Computer Sciences Commons^™

Ai In The College Classroom: From Communication To Animation, Stefanie Powers, Erika Grodzki, Gary Carlin, Hung Chum Kao

Faculty and Staff Publications & Presentations

No abstract provided.

Experiences Of Autistic Twitch Livestreamers: “I Have Made Easily The Most Meaningful And Impactful Relationships”, Terrance Mok, Anthony Tang, Adam Mccrimmon, Lora Oehlberg

Research Collection School Of Computing and Information Systems

We present perspectives from 10 autistic Twitch streamers regarding their experiences as livestreamers and how autism uniquely colors their experiences. Livestreaming offers a social online experience distinct from in-person, face-to-face communication, where autistic people tend to encounter challenges. Our reflexive thematic analysis of interviews with 10 participants showcases autistic livestreamers’ perspectives in their own words. Our findings center on the importance of having streamers establishing connections with other, sharing autistic identities, controlling a space for social interaction, personal growth, and accessibility challenges. In our discussion, we highlight the crucial value of having a medium for autistic representation, as well as …

The Power Of Identity Cues In Text-Based Customer Service: Evidence From Twitter, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers’ perceived social presence on service outcomes and customers’ attitudes toward agents. Our identification strategy hinged on Southwest Airlines’ sudden requirement to include a first name in response to service requests on Twitter, which …

How I Read An Article That Uses Machine Learning Methods, Aziz Nazha, Olivier Elemento, Shannon Mcweeney, Moses Miles, Torsten Haferlach

Kimmel Cancer Center Faculty Papers

No abstract provided.

An Interactional Account Of Empathy In Human-Machine Communication, Shauna Concannon, Ian Roberts, Marcus Tomalin

Human-Machine Communication

Efforts to develop empathetic agents, or systems capable of responding appropriately to emotional content, have increased as the deployment of such systems in socially complex scenarios becomes more commonplace. In the context of human-machine communication (HMC), the ability to create the perception of empathy is achieved in large part through linguistic behavior. However, studies of how language is used to display and respond to emotion in ways deemed empathetic are limited. This article aims to address this gap, demonstrating how an interactional linguistics informed methodological approach can be applied to the study of empathy in HMC. We present an analysis …

Impact Of Difficult Negatives On Twitter Crisis Detection, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Twitter has become an alternative information source during a crisis. However, the short, noisy nature of tweets hinders information extraction. While models trained with standard Twitter crisis datasets accomplished decent performance, it remained a challenge to generalize to unseen crisis events. Thus, we proposed adding “difficult” negative examples during training to improve model generalization for Twitter crisis detection. Although adding random noise is a common practice, the impact of difficult negatives, i.e., negative data semantically similar to true examples, was never examined in NLP. Most of existing research focuses on the classification task, without considering the primary information need of …

Hacker, Influencer, Counter-Culture Spy: Cyberspace Actors’ Models Of Misinformation And Counter-Operations, Benjamin Kessell

College of Computing and Digital Media Dissertations

As misinformation continues to spread on social media, its residents have begun to fight back, independent of any platform. This organic resistance to the diffusion of misinformation is a clearly observable phenomenon with roots in Anonymous’ distributed campaigns from the 2010s outwards. Hacker and information security communities are acting in defense of some of their favorite spaces, most notably, Twitter. Security researchers of all stripes use it for sharing indicators of compromise but, as the diffusion of misinformation becomes more problematic it becomes more difficult to find signals in the noise.

These actors’ response to the issues at hand is …

Du Undergraduate Showcase: Research, Scholarship, And Creative Works, Caitlyn Aldersea, Justin Bravo, Sam Allen, Anna Block, Connor Block, Emma Buechler, Maria De Los Angeles Bustillos, Arianna Carlson, William Christensen, Olivia Kachulis, Noah Craver, Kate Dillon, Muskan Fatima, Angel Fernandes, Emma Finch, Colleen Cassidy, Amy Fishman, Andrea Francis, Stacia Fritz, Simran Gill, Emma Gries, Rylie Hansen, Shannon Powers, Jacqueline Martinez, Zachary Harker, Ashley Hasty, Mykaela Tanino-Springsteen, Kathleen Hopps, Adelaide Kerenick, Colin Kleckner, Ci Koehring, Elijah Kruger, Braden Krumholz, Maddie Leake, Lyneé Alves, Seraphina Loukas, Yatzari Lozano Vazquez, Haley Maki, Emily Martinez, Sierra Mckinney, Audrey Mitchell, Kipling Newman, Audrey Ng, Megan Lucyshyn, Andrew Nguyen, Stevie Ostman, Casandra Pearson, Alexandra Penney, Julia Gielczynski, Tyler Ball, Anna Rini, Christina Rorres, Simon Ruland, Helayna Schafer, Emma Sellers, Sarah Schuller, Claire Shaver, Kevin Summers, Isabella Shaw, Madison Sinar, Claudia Pena, Apshara Siwakoti, Carter Sorensen, Madi Sousa, Anna Sparling, Alexandra Revier, Brandon Thierry, Dylan Tyree, Maggie Williams, Lauren Wols

