant advances in probabilistically learning latent patterns in the data using a multi-layered network of computational nodes (i.e. neurons/hidden units)....
Preprint
Full-text available
Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. However, for dynamic real-world applications such as social networks, recommender systems, computational biology, relational knowledge representation has emerged as a challenging research problem where there is a need to...
Article
Full-text available
Intelligent systems designed using machine learning algorithms require a large number of labeled data. Background knowledge provides complementary, real-world factual information that can augment the limited labeled data to train a machine learning algorithm. The term Knowledge Graph (KG) is in vogue as for many practical applications, it is conven...
Preprint
Full-text available
The autonomous driving (AD) industry is exploring the use of knowledge graphs (KGs) to manage the vast amount of heterogeneous data generated from vehicular sensors. The various types of equipped sensors include video, LIDAR and RADAR. Scene understanding is an important topic in AD which requires consideration of various aspects of a scene, such a...
Article
Over the past several decades, the incidence of early-onset colorectal cancer (EOCRC; in patients <50 years old) has increased at an alarming rate. Although robust and scientifically rigorous epidemiological studies have sifted out environmental elements linked to EOCRC, our knowledge of the causes and mechanisms of this disease is far from complet...
Article
Full-text available
Nowadays, healthy lifestyle, fitness, and diet habits have become central applications in our daily life. Positive psychology such as well-being and happiness is the ultimate dream of everyday people's feelings (even without being aware of it). Wearable devices are being increasingly employed to support well-being and fitness. Those devices produce...
Article
Full-text available
Terror attacks have been linked in part to online extremist content. Online conversations are cloaked in religious ambiguity, with deceptive intentions, often twisted from mainstream meaning to serve a malevolent ideology. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peacefu...
Article
Background: Establishing trends of drug overdoses requires the identification of individual drugs in death certificates, not supported by coding with the International Classification of Diseases. However, identifying drug mentions from the literal portion of death certificates remains challenging due to the variability of drug names. Objectives:...
Preprint
Full-text available
Terror attacks have been linked in part to online extremist content. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremi...
Conference Paper
Full-text available
In this paper, we focus on the collection and analysis of relevant Twitter data on a state-by-state basis for (i) measuring public opinion on marijuana legalization by mining sentiment in Twitter data and (ii) determining the usage trends for six distinct types of marijuana. We overcome the challenges posed by the informal and ungrammatical nature...
Conference Paper
Natural disasters such as floods, forest fires, and hurricanes can cause catastrophic damage to human life and infrastructure. We focus on response to hurricanes caused by both river water flooding and storm surge. Using models for storm surge simulation and flood extent prediction, we generate forecasts about areas likely to be highly affected by...
Article
Full-text available
Presents case studies in the healthcare industry that focus on the use of Chatbots to improve patient monitoring and medical services. The transition towards personalized health management requires public awareness about management strategies of self-monitoring, self-appraisal, and self-management, eventually paving a way to more timely interventio...
Article
Full-text available
Knowledge Graphs (KGs) represent real-world noisy raw information in a structured form, capturing relationships between entities. However, for dynamic real-world applications such as social networks, recommender systems, computational biology, relational knowledge representation has emerged as a challenging research problem where there is a need to...
Article
Full-text available
Background: Asthma is a chronic pulmonary disease with multiple triggers. It can be managed by strict adherence to an asthma care plan and by avoiding these triggers. Clinicians cannot continuously monitor their patients' environment and their adherence to an asthma care plan, which poses a significant challenge for asthma management. Objective:...
Conference Paper
Full-text available
There is a well-recognized need for a shift to proactive asthma care given the impact asthma has on overall healthcare costs. The demand for continuous monitoring of patient's adherence to the medication care plan, assessment of environmental triggers, and management of asthma can be challenging in traditional clinical settings and taxing on clinic...
Conference Paper
Full-text available
Mental health illness such as depression is a significant risk factor for suicide ideation, behaviors, and attempts. A report by Substance Abuse and Mental Health Services Administration (SAMHSA) shows that 80% of the patients suffering from Borderline Personality Disorder (BPD) have suicidal behavior, 5-10% of whom commit suicide. While multiple i...
Article
Social determinants of health (SDOH) are known to influence mental health outcomes, which are independent risk factors for poor health status and physical illness. Currently, however, existing SDOH data collection methods are ad hoc and inadequate, and SDOH data are not systematically included in clinical research or used to inform patient care. So...
Preprint
Most NLP and Computer Vision tasks are limited to scarcity of labelled data. In social media emotion classification and other related tasks, hashtags have been used as indicators to label data. With the rapid increase in emoji usage of social media, emojis are used as an additional feature for major social NLP tasks. However, this is less explored...
