Amit Sheth

Amit Sheth
  • Doctor of Philosophy
  • Managing Director at University of South Carolina

About

1,018
Publications
343,206
Reads
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43,603
Citations
Current institution
University of South Carolina
Current position
  • Managing Director
Additional affiliations
January 2007 - November 2018
Wright State University
Position
  • LexisNexis Ohio Eminent Scholar; Exec. Dir. - Kno.e.sis
January 2007 - November 2015
Wright State University
Position
  • LexisNexis Ohio Eminent Scholar
January 2007 - present
Wright State University
Position
  • LexisNexis Ohio Eminent Scholar

Publications

Publications (1,018)
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
Full-text available
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
Full-text available
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
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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...
Article
Full-text available
Background: In the traditional asthma management protocol, a child meets with a clinician infrequently, once in 3 to 6 months, and is assessed using the Asthma Control Test questionnaire. This information is inadequate for timely determination of asthma control, compliance, precise diagnosis of the cause, and assessing the effectiveness of the trea...
Preprint
Full-text available
The ever-growing datasets published on Linked Open Data mainly contain encyclopedic information. However, there is a lack of quality structured and semantically annotated datasets extracted from unstructured real-time sources. In this paper, we present principles for developing a knowledge graph of interlinked events using the case study of news he...
Preprint
Full-text available
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 share health-related information. In this paper, we address an important and timely topic by analyzing the users'...
Article
Full-text available
The Internet of Things (IoT) plays an ever-increasing role in enabling Smart City applications. An ontology-based semantic approach can help improve interoperability between a variety of IoT-generated as well as complementary data needed to drive these applications. While multiple ontology catalogs exist, using them for IoT and smart city applicati...
Article
Full-text available
AI techniques combined with recent advancements in the Internet of Things, Web of Things, and Semantic Web-jointly referred to as the Semantic Web-promise to play an important role in Industry 4.0. As part of this vision, the authors present a Semantic Web of Things for Industry 4.0 (SWeTI) platform. Through realistic use case scenarios, they showc...
Preprint
Full-text available
With 93% of pro-marijuana population in US favoring legalization of medical marijuana, high expectations of a greater return for Marijuana stocks, and public actively sharing information about medical, recreational and business aspects related to marijuana, it is no surprise that marijuana culture is thriving on Twitter. After the legalization of m...
Preprint
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...
Presentation
Full-text available
Ability to extract or estimate location in social media content, and perform location-centric analyses offer unique and wide-ranging applications. Examples include disaster management, demographic and socio-cultural studies, and spatiotemporal tracking. For instance, location information is critical to reach and rescue disaster-stricken people and...
Book
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...
Preprint
BACKGROUND To understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies’ efforts to disseminate relevant informa...
Article
Full-text available
Background: To understand the public sentiment regarding the Zika virus, social media can be leveraged to understand how positive, negative, and neutral sentiments are expressed in society. Specifically, understanding the characteristics of negative sentiment could help inform federal disease control agencies' efforts to disseminate relevant infor...
Article
Full-text available
Digital transformation is driving a new wave of large-scale data-rich smart environments with data on every aspect of our world. The resulting data ecosystems present new challenges and opportunities in the design of intelligent systems and system of systems.
Article
Full-text available
Introduction Sleep disorders are common in children with asthma and have been implicated in poor asthma control. Smart wearables such as the Fitbit wristband allow monitoring patients sleep duration and quality in their natural surroundings. However, the utility and efficacy of using wearable devices to monitor sleep quality and sleep duration in p...
Conference Paper
Full-text available
A quality annotated corpus is essential to research. Despite the recent focus of the Web science community on cyberbullying research, the community lacks standard benchmarks. This paper provides both a quality annotated corpus and an offensive words lexicon capturing different types of harassment content: (i) sexual, (ii) racial, (iii) appearance-r...
Conference Paper
Full-text available
The Web of Things (WoT) is an extension of the Internet of Things (IoT) to ease the access to data generated by things/devices using the benefits of Web technologies. Data is exploited by WoT applications to monitor healthcare or even control home automation devices. The purpose of the Knowledge Extraction for the Web of Things (KE4WoT) challenge i...
Article
Aims: The purpose of this paper is to analyze characteristics of marijuana concentrate users, describe patterns and reasons of use, and identify factors associated with daily use of concentrates among U.S.-based cannabis users recruited via a Twitter-based online survey. Methods: An anonymous Web-based survey was conducted in June 2017 with 687...
Article
Full-text available
Although there is an emerging trend towards generating embeddings for primarily unstructured data, and recently for structured data, there is not yet any systematic suite for measuring the quality of embeddings. This deficiency is further sensed with respect to embeddings generated for structured data because there are no concrete evaluation metric...
