Digital Commons Network^™

Using Statistical Methods To Determine Geolocation Via Twitter, Christopher M. Wright

Masters Theses & Specialist Projects

With the ever expanding usage of social media websites such as Twitter, it is possible to use statistical inquires to form a geographic location of a person using solely the content of their tweets. According to a study done in 2010, Zhiyuan Cheng, was able to detect a location of a Twitter user within 100 miles of their actual location 51% of the time. While this may seem like an already significant find, this study was done while Twitter was still finding its ground to stand on. In 2010, Twitter had 75 million unique users registered, as of March 2013, …

Teaching Hdfs/Mapreduce Systems Concepts To Undergraduates, Linh B. Ngo, Amy W. Apon, Edward B. Duffy

Publications

This paper presents the development of a Hadoop MapReduce module that has been taught in a course in distributed computing to upper undergraduate computer science students at Clemson University. The paper describes our teaching experiences and the feedback from the students over several semesters that have helped to shape the course. We provide suggested best practices for lecture materials, the computing platform, and the teaching methods. In addition, the computing platform and teaching methods can be extended to accommodate emerging technologies and modules for related courses.

Simple Effective Named Entity Recognition For Microblogs: Arabic As An Example, Kareem Darwish, Wei Gao

Research Collection School Of Computing and Information Systems

No abstract provided.

An Integrated Model For User Attribute Discovery: A Case Study On Political Affiliation Identification, Swapna Gottipati, Minghui Qiu, Liu Yang, Feida Zhu, Jing Jiang

Research Collection School Of Computing and Information Systems

Discovering user demographic attributes from social media is a problem of considerable interest. The problem setting can be generalized to include three components — users, topics and behaviors. In recent studies on this problem, however, the behavior between users and topics are not effectively incorporated. In our work, we proposed an integrated unsupervised model which takes into consideration all the three components integral to the task. Furthermore, our model incorporates collaborative filtering with probabilistic matrix factorization to solve the data sparsity problem, a computational challenge common to all such tasks. We evaluated our method on a case study of user …

White Noise And Newer Media: The Prophetic Impact Of Jack's Avatars, Caleb Milligan

All Theses

In this paper, I analyze Don DeLillo's White Noise through a contemporary techno-literate approach that utilizes Internet and game studies to better understand its protagonist, Jack Gladney, and to reevaluate the novel's critical legacy. Jack is not a modernist living in a postmodern world, as critics like Tom LeClair, John Duvall, and Leonard Wilcox have claimed for the many years since the publication of this novel. Lacking the authentic consistency for such a title, he is instead a postmodern human simulacrum sampling different character types to avoid his lack of discernable self. In each role he plays, however, he is …

Using The Web 1t 5-Gram Database For Attribute Selection In Formal Concept Analysis To Correct Overstemmed Clusters, Guymon Hall

UNLV Theses, Dissertations, Professional Papers, and Capstones

Information retrieval is the process of finding information from an unstructured collection of data. The process of information retrieval involves building an index, commonly called an inverted file. As part of the inverted file, information retrieval algorithms often stem words to a common root. Stemming involves reducing a document term to its root. There are many ways to stem a word: affix removal and successor variety are two common categories of stemmers. The Porter Stemming Algorithm is a suffix removal stemmer that operates as a rule-based process on English words. We can think of stemming as a way to cluster …

Recurrent Chinese Restaurant Process With A Duration-Based Discount For Event Identification From Twitter, Qiming Diao, Jing Jiang

Research Collection School Of Computing and Information Systems

Due to the fast development of social media on the Web, Twitter has become one of the major platforms for people to express themselves. Because of the wide adoption of Twitter, events like breaking news and release of popular videos can easily catch people’s attention and spread rapidly on Twitter, and the number of relevant tweets approximately reflects the impact of an event. Event identification and analysis on Twitter has thus become an important task. Recently the Recurrent Chinese Restaurant Process (RCRP) has been successfully used for event identification from news streams and news-centric social media streams. However, these models …

Leveraging Social Media And Web Of Data For Crisis Response Coordination, Carlos Castillo, Fernando Diaz, Hemant Purohit

Kno.e.sis Publications

There is an ever increasing number of users in social media (1B+ Facebook users, 500M+ Twitter users) and ubiquitous mobile access (6B+ mobile phone subscribers) who share their observations and opinions. In addition, the Web of Data and existing knowledge bases keep on growing at a rapid pace. In this scenario, we have unprecedented opportunities to improve crisis response by extracting social signals, creating spatio-temporal mappings, performing analytics on social and Web of Data, and supporting a variety of applications. Such applications can help provide situational awareness during an emergency, improve preparedness, and assist during the rebuilding/recovery phase of a …