Article
Full-text available
As America’s opioid crisis has become an “epidemic of epidemics,” Ohio has been identified as one of the high burden states regarding fentanyl-related overdose mortality. This study aims to examine changes in the availability of fentanyl, fentanyl analogs, and other non-pharmaceutical opioids on cryptomarkets and assess relationship with the trends...
Article
During this decade, artificial intelligence (AI) has established itself as a phenomenon in our daily life. It is one of the most important investment priorities and has been at the forefront of recent technological disruptions. New boundaries are being pushed daily, ranging from winning against the world's best Go player to selfdriving and autopilo...
Preprint
With ubiquity of social media platforms, millions of people are sharing their online persona by expressing their thoughts, moods, emotions, feelings, and even their daily struggles with mental health issues voluntarily and publicly on social media. Unlike the most existing efforts which study depression by analyzing textual content, we examine and...
Preprint
Full-text available
Metrics for Evaluating Quality of Embeddings for Ontological Concepts
Conference Paper
Full-text available
Recent studies show that by combining network topology and node attributes, we can better understand community structures in complex networks. However, existing algorithms do not explore "contextually" similar node attribute values, and therefore may miss communities defined with abstract concepts. We propose a community detection and characterizat...
Chapter
Social media provides a virtual platform for users to share and discuss their daily life, activities, opinions, health, feelings, etc. Such personal accounts readily generate Big Data marked by velocity, volume, value, variety, and veracity challenges. This type of Big Data analytics already supports useful investigations ranging from research into...
Chapter
Full-text available
Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive experimentation and analysis for insights have been carried out using Twitter data in various domains such as healthcare...
Article
Full-text available
The Workshop Program of the Association for the Advancement of Artificial Intelligence’s 12th International Conference on Web and Social Media (AAAI-18) was held at Stanford University, Stanford, California USA, on Monday, June 25, 2018. There were fourteen workshops in the program: Algorithmic Personalization and News: Risks and Opportunities; Bey...
Preprint
Full-text available
BACKGROUND Asthma is a chronic pulmonary disease with multiple triggers causing the symptoms. It can be managed by strict adherence to the asthma care plan and by avoiding triggers. The clinician cannot continuously monitor the patient’s environment and their compliance towards the asthma care plan, thus posing a significant challenge for asthma ma...
Conference Paper
Full-text available
We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with...
Preprint
Full-text available
The presence of a significant amount of harassment in user-generated content and its negative impact calls for robust automatic detection approaches. This requires that we can identify different forms or types of harassment. Earlier work has classified harassing language in terms of hurtfulness, abusiveness, sentiment, and profanity. However, to id...
Article
Full-text available
Introduction Childhood Asthma is a significant public health concern worldwide. Effective management of childhood asthma requires close monitoring of disease triggers, medication compliance and symptom control. The recent growth of the Internet of Things (IoT) based devices has enabled continuous monitoring of patients. kHealth-Asthma is a knowledg...
Preprint
Full-text available
In the domain of emergency management during hazard crises, having sufficient situational awareness information is critical. It requires capturing and integrating information from sources such as satellite images, local sensors and social media content generated by local people. A bold obstacle to capturing, representing and integrating such hetero...
Conference Paper
Full-text available
Social media platforms are increasingly being used to share and seek advice on mental health issues. In particular, Reddit users freely discuss such issues on various subreddits, whose structure and content can be leveraged to formally interpret and relate subreddits and their posts in terms of mental health diagnostic categories. There is prior re...
Article
Full-text available
Objective To characterize nonpsychiatric prescription patterns of antidepressants according to drug labels and evidence assessments (on-label, evidence-based, and off-label) using structured outpatient electronic health record (EHR) data. Methods A retrospective analysis was conducted using deidentified EHR data from an outpatient practice at a Ne...
Conference Paper
Full-text available
Extracting location names from informal and unstructured social media data requires the identification of referent boundaries and partitioning compound names. Variability, particularly systematic variability in location names (Carroll, 1983), challenges the identification task. Some of this variability can be anticipated as operations within a stat...
Preprint
Full-text available
This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of s...
Preprint
BACKGROUND Asthma is a multifactorial chronic disease that severely affects a child’s daily activity and quality of life. Pediatric asthma causes reduced playtime, disturbed sleep, and missed school days -- impacting a child’s long-term academic and physical growth. In this paper, we discuss the use of the kHealth system for continuous and comprehe...
Conference Paper
Full-text available
This work addresses challenges arising from extracting entities from textual data, including the high cost of data annotation, model accuracy, selecting appropriate evaluation criteria, and the overall quality of annotation. We present a framework that integrates Entity Set Expansion (ESE) and Active Learning (AL) to reduce the annotation cost of s...