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Trends In Women’S Participation In Computer Industry Subfields, Tristyn Maalouf 2019 Liberty University

Trends In Women’S Participation In Computer Industry Subfields, Tristyn Maalouf

The Kabod

The participation of women in specific subfields of computer science (CS) and information technology (IT) will be investigated to determine the existence of any trends that may exist indicating special interest amongst women. Specifically, the subfield of database administration will be considered to determine if women tend to enter this subfield more frequently than other subfields. Research will also acknowledge statistics regarding male participation in database administration and other relevant subfields to determine if any trends in women’s participation are unique to women or if they exist across the board. Conclusions will be drawn based on the data and ...


Cs04all: Machine Learning Module, Hunter R. Johnson 2019 CUNY John Jay College

Cs04all: Machine Learning Module, Hunter R. Johnson

Open Educational Resources

These are materials that may be used in a CS0 course as a light introduction to machine learning.

The materials are mostly Jupyter notebooks which contain a combination of labwork and lecture notes. There are notebooks on Classification, An Introduction to Numpy, and An Introduction to Pandas.

There are also two assessments that could be assigned to students. One is an essay assignment in which students are asked to read and respond to an article on machine bias. The other is a lab-like exercise in which students use pandas and numpy to extract useful information about subway ridership in NYC ...


Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth 2019 Wright State University - Main Campus

Question Answering For Suicide Risk Assessment Using Reddit, Amanuel Alambo, Usha Lokala, Ugur Kursuncu, Krishnaprasad Thirunarayan, Amelia Gyrard, Randon S. Welton, Jyotishman Pathak, Amit P. Sheth

Kno.e.sis Publications

Mental Health America designed ten questionnaires that are used to determine the risk of mental disorders. They are also commonly used by Mental Health Professionals (MHPs) to assess suicidality. Specifically, the Columbia Suicide Severity Rating Scale (C-SSRS), a widely used suicide assessment questionnaire, helps MHPs determine the severity of suicide risk and offer an appropriate treatment. A major challenge in suicide treatment is the social stigma wherein the patient feels reluctance in discussing his/her conditions with an MHP, which leads to inaccurate assessment and treatment of patients. On the other hand, the same patient is comfortable freely discussing his ...


Online Sharing Of Documents: The Mobile Office, Rebecca Sulyma, Sanjay Ram, Steven C. Hatch 2019 University of Massachusetts Medical School

Online Sharing Of Documents: The Mobile Office, Rebecca Sulyma, Sanjay Ram, Steven C. Hatch

PEER Liberia Project

This presentation provides an overview of cloud-based office programs, cloud computing, and filesharing, covering products such as Google docs, Microsoft Office, OneDrive, and Dropbox.


Dish: Democracy In State Houses, Nicholas A. Russo 2019 California Polytechnic State University, San Luis Obispo

Dish: Democracy In State Houses, Nicholas A. Russo

Master's Theses and Project Reports

In our current political climate, state level legislators have become increasingly impor- tant. Due to cuts in funding and growing focus at the national level, public oversight for these legislators has drastically decreased. This makes it difficult for citizens and activists to understand the relationships and commonalities between legislators. This thesis provides three contributions to address this issue. First, we created a data set containing over 1200 features focused on a legislator’s activity on bills. Second, we created embeddings that represented a legislator’s level of activity and engagement for a given bill using a custom model called Democracy2Vec ...


How To Derive Causal Insights For Digital Commerce In China? A Research Commentary On Computational Social Science Methods, David C.W. PHANG, Kanliang WANG, Qiu-hong WANG, Robert John KAUFFMAN, Maurizio NALDI 2019 Singapore Management University

How To Derive Causal Insights For Digital Commerce In China? A Research Commentary On Computational Social Science Methods, David C.W. Phang, Kanliang Wang, Qiu-Hong Wang, Robert John Kauffman, Maurizio Naldi

Research Collection School Of Information Systems

The transformation of empirical research due to the arrival of big data analytics and data science, as well as the new availability of methods that emphasize causal inference, are moving forward at full speed. In this Research Commentary, we examine the extent to which this has the potential to influence how e-commerce research is conducted. China offers the ultimate in data-at-scale settings, and the construction of real-world natural experiments. Chinese e-commerce includes some of the largest firms involved in e-commerce, mobile commerce, social media and social networks. This article was written to encourage young faculty and doctoral students to engage ...