Volume 06, Kristen Gains, Amanda Willis, Holly Backer, Monika Gutierrez, Cara O'Neal, Sara Nelson, Sasha Silberman, Jessica Beardsley, Jamie Gardner, Edward Peeples, Matthew Sakach, Tess Lione, Emily Wilkins, Kelsey Holt, Jessica Page, Jamie Clift, Charles Vancampen, Gilbert Hall, Jenny Nehrt, Kasey Dye, Amanda Tharp, Jamie Leeuwrik, Ashley Mcgee, Emily Poulin, Michael Kropf, Nick Pastore, Austin Polasky, Morgan Glasco, Laura L. Kahler, Melinda L. Edwards, Brandon C. Smith, Mariah Asbell, Cabell Edmunds, Amelia D. Perry, Alyssa Hayes, Irina Boothe, Perry Bason, James Early

Incite: The Journal of Undergraduate Scholarship

Introduction from Dean Dr. Charles Ross

Caught Between Folklore and the Cold War: The Americanization of Russian Children's Literature by Kristen Gains

Graphic Design by Amanda Willis

Graphic Design by Holly Backer

Prejudices in Swiss German Accents by Monika Gutierrez

Photography by Cara O'Neal

Photography by Sara Nelson

Edmund Tyrone's Long Journey through Night by Sasha Silberman

Photography by Jessica Beardsley

Photography by Jamie Gardner and Edward Peeples

The Republican Razor: The Guillotine as a Symbol of Equality by Jamie Clift

Graphic Design by Matthew Sakach

Genocide: The Lasting Effects of Gender Stratification in Rwanda By Tess Lione and Emily …

Web Archive Services Framework For Tighter Integration Between The Past And Present Web, Ahmed Alsum

Computer Science Theses & Dissertations

Web archives have contained the cultural history of the web for many years, but they still have a limited capability for access. Most of the web archiving research has focused on crawling and preservation activities, with little focus on the delivery methods. The current access methods are tightly coupled with web archive infrastructure, hard to replicate or integrate with other web archives, and do not cover all the users' needs. In this dissertation, we focus on the access methods for archived web data to enable users, third-party developers, researchers, and others to gain knowledge from the web archives. We build …

Incorporating Wordnet In An Information Retrieval System, Shailesh Padave

Master's Projects

Query expansion is a method of modifying an initial query to enhance retrieval performance in information retrieval operations [11] . There are alternate ways to expand a user input query such as finding synonyms of words, re-weighting the query, fixing spelling mistakes, etc. [11] . In this project, we created a query rewriting algorithm, which uses synonyms for a given word for query expansion. These synonyms were chosen using WordNet, a lexical database for English [16] [15] . Similarity ranking functions and a part-of- speech tagger were written to extract the essential data from WordNet output. Various experiments were carried …

Big Data Analysis Using Neuro-Fuzzy System, Amir Eibagi

Master's Projects

This project addresses big data classification using hybrid Intelligence
Classification System. Hybrid Intelligence classification system is a system that
combines at least two intelligent technologies. Specifically, the focus of this project is to
apply hybrid Neuro-Fuzzy system to the IBM Watson data and Innocentive
Trustworthiness challenge data for prediction and classification. Neural network are low-
level computational structure which has ability to learn and performs well on the raw
data. On the other hand, fuzzy logic deals with reasoning on higher level using If-then
rules and linguistic variables. So combining these two methods can provide us with a
very powerful …

Computational Pain Quantification And The Effects Of Age, Gender, Culture And Cause, Colin R. Ostberg

Master's Theses (2009 -)

Chronic pain affects more than 100 million Americans and more than 1.5 billion people worldwide. Pain is a multidimensional construct, expressed through a variety of means. Facial expressions are one such type of pain expression. Automatic facial expression recognition, and in particular pain expression recognition, are fields that have been studied extensively. However, nothing has explored the possibility of an automatic pain quantification algorithm, able to output pain levels based upon a facial image. Developed for a remote monitoring context, a computational pain quantification algorithm has been developed and validated by two distinct sets of data. The second set of …

Stfu Noob!: Predicting Crowdsourced Decisions On Toxic Behavior In Online Games, Jeremy Blackburn, Haewoon Kwak