DU Undergraduate Research Journal Archive

DU Undergraduate Showcase: Research, Scholarship, and Creative Works

Individual Differences In Vulnerability To Phishing, Fake News, And Vishing, Jeff Black

All Theses

Digital deception, such as phishing emails, scam phone calls, and fake news, poses a threat to anyone using digital devices. Research on digital deception often points to individual differences like age, cognitive impulsivity, and digital literacy, but has only investigated different types of digital deception independent of each other. Therefore, it is unclear whether users vulnerable to one type of deception are also vulnerable to others, and why. The present research examined relationships between vulnerability to different types of deception, and how this vulnerability is associated with common individual differences like age, cognitive impulsivity, digital literacy, and gullibility, and exploratory …

Resale Hdb Price Prediction Considering Covid-19 Through Sentiment Analysis, Srinaath Anbu Durai, Zhaoxia Wang

Research Collection School Of Computing and Information Systems

Twitter sentiment has been used as a predictor to predict price values or trends in both the stock market and housing market. The pioneering works in this stream of research drew upon works in behavioural economics to show that sentiment or emotions impact economic decisions. Latest works in this stream focus on the algorithm used as opposed to the data used. A literature review of works in this stream through the lens of data used shows that there is a paucity of work that considers the impact of sentiments caused due to an external factor on either the stock or …

Learning-Based Stock Trending Prediction By Incorporating Technical Indicators And Social Media Sentiment, Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Stock trending prediction is a challenging task due to its dynamic and nonlinear characteristics. With the development of social platform and artificial intelligence (AI), incorporating timely news and social media information into stock trending models becomes possible. However, most of the existing works focus on classification or regression problems when predicting stock market trending without fully considering the effects of different influence factors in different phases. To address this gap, this research solves stock trending prediction problem utilizing both technical indicators and sentiments of the social media text as influence factors in different situations. A 3-phase hybrid model is proposed …

Supporting Account-Based Queries For Archived Instagram Posts, Himarsha R. Jayanetti

Computer Science Theses & Dissertations

Social media has become one of the primary modes of communication in recent times, with popular platforms such as Facebook, Twitter, and Instagram leading the way. Despite its popularity, Instagram has not received as much attention in academic research compared to Facebook and Twitter, and its significant role in contemporary society is often overlooked. Web archives are making efforts to preserve social media content despite the challenges posed by the dynamic nature of these sites. The goal of our research is to facilitate the easy discovery of archived copies, or mementos, of all posts belonging to a specific Instagram account …

Extracting Information From Twitter Screenshots, Tarannum Zaki, Michael L. Nelson, Michele C. Weigle

Modeling, Simulation and Visualization Student Capstone Conference

Screenshots are prevalent on social media as a common approach for information sharing. Users rarely verify before sharing screenshots whether they are fake or real. Information sharing through fake screenshots can be highly responsible for misinformation and disinformation spread on social media. There are services of the live web and web archives that could be used to validate the content of a screenshot. We are going to develop a tool that would automatically provide a probability whether a screenshot is fake by using the services of the live web and web archives.

Behind Derogatory Migrants' Terms For Venezuelan Migrants: Xenophobia And Sexism Identification With Twitter Data And Nlp, Joseph Martínez, Melissa Miller-Felton, Jose Padilla, Erika Frydenlund

Modeling, Simulation and Visualization Student Capstone Conference

The sudden arrival of many migrants can present new challenges for host communities and create negative attitudes that reflect that tension. In the case of Colombia, with the influx of over 2.5 million Venezuelan migrants, such tensions arose. Our research objective is to investigate how those sentiments arise in social media. We focused on monitoring derogatory terms for Venezuelans, specifically veneco and veneca. Using a dataset of 5.7 million tweets from Colombian users between 2015 and 2021, we determined the proportion of tweets containing those terms. We observed a high prevalence of xenophobic and defamatory language correlated with the …

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Responses To Sad Emotion In Autistic And Normal Developing Children: Is There A Difference?, Mohamed Basel Almourad, Emad Bataineh, Zelal Wattar