Adaptive Cost-Sensitive Online Classification, Peilin ZHAO, Yifan ZHANG, Min WU, Steven C. H. HOI, Mingkui TAN, Junzhou HUANG 2019 South China University of Technology

Adaptive Cost-Sensitive Online Classification, Peilin Zhao, Yifan Zhang, Min Wu, Steven C. H. Hoi, Mingkui Tan, Junzhou Huang

Research Collection School Of Information Systems

Cost-Sensitive Online Classification has drawn extensive attention in recent years, where the main approach is to directly online optimize two well-known cost-sensitive metrics: (i) weighted sum of sensitivity and specificity; (ii) weighted misclassification cost. However, previous existing methods only considered first-order information of data stream. It is insufficient in practice, since many recent studies have proved that incorporating second-order information enhances the prediction performance of classification models. Thus, we propose a family of cost-sensitive online classification algorithms with adaptive regularization in this paper. We theoretically analyze the proposed algorithms and empirically validate their effectiveness and properties in extensive experiments. Then ...


Trends In Phishing Attacks: Suggestions For Future Research, Ryan M. Schuetzler 2019 University of Nebraska at Omaha

Trends In Phishing Attacks: Suggestions For Future Research, Ryan M. Schuetzler

Ryan Schuetzler

Deception in computer-mediated communication is a widespread phenomenon. Cyber criminals are exploiting technological mediums to communicate with potential targets as these channels reduce both the deception cues and the risk of detection itself. A prevalent deception-based attack in computer-mediated communication is phishing. Prior phishing research has addressed the “bait” and “hook” components of phishing attacks, the human-computer interaction that takes place as users judge the veracity of phishing emails and websites, and the development of technologies that can aid users in identifying and rejecting these attacks. Despite the extant research on this topic, phishing attacks continue to be successful as ...


When Disclosure Is Involuntary: Empowering Users With Control To Reduce Concerns, David W. Wilson, Ryan M. Schuetzler, Bradley Dorn, Jeffrey Gainer Proudfoot 2019 University of Oklahoma Norman Campus

When Disclosure Is Involuntary: Empowering Users With Control To Reduce Concerns, David W. Wilson, Ryan M. Schuetzler, Bradley Dorn, Jeffrey Gainer Proudfoot

Ryan Schuetzler

Modern organizations must carefully balance the practice of gathering large amounts of valuable data from individuals with the associated ethical considerations and potential negative public image inherent in breaches of privacy. As it becomes increasingly commonplace for many types of information to be collected without individuals' knowledge or consent, managers and researchers alike can benefit from understanding how individuals react to such involuntary disclosures, and how these reactions can impact evaluations of the data-collecting organizations. This research develops and empirically tests a theoretical model that shows how empowering individuals with a sense of control over their personal information can help ...


Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson 2019 University of Nebraska at Omaha

Real-Time Embodied Agent Adaptation, Ryan M. Schuetzler, David W. Wilson

Ryan Schuetzler

This paper reports on initial investigation of two emerging technologies, FaceFX and Smartbody, capable of creating life-like animations for embodied conversational agents (ECAs) such as the AVATAR agent. Real-time rendering and animation generation technologies can enable rapid adaptation of ECAs to changing circumstances. The benefits of each package are discussed.


The Influence Of Conversational Agent Embodiment And Conversational Relevance On Socially Desirable Responding, Ryan M. Schuetzler, Justin Scott Giboney, G. Mark Grimes, Jay F. Nunamaker Jr. 2019 University of Nebraska at Omaha

The Influence Of Conversational Agent Embodiment And Conversational Relevance On Socially Desirable Responding, Ryan M. Schuetzler, Justin Scott Giboney, G. Mark Grimes, Jay F. Nunamaker Jr.

Ryan Schuetzler

Conversational agents (CAs) are becoming an increasingly common component in a wide range of information systems. A great deal of research to date has focused on enhancing traits that make CAs more humanlike. However, few studies have examined the influence such traits have on information disclosure. This research builds on self-disclosure, social desirability, and social presence theories to explain how CA anthropomorphism affects disclosure of personally sensitive information. Taken together, these theories suggest that as CAs become more humanlike, the social desirability of user responses will increase. In this study, we use a laboratory experiment to examine the influence of ...


Robustness Of Multiple Indicators In Automated Screening Systems For Deception Detection, Nathan Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Aaron Elkins, Douglas C. Derrick 2019 Missouri University of Science and Technology

Robustness Of Multiple Indicators In Automated Screening Systems For Deception Detection, Nathan Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Aaron Elkins, Douglas C. Derrick

Ryan Schuetzler

This study investigates the effectiveness of an automatic system for detection of deception by individuals with the use of multiple indicators of such potential deception. Deception detection research in the information systems discipline has postulated increased accuracy through a new class of screening systems that automatically conduct interviews and track multiple indicators of deception simultaneously. Understanding the robustness of this new class of systems and the limitations of its theoretical improved performance is important for refinement of the conceptual design. The design science proof-of-concept study presented here implemented and evaluated the robustness of these systems for automated screening for deception ...


Kinesic Patterning In Deceptive And Truthful Interactions, Judee K. Burgoon, Ryan M. Schuetzler, David W. Wilson 2019 University of Arizona

Kinesic Patterning In Deceptive And Truthful Interactions, Judee K. Burgoon, Ryan M. Schuetzler, David W. Wilson

Ryan Schuetzler

A persistent question in the deception literature has been the extent to which nonverbal behaviors can reliably distinguish between truth and deception. It has been argued that deception instigates cognitive load and arousal that are betrayed through visible nonverbal indicators. Yet, empirical evidence has often failed to find statistically significant or strong relationships. Given that interpersonal message production is characterized by a high degree of simultaneous and serial patterning among multiple behaviors, it may be that patterns of behaviors are more diagnostic of veracity. Or it may be that the theorized linkage between internal states of arousal, cognitive taxation, and ...


Man Vs. Machine: Investigating The Effects Of Adversarial System Use On End-User Behavior In Automated Deception Detection Interviews, Jeffrey Gainer Proudfoot, Randall Boyle, Ryan M. Schuetzler 2019 Bentley University

Man Vs. Machine: Investigating The Effects Of Adversarial System Use On End-User Behavior In Automated Deception Detection Interviews, Jeffrey Gainer Proudfoot, Randall Boyle, Ryan M. Schuetzler

Ryan Schuetzler

Deception is an inevitable component of human interaction. Researchers and practitioners are developing information systems to aid in the detection of deceptive communication. Information systems are typically adopted by end users to aid in completing a goal or objective (e.g., increasing the efficiency of a business process). However, end-user interactions with deception detection systems (adversarial systems) are unique because the goals of the system and the user are orthogonal. Prior work investigating systems-based deception detection has focused on the identification of reliable deception indicators. This research extends extant work by looking at how users of deception detection systems alter ...


Overview And Guidance On Agile Development In Large Organizations, Jordan B. Barlow, Justin Scott Giboney, Mark Jeffrey Keith, David W. Wilson, Ryan Schuetzler, Paul Benjamin Lowry, Anthony Vance 2019 Indiana University

Overview And Guidance On Agile Development In Large Organizations, Jordan B. Barlow, Justin Scott Giboney, Mark Jeffrey Keith, David W. Wilson, Ryan Schuetzler, Paul Benjamin Lowry, Anthony Vance

Ryan Schuetzler

A continual debate surrounds the effectiveness of agile software development practices. Some organizations adopt agile practices to become more competitive, improve processes, and reduce costs. Other organizations are skeptical about whether agile development is beneficial. Large organizations face an additional challenge in integrating agile practices with existing standards and business processes. To examine the effects of agile development practices in large organizations, we review and integrate scientific literature and theory on agile software development. We further organize our theory and observations into a framework with guidelines for large organizations considering agile methodologies. Based on this framework, we present recommendations that ...


Establishing A Foundation For Automated Human Credibility Screening, Jay F. Nunamaker Jr., Judee K. Burgoon, Nathan W. Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Justin Scott Giboney 2019 University of Arizona

Establishing A Foundation For Automated Human Credibility Screening, Jay F. Nunamaker Jr., Judee K. Burgoon, Nathan W. Twyman, Jeffrey Gainer Proudfoot, Ryan M. Schuetzler, Justin Scott Giboney

Ryan Schuetzler

Automated human credibility screening is an emerging research area that has potential for high impact in fields as diverse as homeland security and accounting fraud detection. Systems that conduct interviews and make credibility judgments can provide objectivity, improved accuracy, and greater reliability to credibility assessment practices, need to be built. This study establishes a foundation for developing automated systems for human credibility screening.


Countermeasures And Eye Tracking Deception Detection, Ryan M. Schuetzler 2019 University of Nebraska at Omaha

Countermeasures And Eye Tracking Deception Detection, Ryan M. Schuetzler

Ryan Schuetzler

A new development in the field of deception detection is been the development of rapid, noncontact tools for automated detection. This research in progress paper describes a method for assessing the robustness of eye tracker-based deception detection to countermeasures employed by knowledgeable participants.


Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment, Ryan M. Schuetzler, Mark Grimes, Justin Scott Giboney, Joesph Buckman 2019 University of Nebraska at Omaha

Facilitating Natural Conversational Agent Interactions: Lessons From A Deception Experiment, Ryan M. Schuetzler, Mark Grimes, Justin Scott Giboney, Joesph Buckman

Ryan Schuetzler

This study reports the results of a laboratory experiment exploring interactions between humans and a conversational agent. Using the ChatScript language, we created a chat bot that asked participants to describe a series of images. The two objectives of this study were (1) to analyze the impact of dynamic responses on participants’ perceptions of the conversational agent, and (2) to explore behavioral changes in interactions with the chat bot (i.e. response latency and pauses) when participants engaged in deception. We discovered that a chat bot that provides adaptive responses based on the participant’s input dramatically increases the perceived ...


A Systems Approach To Countermeasures In Credibility Assessment Interviews, Nathan Twyman, Ryan M. Schuetzler, Jeffrey Gainer Proudfoot, Aaron Elkins 2019 University of Arizona

A Systems Approach To Countermeasures In Credibility Assessment Interviews, Nathan Twyman, Ryan M. Schuetzler, Jeffrey Gainer Proudfoot, Aaron Elkins

Ryan Schuetzler

Countermeasures, or techniques for hiding guilt during a credibility assessment examination, have long been an important topic in cognitive psychology and criminal justice fields. With recent IS research on automated screening systems, understanding the potential for countermeasures in this new paradigm is of increasing importance. This paper reports on a large experiment examining countermeasures in an automated deception detection screening context. The effectiveness of traditional countermeasure types (mental and physical) are examined, as well as an exploratory approach of trying several countermeasures at once. The exploratory approach was tested to investigate a proposed novel systems-inspired solution to countermeasures—triangulating on ...


Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater 2019 Southern Methodist University

Improving Vix Futures Forecasts Using Machine Learning Methods, James Hosker, Slobodan Djurdjevic, Hieu Nguyen, Robert Slater

SMU Data Science Review

The problem of forecasting market volatility is a difficult task for most fund managers. Volatility forecasts are used for risk management, alpha (risk) trading, and the reduction of trading friction. Improving the forecasts of future market volatility assists fund managers in adding or reducing risk in their portfolios as well as in increasing hedges to protect their portfolios in anticipation of a market sell-off event. Our analysis compares three existing financial models that forecast future market volatility using the Chicago Board Options Exchange Volatility Index (VIX) to six machine/deep learning supervised regression methods. This analysis determines which models provide ...


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