Research Collection School Of Computing and Information Systems

One problem facing players of competitive games is negative, or toxic, behavior. League of Legends, the largest eSport game, uses a crowdsourcing platform called the Tribunal to judge whether a reported toxic player should be punished or not. The Tribunal is a two stage system requiring reports from those players that directly observe toxic behavior, and human experts that review aggregated reports. While this system has successfully dealt with the vague nature of toxic behavior by majority rules based on many votes, it naturally requires tremendous cost, time, and human efforts. In this paper, we propose a supervised learning approach …

Logic Of Scientific Discovery: How Physical Induction Affects What Is Computable, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Most of our knowledge about a physical world comes from physical induction: if a hypothesis is confirmed by a sufficient number of observations, we conclude that this hypothesis is universally true. We show that a natural formalization of this property affects what is computable when processing measurement and observation results, and we explain how this formalization is related to Kolmogorov complexity and randomness. We also consider computational consequences of an alternative idea also coming form physics: that no physical law is absolutely true, that every physical law will sooner or later need to be corrected. It turns out that this …

On Predicting User Affiliations Using Social Features In Online Social Networks, Minh Thap Nguyen

Dissertations and Theses Collection (Open Access)

User profiling such as user affiliation prediction in online social network is a challenging task, with many important applications in targeted marketing and personalized recommendation. The research task here is to predict some user affiliation attributes that suggest user participation in different social groups.

Investigating Automatic Measurements Of Prosodic Accommodation And Its Dynamics In Social Interaction, Celine De Looze, Stefan Scherer, Brian Vaughan, Nick Campbell

Articles

Spoken dialogue systems are increasingly being used to facilitate and enhance human communication. While these interactive systems can process the linguistic aspects of human communication, they are not yet capable of processing the complex dynamics involved in social interaction, such as the adaptation on the part of interlocutors. Providing interactive systems with the capacity to process and exhibit this accommodation could however improve their efficiency and make machines more socially-competent interactants.

At present, no automatic system is available to process prosodic accommodation, nor do any clear measures exist that quantify its dynamic manifestation. While it can be observed to be …

A Comparative Study On The Effectiveness Of Part-Of-Speech Tagging Techniques On Bug Reports, Yuan Tian, David Lo

Research Collection School Of Computing and Information Systems

Many software artifacts are written in natural language or contain substantial amount of natural language contents. Thus these artifacts could be analyzed using text analysis techniques from the natural language processing (NLP) community, e.g., the part-of-speech (POS) tagging technique that assigns POS tags (e.g., verb, noun, etc.) to words in a sentence. In the literature, several studies have already applied POS tagging technique on software artifacts to recover important words in them, which are then used for automating various tasks, e.g., locating buggy files for a given bug report, etc. There are many POS tagging techniques proposed and they are …

Applicability Of Latent Dirichlet Allocation To Multi-Disk Search, George E. Noel, Gilbert L. Peterson

Faculty Publications

Digital forensics practitioners face a continual increase in the volume of data they must analyze, which exacerbates the problem of finding relevant information in a noisy domain. Current technologies make use of keyword based search to isolate relevant documents and minimize false positives with respect to investigative goals. Unfortunately, selecting appropriate keywords is a complex and challenging task. Latent Dirichlet Allocation (LDA) offers a possible way to relax keyword selection by returning topically similar documents. This research compares regular expression search techniques and LDA using the Real Data Corpus (RDC). The RDC, a set of over 2400 disks from real …

A Computational Approach To Qualitative Analysis In Large Textual Datasets, Michael Evans

Dartmouth Scholarship

In this paper I introduce computational techniques to extend qualitative analysis into the study of large textual datasets. I demonstrate these techniques by using probabilistic topic modeling to analyze a broad sample of 14,952 documents published in major American newspapers from 1980 through 2012. I show how computational data mining techniques can identify and evaluate the significance of qualitatively distinct subjects of discussion across a wide range of public discourse. I also show how examining large textual datasets with computational methods can overcome methodological limitations of conventional qualitative methods, such as how to measure the impact of particular cases on …

Cursing In English On Twitter, Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of …

Automated Learner Classification Through Interface Event Stream And Summary Statistics Analysis, Edgar E. Troudt

Dissertations, Theses, and Capstone Projects

Reading comprehension is predominately measured through multiple choice examinations. Yet, as we will discuss in this thesis, such exams are often criticized for their inaccuracies. With the advent of "big data" and the rise of ITS (Intelligent Tutoring Systems), increasing focus will be placed on finding dynamic, automated ways of measuring students' aptitude and progress.

This work takes the first step towards automated learner classification based on the application of graphic organizers. We address the following specific problem experimentally: How effectively can we measure task comprehension via human translation of written text into a visual representation on a computer? Can …

Data-Driven Synthesis Of Animations Of Spatially Inflected American Sign Language Verbs Using Human Data, Pengfei Lu

Dissertations, Theses, and Capstone Projects

Techniques for producing realistic and understandable animations of American Sign Language (ASL) have accessibility benefits for signers with lower levels of written language literacy. Previous research in sign language animation didn’t address the specific linguistic issue of space use and verb inflection, due to a lack of sufficiently detailed and linguistically annotated ASL corpora, which is necessary for modern data-driven approaches. In this dissertation, a high-quality ASL motion capture corpus with ASL-specific linguistic structures is collected, annotated, and evaluated using carefully designed protocols and well-calibrated motion capture equipment. In addition, ASL animations are modeled, synthesized, and evaluated based on samples …

Svmaud: Using Textual Information To Predict The Audience Level Of Written Works Using Support Vector Machines, Todd Will

Dissertations

Information retrieval systems should seek to match resources with the reading ability of the individual user; similarly, an author must choose vocabulary and sentence structures appropriate for his or her audience. Traditional readability formulas, including the popular Flesch-Kincaid Reading Age and the Dale-Chall Reading Ease Score, rely on numerical representations of text characteristics, including syllable counts and sentence lengths, to suggest audience level of resources. However, the author’s chosen vocabulary, sentence structure, and even the page formatting can alter the predicted audience level by several levels, especially in the case of digital library resources. For these reasons, the performance of …

Pharaoh: Conceptual Blending Of Cognitive Scripts For Computationally Creative Agents, Rania Hodhod

Faculty Bibliography

Improvisational acting is a creative group performance where actors co-construct stories on stage in real-time based on actors’ perceptions of the environment. The Digital Improv Project has been engaged in a multi-year study of the cognitive processes involved in improvisational acting. This better understanding of human cognition and creativity has led to formal computational models of some aspects of our findings. In this work, we consider enriching AI improv agents with the ability to improvise new nontraditional scenes based on existing social cognitive scripts. This paper shows how the use of Pharaoh -a context based structural retrieval algorithm for cognitive …

Ontology Design Patterns For Ocean Science Data Discovery, Pascal Hitzler

Computer Science and Engineering Faculty Publications

No abstract provided.

Modeling Tolerance In Dynamic Social Networks, Amanda Luby

Honors Theses, 1963-2015

The study of social networks has become increasingly important in recent years. Multi-agent systems research has proven to be an effective way of representing both static and dynamic social networks in order to model and analyze many different situations. Previous implementations of multi-agent systems have observed a phenomenon called tolerance between agents through simulation studies, which is defined as an agent maintaining an unrewarding connection. This concept has also arisen in the social sciences through the study of networks. We aim to bridge this gap between simulation studies in multi-agent systems and real-world observations. This project explores how local interactions …

Online Efficient And Effective Search In Large And Noisy Sequence Databases, Alexios Kotsifakos

Computer Science and Engineering Dissertations - Archive

This thesis investigates the problem of similarity search in large and noisy sequence databases. A key application domain of interest in this work is the very challenging Query-By-Humming (QBH) problem, according to which, given a hummed part of a song, we would like to identify the closest matches in a large music repository. The problem of selecting the most appropriate, based on each specific query, distance measure out of a pool of measures for classification in time series data is also investigated. In addition, searching time series databases via examples, which may be either time series or models, is also …

Location Prediction Of Twitter Users Using Wikipedia, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan

Kno.e.sis Publications

The mining of user generated content in social media has proven very effective in domains ranging from personalization and recommendation systems to crisis management. The knowledge of online users locations makes their tweets more informative and adds another dimension to their analysis. Existing approaches to predict the location of Twitter users are purely data-driven and require large training data sets of geo-tagged tweets. The collection and modelling process of tweets can be time intensive. To overcome this drawback, we propose a novel knowledge based approach that does not require any training data. Our approach uses information in Wikipedia, about cities …

A Context-Driven Subgraph Model For Literature-Based Discovery, Delroy Huborn Cameron

Browse all Theses and Dissertations

Literature-Based Discovery (LBD) refers to the process of uncovering hidden connections that are implicit in scientific literature. Numerous hypotheses have been generated from scientific literature using the LBD paradigm, which influenced innovations in diagnosis, treatment, preventions and overall public health. However, much of the existing research on discovering hidden connections among concepts have used distributional statistics and graph-theoretic measures to capture implicit associations. Such metrics do not explicitly capture the semantics of hidden connections. Rather, they only allude to the existence of meaningful underlying associations. To gain in-depth insights into the meaning of hidden (and other) connections, complementary methods have …