Article
Full-text available
Having a quality annotated corpus is essential especially for applied research. Despite the recent focus of Web science community on researching about cyberbullying, the community dose not still have standard benchmarks. In this paper, we publish first, a quality annotated corpus and second, an offensive words lexicon capturing different types type...
Article
Full-text available
Modern healthcare systems now rely on advanced computing methods and technologies, such as IoT devices and clouds, to collect and analyze personal health data at unprecedented scale and depth. Patients, doctors, healthcare providers, and researchers depend on analytical models derived from such data sources to remotely monitor patients, early-diagn...
Article
Full-text available
Internet-of-Things (IoT) is profoundly redefining the way we create, consume, and share information. Health aficionados and citizens are increasingly using IoT technologies to track their sleep, food intake, activity, vital body signals, and other physiological observations. This is complemented by IoT systems that continuously collect health-relat...
Article
Background: "Rosin tech" is an emerging solventless method consisting in applying moderate heat and constant pressure on marijuana flowers to prepare marijuana concentrates referred to as "rosin." This paper explores rosin concentrate-related Twitter data to describe tweet content and analyze differences in rosin-related tweeting across states wit...
Conference Paper
Full-text available
Through the proposed tutorial, we aim to cover the state-of-the-art approaches in Knowledge Graph Construction from various types of data (i.e. unstructured, semi structured and structured data) and using both manual as well as automated methods. We also wish to review applications from various disciplines that benefit from the structure and semant...
Article
Objective: Twitter data offer new possibilities for tracking health-related communications. This study is among the first to apply advanced information processing to identify geographic and content features of cannabis-related tweeting in the United States. Method: Tweets were collected using streaming Application Programming Interface (March-Ma...
Chapter
Full-text available
This chapter presents studies concerning feature engineering for Twitter-based applications. It first discusses how Twitter data can be downloaded from the Twitter Application Programming Interface (API) and the kinds of data available in the downloaded tweets. Then, it discusses various textual features, image and video features, Twitter metadata-...
Article
Full-text available
With the proliferation of social media over the last decade, determining peopletextquoterights attitude with respect to a specific topic, document, interaction or events has fueled research interest in natural language processing and introduced a new channel called textquotedblleftsentiment and emotion analysistextquotedblright [1]. For instance, b...
Article
Full-text available
Rapid developments in hardware, software, and communication technologies have allowed the emergence of Internet-connected sensory devices that provide observation and data measurement from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As the numbers gro...
Article
Full-text available
This article presents a flexible architecture for Internet of Things (IoT) data analytics using the concept of fog computing. The authors identify different actors and their roles in order to design adaptive IoT data analytics solutions. The presented approach can be used to effectively design robust IoT applications that require a tradeoff between...
Article
Full-text available
Healthcare as we know it is in the process of going through a massive change - from episodic to continuous, from disease focused to wellness and quality of life focused, from clinic centric to anywhere a patient is, from clinician controlled to patient empowered, and from being driven by limited data to 360-degree, multimodal personal-public-popula...
Conference Paper
"Wisdom of Crowds" (WoC) refers to a form of collective intelligence in which the aggregate judgment of a group of individuals is, in most instances, superior to that of any one group member. For a crowd to be wise, its members must possess diverse knowledge and viewpoints. Such diversity leads to uncorrelated judgment errors that cancel out in agg...
Conference Paper
This paper exploits a large number of self-labeled emotion tweets as the training data from the source domain to improve emotion identification in target domains (i.e., blogs and fairy tales), where there is a short supply of labeled data. Due to the noisy and ambiguous nature of self-labeled emotion training data, the existing domain adaptation me...
Book
Web Intelligence (WI) aims to achieve a multi-disciplinary balance between research advances in theories and methods usually associated with Collective Intelligence, Data Science, Human-Centric Computing, Knowledge Management, and Network Science. It is committed to addressing research that both deepen the understanding of computational, logical, c...
Conference Paper
Full-text available
Understanding the role of differential gene expression in cancer etiology and cellular process is a complex problem that continues to pose a challenge due to sheer number of genes and inter-related biological processes involved. In this paper, we employ an unsupervised topic model, Latent Dirichlet Allocation (LDA) to mitigate overfitting of high-d...
Conference Paper
Full-text available
With the rise of social media, millions of people are routinely expressing their moods, feelings, and daily struggles with mental health issues on social media platforms like Twitter. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of clinical depression f...
Conference Paper
Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this p...
Conference Paper
Full-text available
Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail),...

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