All Works

This paper describes how the gazing pattern differ between the responses of Normal Developing (ND) and Autistic (AP) children to sad emotion. We employed an eye tracking technology to collect and track the participants’ eye movements by showing a dynamic stimulus (video) that showed a gradual transition from pale emotions to melancholy facial expressions in both female and male faces. The location of the child's gaze in the stimulus was the focus of our data analysis. We deduced that there was a distinction between the two groups based on this. ND children predominantly concentrated on the eyes and mouth region …

Investment And Risk Management With Online News And Heterogeneous Networks, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Stock price movements in financial markets are influenced by large volumes of news from diverse sources on the web, e.g., online news outlets, blogs, social media. Extracting useful information from online news for financial tasks, e.g., forecasting stock returns or risks, is, however, challenging due to the low signal-to-noise ratios of such online information. Assessing the relevance of each news article to the price movements of individual stocks is also difficult, even for human experts. In this article, we propose the Guided Global-Local Attention-based Multimodal Heterogeneous Network (GLAM) model, which comprises novel attention-based mechanisms for multimodal sequential and graph encoding, …

Gamesmanship In Modern Discovery Tech, Neel Guha, Peter Henderson, Diego A. Zambrano

Faculty Scholarship

This chapter explores the potential for gamesmanship in technology-assisted discovery. Attorneys have long embraced gamesmanship strategies in analog discovery, producing reams of irrelevant documents, delaying depositions, or interpreting requests in a hyper-technical manner. The new question, however, is whether machine learning technologies can transform gaming strategies. By now it is well known that technologies have reinvented the practice of civil litigation and, specifically, the extensive search for relevant documents in complex cases. Many sophisticated litigants use machine learning algorithms – under the umbrella of “Technology Assisted Review” (TAR) – to simplify the identification and production of relevant documents in discovery. …

Is A Pretrained Model The Answer To Situational Awareness Detection On Social Media?, Siaw Ling Lo, Kahhe Lee, Yuhao Zhang

Research Collection School Of Computing and Information Systems

Social media can be valuable for extracting information about an event or incident on the ground. However, the vast amount of content shared, and the linguistic variants of languages used on social media make it challenging to identify important situational awareness content to aid in decision-making for first responders. In this study, we assess whether pretrained models can be used to address the aforementioned challenges on social media. Various pretrained models, including static word embedding (such as Word2Vec and GloVe) and contextualized word embedding (such as DistilBERT) are studied in detail. According to our findings, a vanilla DistilBERT pretrained language …

Champions For Social Good: How Can We Discover Social Sentiment And Attitude-Driven Patterns In Prosocial Communication?, Raghava Rao Mukkamala, Robert J. Kauffman, Helle Zinner Henriksen

Research Collection School Of Computing and Information Systems

The UN High Commissioner on Refugees (UNHCR) is pursuing a social media strategy to inform people about displaced populations and refugee emergencies. It is actively engaging public figures to increase awareness through its prosocial communications and improve social informedness and support for policy changes in its services. We studied the Twitter communications of UNHCR social media champions and investigated their role as high-profile influencers. In this study, we offer a design science research and data analytics framework and propositions based on the social informedness theory we propose in this paper to assess communication about UNHCR’s mission. Two variables—refugee-emergency and champion …

“Any Means Necessary To Refuse Erasure By Algorithm:” Lillian-Yvonne Bertram’S Travesty Generator, Zach Whalen

Communication & Digital Studies Articles

Lillian-Yvonne Bertram's 2019 book of poetry is titled Travesty Generator in reference to Hugh Kenner and Joseph O'Rourke's Pascal program to “fabricate pseudo-text” by producing text such that each n-length string of characters in the output occurs at the same frequency as in the source text. Whereas for Kenner and O'Rourke, labeling their work a “travesty” is a hyperbolic tease or a literary burlesque, for Bertram, the travesty is the political reality of racism in America. For each of the works Travesty Generator, Bertram uses the generators of computer poetry to critique, resist, and replace narratives of oppression and to …

Anti-American Stance In Turkey: A Twitter Case Study, Gowri Prathap, Alex Korb, Luke Palmieri, Ekrem Kaya, Saltuk Karahan, Hamdi Kavak

School of Cybersecurity Faculty Publications

The availability of social media and biased actors exacerbated Anti-American and Anti-Western views to extremes. In this paper, we report our efforts in analyzing anti-American views on Twitter. We have collected over three years of Turkish tweets related to the US, translated them into English, and analyzed these tweets using various computational social science tools. We found that Turkish tweets related to the US are significantly negative, and emotions reflect disgust and anger. Furthermore, we found that the source of the negative views stems from political actors like Trump or Biden rather than general hatred. Our results shed light on …

