Digital Commons Network^™

Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang

Research Collection School Of Computing and Information Systems

No abstract provided.

The Accessible User Interaction Framework For Android Applications, Xiaoxi Luo

Master's Theses

As mobile technologies advance, accessibility features of smartphones are continu- ously improving and becoming more prevalent. It is essential that the user interaction design of mobile applications provides equal access and equal service to all our com- munity, especially for people with disabilities. However, there are no general mobile accessibility design guidelines publicly available. This paper reviews the web acces- sibility development guidelines as a reference, and the current accessibility features provided by modern mobile operating systems.

It is proposed in this paper to use interactive spoken dialogues as the user interac- tion framework for accessible mobile applications. The idea …

Understanding Common Perceptions From Online Social Media, Derek Doran, Swapna S. Gokhale, Aldo Dagnino

Computer Science and Engineering Faculty Publications

Modern society habitually uses online social media services to publicly share observations, thoughts, opinions, and beliefs at any time and from any location. These geotagged social media posts may provide aggregate insights into people's perceptions on a bad range of topics across a given geographical area beyond what is currently possible through services such as Yelp and Foursquare. This paper develops probabilistic language models to investigate whether collective, topic-based perceptions within a geographical area can be extracted from the content of geotagged Twitter posts. The capability of the methodology is illustrated using tweets from three areas of different sizes. An …

A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang

Research Collection School Of Computing and Information Systems

No abstract provided.

Explore Global Opportunities For Mathematics Scholarship, Teaching, And Service, Ron Benbow

ACMS Conference Proceedings 2013

There are numerous overseas opportunities in which to apply your knowledge and interest in mathematics. These international experiences allow you to expand your scholarship, to extend your teaching skills, to offer professional services to K-12 teachers or other university instructors, and to provide much personal enrichment as well. Examples from recent professional experiences in Liberia, Haiti, Guatemala, and Ecuador will be shared to illustrate the connections to teaching, scholarship, and service. Information regarding MAA Study Tours, Fulbright Specialist grants, and other relevant organizations will be provided.

Misheard Me Oronyminator: Using Oronyms To Validate The Correctness Of Frequency Dictionaries, Jennifer G. Hughes

Master's Theses

In the field of speech recognition, an algorithm must learn to tell the difference between "a nice rock" and "a gneiss rock". These identical-sounding phrases are called oronyms. Word frequency dictionaries are often used by speech recognition systems to help resolve phonetic sequences with more than one possible orthographic phrase interpretation, by looking up which oronym of the root phonetic sequence contains the most-common words.

Our paper demonstrates a technique used to validate word frequency dictionary values. We chose to use frequency values from the UNISYN dictionary, which tallies each word on a per-occurance basis, using a proprietary text corpus, …

Mining User Relations From Online Discussions Using Sentiment Analysis And Probabilistic Matrix Factorization, Minghui Qiu, Liu Yang, Jing Jiang

Research Collection School Of Computing and Information Systems

Advances in sentiment analysis have enabled extraction of user relations implied in online textual exchanges such as forum posts. However, recent studies in this direction only consider direct relation extraction from text. As user interactions can be sparse in online discussions, we propose to apply collaborative filtering through probabilistic matrix factorization to generalize and improve the opinion matrices extracted from forum posts. Experiments with two tasks show that the learned latent factor representation can give good performance on a relation polarity prediction task and improve the performance of a subgroup detection task.

Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song

Research Collection School Of Computing and Information Systems

In this paper, we propose SocioPhone, a novel initiative to build a mobile platform for face-to-face interaction monitoring. Face-to-face interaction, especially conversation, is a fundamental part of everyday life. Interaction-aware applications aimed at facilitating group conversations have been proposed, but have not proliferated yet. Useful contexts to capture and support face-to-face interactions need to be explored more deeply. More important, recognizing delicate conversational contexts with commodity mobile devices requires solving a number of technical challenges. As a first step to address such challenges, we identify useful meta-linguistic contexts of conversation, such as turn-takings, prosodic features, a dominant participant, and pace. …

Demo: Sociophone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion, Youngki Lee, Chulhong Min, Chanyou Hwang, Jaeung Lee, Inseok Hwang, Younghyun Ju, Chungkuk Yoo, Miri Moon, Uichin Lee, Junehwa Song

Research Collection School Of Computing and Information Systems

In this demo, we introduce SocioPhone, a novel initiative toward everyday face-to-face interaction monitoring platform. Among diverse verbal, aural, visual cues expressed during face-to-face interaction, SocioPhone captures diverse meta-linguistic information from conversations and provides interaction-aware applications on-the-fly. Undoubtedly, conversations are a key channel for face-to-face interaction. Specifically, monitoring conversational turns, i.e., alternation of different speakers (including none speaking), is the first crucial step to derive diverse interesting aspects of conversations, e.g., who is talking right now, how long and often one talks, how quickly one responds to another, and so on. In this demo, we will show the core technique …

A Latent Variable Model For Viewpoint Discovery From Threaded Forum Posts, Minghui Qiu, Jing Jiang

Research Collection School Of Computing and Information Systems

Threaded discussion forums provide an important social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or stances on hot issues from forum threads is an important and useful task. In this paper, we propose a novel latent variable model for viewpoint discovery from threaded forum posts. Our model is a principled generative latent variable model which captures three important factors: viewpoint specific topic preference, user identity and user interactions. Evaluation results show that our model clearly outperforms a number of baseline models in terms of both clustering …

Real Time Event Detection In Twitter, Xun Wang, Feida Zhu, Jing Jiang, Sujian Li

Research Collection School Of Computing and Information Systems

Event detection has been an important task for a long time. When it comes to Twitter, new problems are presented. Twitter data is a huge temporal data flow with much noise and various kinds of topics. Traditional sophisticated methods with a high computational complexity aren’t designed to handle such data flow efficiently. In this paper, we propose a mixture Gaussian model for bursty word extraction in Twitter and then employ a novel time-dependent HDP model for new topic detection. Our model can grasp new events, the location and the time an event becomes bursty promptly and accurately. Experiments show the …

Concept Graphs: Applications To Biomedical Text Categorization And Concept Extraction, Said Bleik

Dissertations

As science advances, the underlying literature grows rapidly providing valuable knowledge mines for researchers and practitioners. The text content that makes up these knowledge collections is often unstructured and, thus, extracting relevant or novel information could be nontrivial and costly. In addition, human knowledge and expertise are being transformed into structured digital information in the form of vocabulary databases and ontologies. These knowledge bases hold substantial hierarchical and semantic relationships of common domain concepts. Consequently, automating learning tasks could be reinforced with those knowledge bases through constructing human-like representations of knowledge. This allows developing algorithms that simulate the human reasoning …

Iterative Statistical Verification Of Probabilistic Plans, Colin M. Potts

Lawrence University Honors Projects

Artificial intelligence seeks to create intelligent agents. An agent can be anything: an autopilot, a self-driving car, a robot, a person, or even an anti-virus system. While the current state-of-the-art may not achieve intelligence (a rather dubious thing to quantify) it certainly achieves a sense of autonomy. A key aspect of an autonomous system is its ability to maintain and guarantee safety—defined as avoiding some set of undesired outcomes. The piece of software responsible for this is called a planner, which is essentially an automated problem solver. An advantage computer planners have over humans is their ability to consider and …

Analysis Of Features Composing An Automated Text Readability Formula., Michael Schneider

Undergraduate Honors Theses

In an effort to make reading more accessible, an automated readability formula can help pair readers with material appropriate for their reading level. This study attempts to discover and analyze a set of possible features that may be included in a future automated readability formula. This set is not a definitive list of readability formula features, but rather an overview of current features being study in the Natural Language Processing field.

Data Carving Parser Generation, Benjamin Nathaniel Kelley

Masters Theses, 2010-2019

As our day to day interaction with technology continues to grow, so does the amount of data created through this interaction. The science of digital forensics grew out of the need for specialists to recover, analyze, and interpret this data. When events or actions, either by accident or with criminal intent create, delete or manipulate data, it is the role of a digital forensics analyst to acquire this data and draw conclusions about the discovered facts about who or what is responsible for the event. This thesisidentifies a gap in the research between data analysis and interpretation. Current research and …

The Use Of Relation Valued Attributes In Support Of Fuzzy Data, Larry Ritchie Williams Jr.

Theses and Dissertations

In his paper introducing fuzzy sets, L.A. Zadeh describes the difficulty of assigning some real-world objects to a particular class when the notion of class membership is ambiguous. If exact classification is not obvious, most people approximate using intuition and may reach agreement by placing an object in more than one class. Numbers or ‘degrees of membership’ within these classes are used to provide an approximation that supports this intuitive process. This results in a ‘fuzzy set’. This fuzzy set consists any number of ordered pairs to represent both the class and the class’s degree of membership to provide a …

The Role Of String Similarity Metrics In Ontology Alignment, Michelle Cheatham, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Tim Berners-Lee originally envisioned a much different world wide web than the one we have today - one that computers as well as humans could search for the information they need [3]. There are currently a wide variety of research efforts towards achieving this goal, one of which is ontology alignment.

Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao

Research Collection School Of Computing and Information Systems

Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …

Collocation Error Correction In Web Queries And Text Documents, Alan T. Varghese

Theses, Dissertations and Culminating Projects

Collocations are words in English that occur together frequently. Non-native speakers of English tend to confuse certain terms with other similar terms. This causes one of the terms to be substituted with a term that is not commonly used with the other term. “Powerful tea” is an example of such an odd collocation. In this scenario the more commonly used term is “strong tea”.

This paper proposes an approach called CollOrder to detect such odd collocations in written English. CollOrder also provides suggestions to correct the odd collocate. These suggestions are filtered and ranked as top-k suggestions.

We make use …

Your Love Is Public Now: Questioning The Use Of Personal Information In Authentication, Payas Gupta, Swapna Gottipati, Jing Jiang, Debin Gao

Research Collection School Of Computing and Information Systems

Most social networking platforms protect user's private information by limiting access to it to a small group of members, typically friends of the user, while allowing (virtually) everyone's access to the user's public data. In this paper, we exploit public data available on Facebook to infer users' undisclosed interests on their profile pages. In particular, we infer their undisclosed interests from the public data fetched using Graph APIs provided by Facebook. We demonstrate that simply liking a Facebook page does not corroborate that the user is interested in the page. Instead, we perform sentiment-oriented mining on various attributes of a …

Tower Of Babel: A Crowdsourcing Game Building Sentiment Lexicons For Resource-Scarce Languages, Yoonsung Hong, Haewoon Kwak, Youngmin Baek, Sue. Moon

Research Collection School Of Computing and Information Systems

With the growing amount of textual data produced by online social media today, the demands for sentiment analysis are also rapidly increasing; and, this is true for worldwide. However, non-English languages often lack sentiment lexicons, a core resource in performing sentiment analysis. Our solution, Tower of Babel (ToB), is a language-independent sentiment-lexicon-generating crowdsourcing game. We conducted an experiment with 135 participants to explore the difference between our solution and a conventional manual annotation method. We evaluated ToB in terms of effectiveness, efficiency, and satisfactions. Based on the result of the evaluation, we conclude that sentiment classification via ToB is accurate, …

The Application Of Embodied Conversational Agents For Mentoring African American Stem Doctoral Students, Kinnis Gosha

All Dissertations

This dissertation presents the design, development and short-term evaluation of an embodied conversational agent designed to mentor human users. An embodied conversational agent (ECA) was created and programmed to mentor African American computer science majors on their decision to pursue graduate study in computing. Before constructing the ECA, previous research in the fields of embodied conversational agents, relational agents, mentorship, telementorship and successful mentoring programs and practices for African American graduate students were reviewed. A survey used to find areas of interest of the sample population. Experts were then interviewed to collect information on those areas of interest and a …

Document Collection Visualization And Clustering Using An Atom Metaphor For Display And Interaction, Khanh V. Nghi

Theses and Dissertations - UTB/UTPA

Visual Data Mining have proven to be of high value in exploratory data analysis and data mining because it provides an intuitive feedback on data analysis and support decision-making activities. Several visualization techniques have been developed for cluster discovery such as Grand Tour, HD-Eye, Star Coordinates, etc. They are very useful tool which are visualized in 2D or 3D; however, they have not simple for users who are not trained. This thesis proposes a new approach to build a 3D clustering visualization system for document clustering by using k-mean algorithm. A cluster will be represented by a neutron (centroid) and …

Why Individuals Seek Diverse Opinions (Or Why They Don't), Jisun An, Daniele Quercia, Jon Crowcroft

Research Collection School Of Computing and Information Systems

Fact checking has been hard enough to do in traditional settings, but, as news consumption is moving on the Internet and sources multiply, it is almost unmanageable. To solve this problem, researchers have created applications that expose people to diverse opinions and, as a result, expose them to balanced information. The wisdom of this solution is, however, placed in doubt by this paper. Survey responses of 60 individuals in the UK and South Korea and in-depth structured interviews of 10 respondents suggest that exposure to diverse opinions would not always work. That is partly because not all individuals equally value …

Impact Of Multimedia In Sina Weibo: Popularity And Life Span, Xun Zhao, Feida Zhu, Weining Qian, Aoying Zhou

Research Collection School Of Computing and Information Systems

Multimedia contents such as images and videos are widely used in social network sites nowadays. Sina Weibo, a Chinese microblogging service, is one of the first microblog platforms to incorporate multimedia content sharing features. This work provides statistical analysis on how multimedia contents are produced, consumed, and propagated in Sina Weibo. Based on 230 million tweets and 1.8 million user profiles in Sina Weibo, we study the impact of multimedia contents on the popularity of both users and tweets as well as tweet life span. Our preliminary study shows that multimedia tweets dominant pure text ones in Sina Weibo. Multimedia …

Retweeting: An Act Of Viral Users, Susceptible Users, Or Viral Topics?, Tuan-Anh Hoang, Ee Peng Lim

Research Collection School Of Computing and Information Systems

When a user retweets, there are three behavioral factors that cause the actions. They are the topic virality, user virality and user susceptibility. Topic virality captures the degree to which a topic attracts retweets by users. For each topic, user virality and susceptibility refer to the likelihood that a user attracts retweets and performs retweeting respectively. To model a set of observed retweet data as a result of these three topic specific factors, we first represent the retweets as a three-dimensional tensor of the tweet authors, their followers, and the tweets themselves. We then propose the V 2S model, a …

Context-Driven Image Annotation Using Imagenet, George E. Noel, Gilbert L. Peterson

Faculty Publications

Image annotation research has demonstrated success on test data for focused domains. Unfortunately, extending these techniques to the broader topics found in real world data often results in poor performance. This paper proposes a novel approach that leverages WordNet and ImageNet capabilities to annotate images based on local text and image features. Signatures generated from ImageNet images based on WordNet synonymous sets are compared using Earth Mover's Distance against the query image and used to rank order surrounding words by relevancy. The results demonstrate effective image annotation, producing higher accuracy and improved specificity over the ALIPR image annotation system. Abstract …

Script-Based Story Matching For Cyberbullying Prevention, Jamie Macbeth, Hanna Adeyema, Henry Lieberman, Christopher Fry

Computer Science: Faculty Publications

While the Internet and social media help keep today’s youth better connected to their friends, family, and community, the same media are also the form of expression for an array of harmful social behaviors, such as cyberbullying and cyber-harassment. In this paper we present work in progress to develop intelligent interfaces to social media that use commonsense knowledge bases and automated narrative analyses of text communications between users to trigger selective interventions and prevent negative outcomes. While other approaches seek merely to classify the overall topic of the text, we try to match stories to finer-grained “scripts” that represent stereotypical …

Probabilistic Explicit Topic Modeling, Joshua Aaron Hansen

Theses and Dissertations

Latent Dirichlet Allocation (LDA) is widely used for automatic discovery of latent topics in document corpora. However, output from analysis using an LDA topic model suffers from a lack of identifiability between topics not only across corpora, but across runs of the algorithm. The output is also isolated from enriching information from knowledge sources such as Wikipedia and is difficult for humans to interpret due to a lack of meaningful topic labels. This thesis introduces two methods for probabilistic explicit topic modeling that address these issues: Latent Dirichlet Allocation with Static Topic-Word Distributions (LDA-STWD), and Explicit Dirichlet Allocation (EDA). LDA-STWD …

Predicting Product Review Helpfulness Using Machine Learning And Specialized Classification Models, Scott Bolter

Master's Projects

In this paper we focus on automatically classifying product reviews as either helpful or unhelpful using machine learning techniques, namely, SVM classifiers. Using LIBSVM and a set of Amazon product reviews from 25 product categories, we train models for each category to determine if a review will be helpful or unhelpful. Previous work has focused on training one classifier for all reviews in the data set, but we hypothesize that a distinct model for each of the 25 product types available in the review dataset will improve the accuracy of classification. ! Furthermore, we develop a framework to inform authors …