Anchorage: Visual Analysis Of Satisfaction In Customer Service Videos Via Anchor Events, Kam Kwai Wong, Xingbo Wang, Yong Wang, Jianben He, Rong Zhang, Huamin Qu

Research Collection School Of Computing and Information Systems

Delivering customer services through video communications has brought new opportunities to analyze customer satisfaction for quality management. However, due to the lack of reliable self-reported responses, service providers are troubled by the inadequate estimation of customer services and the tedious investigation into multimodal video recordings. We introduce , a visual analytics system to evaluate customer satisfaction by summarizing multimodal behavioral features in customer service videos and revealing abnormal operations in the service process. We leverage the semantically meaningful operations to introduce structured event understanding into videos which help service providers quickly navigate to events of their interest. supports a comprehensive …

S-400s, Disinformation, And Anti-American Sentiment In Turkey, Russell "Alex" Korb, Saltuk Karahan, Gowri Prathap, Ekrem Kaya, Luke Palmieri, Hamdi Kavak, Richard L. Wilson (Ed.), Major Brendan Curran (Ed.)

Political Science & Geography Faculty Publications

As social and political discourse in most countries becomes more polarized, anti-Americanism has risen not only in the Middle East and Latin America but also among the U.S. allies in Europe. Social media is one platform used to disseminate anti-American views in NATO countries, and its effectiveness can be magnified when mass media, public officials, and popular figures adopt these views. Disinformation, in particular, has gained recognition as a cybersecurity issue from 2016 onward, but disinformation can be manufactured domestically in addition to being part of a foreign influence campaign. In this paper, we analyze Turkish tweets using sentiment analysis …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Enabling Customization Of Discussion Forums For Blind Users, Mohan Sunkara, Yash Prakash, Hae-Na Lee, Sampath Jayarathna, Vikas Ashok

Computer Science Faculty Publications

Online discussion forums have become an integral component of news, entertainment, information, and video-streaming websites, where people all over the world actively engage in discussions on a wide range of topics including politics, sports, music, business, health, and world affairs. Yet, little is known about their usability for blind users, who aurally interact with the forum conversations using screen reader assistive technology. In an interview study, blind users stated that they often had an arduous and frustrating interaction experience while consuming conversation threads, mainly due to the highly redundant content and the absence of customization options to selectively view portions …

Multivariate Fairness For Paper Selection, Reem Alsaffar

Graduate Theses and Dissertations

Peer review is the process by which publishers select the best publications for inclusion in a journal or a conference. Bias in the peer review process can impact which papers are selected for inclusion in conferences and journals. Although often implicit, race, gender and other demographics can prevent members of underrepresented groups from presenting at major conferences. To try to avoid bias, many conferences use a double-blind review process to increase fairness during reviewing. However, recent studies argue that the bias has not been removed completely. Our research focuses on developing fair algorithms that correct for these biases and select …

Bounded Confidence: How Ai Could Exacerbate Social Media’S Homophily Problem, Dylan Weber, Scott Atran, Rich Davis

New England Journal of Public Policy

The advent of the Internet was heralded as a revolutionary development in the democratization of information. It has emerged, however, that online discourse on social media tends to narrow the information landscape of its users. This dynamic is driven by the propensity of the network structure of social media to tend toward homophily; users strongly prefer to interact with content and other users that are similar to them. We review the considerable evidence for the ubiquity of homophily in social media, discuss some possible mechanisms for this phenomenon, and present some observed and hypothesized effects. We also discuss how the …

Social Access And Representation For Autistic Adult Livestreamers, Terrance Mok, Anthony Tang, Adam Mccrimmon, Lora Oehlberg

Research Collection School Of Computing and Information Systems

We interviewed 10 autistic livestreamers to understand their motivations for livestreaming on Twitch. Our participants explained that streaming helped them fulfill social desires by: supporting them in making meaningful social connections with others; giving them a safe space to practice social skills like “small talk”; and empowering them to be autistic role models and to share their true selves. This work offers an early report on how autistic individuals leverage livestreaming as a beneficial social platform while struggling with audience expectations.

“Be A Pattern For The World”: The Development Of A Dark Patterns Detection Tool To Prevent Online User Loss, Jordan Donnelly, Alan Dowley, Yunpeng Liu, Yufei Su, Quanwei Sun, Lan Zeng, Andrea Curley, Damian Gordon, Paul Kelly, Dympna O'Sullivan, Anna Becevel

Articles

Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns.