Computer Sciences Commons^™

Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we argue for expanded research into an area called Socio-Physical Analytics, that focuses on combining the behavioral insight gained from mobile-sensing based monitoring of physical behavior with the inter-personal relationships and preferences deduced from online social networks. We highlight some of the research challenges in combining these heterogeneous data sources and then describe some examples of our ongoing work (based on real-world data being collected at SMU) that illustrate two aspects of socio-physical analytics: (a) how additional demographic and online analytics based attributes can potentially provide better insights into the preferences and behaviors of individuals or groups …

Does Latitude Hurt While Longitude Kills? Geographical And Temporal Separation In A Large Scale Software Development Project, Patrick Wagstrom, Subhajit Datta

Research Collection School Of Computing and Information Systems

Distributed software development allows firms to leverage cost advantages and place work near centers of competency. This distribution comes at a cost -- distributed teams face challenges from differing cultures, skill levels, and a lack of shared working hours. In this paper we examine whether and how geographic and temporal separation in a large scale distributed software development influences developer interactions. We mine the work item trackers for a large commercial software project with a globally distributed development team. We examine both the time to respond and the propensity of individuals to respond and find that when taken together, geographic …

Qr Codes For The Dead, Tamara Kneese

Media Studies

Graveyards are becoming smart spaces, but will today's technology last for eternity?

With Whom To Coordinate, Why And How In Ad-Hoc Social Media Communications During Crisis Response, Hemant Purohit, Shreyansh Bhatt, Andrew Hampton, Valerie L. Shalin, Amit P. Sheth, John M. Flach

Kno.e.sis Publications

During crises affected people, well-wishers, and observers join social media communities to discuss the event. They often share useful information relevant to response coordination, for example, specific resource needs. However, responders face the challenge of massive data overload and lack the time to monitor social media traffic for important information. Analysis shows that only a small number of event related conversations are actionable. Moreover, responders do not know which sources are trustworthy. To address these challenges, response teams may apply manual filtering methods, resulting in limited coverage and quality. We propose a framework and interface for extracting specific resource-related information …

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, …

Mining Contrast Subspaces, Lei Duan, Guanting Tang, Jian Pei, James Bailey, Guozhu Dong, Akiko Campbell, Changjie Tang

Kno.e.sis Publications

In this paper, we tackle a novel problem of mining contrast subspaces. Given a set of multidimensional objects in two classes C₊  and C₋ and a query object o, we want to find top-k subspaces S that maximize the ratio of likelihood of o in C₊  against that in C₋. We demonstrate that this problem has important applications, and at the same time, is very challenging. It even does not allow polynomial time approximation. We present CSMiner, a mining method with various pruning techniques. CSMiner is substantially faster than the baseline method. Our …

Long-Term Multi-Dimensional Interactive Time-Lapse Photography Using Microsoft Kinect, Daniel Mccoy

All Theses

In this thesis, a method is presented for the capture and interactive presentation of long-term multi-dimensional time-lapse photography. Time-lapse capture is commonly used for the observation based study of relatively long term phenomena such as plant growth and weather patterns. In terms of filmic devices, the visual time compression effect is complementary to slow motion and is nearly as prevalent. In this project, commonly available camera and computer equipment is used to capture images autonomously with minimal system supervision. A set of images is established, using long term, short interval continuous capture at a fixed position. Results are presented demonstrating …

Efficient Control Of Assets In A Modern Production Pipeline, Timothy Curtis

All Theses

Managing large collections of assets created in today's CG productions is no easy task. This thesis examines basic production hierarchies and identifies problems that arise without proper workflow and asset control. The possibility of hundreds of assets being created in several workflows each week creates the potential for extraordinary time waste and user error without a system to track and manage the files being produced. It is becoming increasingly necessary to utilize methods during production that enforce naming and storage standards to prevent catastrophic data loss. This thesis presents an implementation of a customized database used to track all of …

Volumetric Cloud Rendering: An Animation Of Clouds, Zhaoxin Ye

All Theses

This paper demonstrates a production workflow for a volumetric-rendering-based short animation about clouds. The animation is based on the concept of a giant fish swimming in the sky from Zhuangzi's philosophical story. The algorithm and implementation for the modeling and rendering of clouds are also presented. A renderer was developed that uses the OpenVDB library for data storage, fast retrieving and grid manipulation. A user-friendly pipeline was also developed for cloud modeling and rendering, which used Python and XML for adjusting rendering parameters. The pipeline includes Maya to build the rough cloud model and Houdini to calculate the interior light …

An Automated Build System For Articulated Characters, James Sledge

All Theses

Rigging is the process of designing and implementing the manipulation architecture for an animated three-dimensional character. Rigs that give the animator the most control tend to be the most difficult to set up and maintain. Due to the linear nature of some elements of rigging, the more complicated a rig, the more time-intensive--and therefore more expensive--to achieve a high quality rig. A solution to complex rig iterability is to automate as much of the process as possible. The topic of this thesis is a framework for modular rigging automation, with a focus on quick and efficient rig iteration. A rigger …

Humanity Hyper-Externalized, Josh Gloe

Honors Capstones

Capstone submitted as a graduation requirement for the BSU Honors Program.

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 …

Hierarchical Interest Graph From Tweets, Pavan Kapanipathi, Prateek Jain, Chitra Venkataramani, Amit P. Sheth

Kno.e.sis Publications

Industry and researchers have identified numerous ways to monetize microblogs for personalization and recommendation. A common challenge across these different works is the identification of user interests. Although techniques have been developed to address this challenge, a flexible approach that spans multiple levels of granularity in user interests has not been forthcoming. In this work, we focus on exploiting hierarchical semantics of concepts to infer richer user interests expressed as a Hierarchical Interest Graph. To create such graphs, we utilize users' tweets to first ground potential user interests to structured background knowledge such as Wikipedia Category Graph. We then adapt …

On Modeling Community Behaviors And Sentiments In Microblogging, Tuan Anh Hoang, William Cohen, Ee Peng Lim

Research Collection School Of Computing and Information Systems

In this paper, we propose the CBS topic model, a probabilistic graphical model, to derive the user communities in microblogging networks based on the sentiments they express on their generated content and behaviors they adopt. As a topic model, CBS can uncover hidden topics and derive user topic distribution. In addition, our model associates topic-specific sentiments and behaviors with each user community. Notably, CBS has a general framework that accommodates multiple types of behaviors simultaneously. Our experiments on two Twitter datasets show that the CBS model can effectively mine the representative behaviors and emotional topics for each community. We also …

Do You Know The Speaker?: An Online Experiment With Authority Messages On Event Websites, Kwan-Hui Lim, Binyan Jiang, Ee Peng Lim, Achananuparp Palakorn

Research Collection School Of Computing and Information Systems

With the widespread adoption of the Web, many companies and organizations have established websites that provide information and support online transactions (e.g., buying products or viewing content). Unfortunately, users have limited attention to spare for interacting with online sites. Hence, it is of utmost importance to design sites that attract user attention and effectively guide users to the product or content items they like. Thus, we propose a novel and scalable experimentation approach to evaluate the effectiveness of online site designs. Our case study focuses on the effects of an authority message on visitors' browsing behavior on workshop and seminar …

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 …

How Many Credit Card Frauds Must We Endure Before Security Improves?, Maritza Martinez

UCF Forum

Yes, it can happen to you…

Inferences & Connections, Tamara Kneese

Media Studies

Data-oriented systems are inferring relationships between people based on genetic material, behavioral patterns (e.g., shared geography imputed by phone carriers), and performed associations (e.g., "friends" online or shared photographs). What responsibilities do entities who collect data that imputes connections have to those who are implicated by association? For example, as DNA and other biological materials are collected outside of medicine (e.g., at point of arrest, by informatics services like 23andme, for scientific inquiry), what rights do relatives (living, dead, and not-yet-born) have? In what contexts is it acceptable to act based on inferred associations and in which contexts is it …

Predicting Human Behavior, Tamara Kneese

Media Studies

Countless highly accurate predictions can be made from trace data, with varying degrees of personal or societal consequence (e.g., search engines predict hospital admission, gaming companies can predict compulsive gambling problems, government agencies predict criminal activity). Predicting human behavior can be both hugely beneficial and deeply problematic depending on the context. What kinds of predictive privacy harms are emerging? And what are the implications for systems of oversight and due process protections? For example, what are the implications for employment, health care and policing when predictive models are involved? How should varied organizations address what they can predict?

Inequalities And Asymmetries, Tamara Kneese

Media Studies

The availability of data is not evenly distributed. Some organizations, agencies, and sectors are better equipped to gather, use, and analyze data than others. If data is transformative, what are the consequences of defense and security agencies having greater capacity to leverage data than, say, education or social services? Financial wherewithal, technical capacity, and political determinants all affect where data is employed. As data and analytics emerge, who benefits and who doesn't, both at the individual level and the institutional level? What about the asymmetries between those who provide the data and those who collect it? How does uneven data …

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.

Comparative Trust Management With Applications: Bayesian Approaches Emphasis, Krishnaprasad Thirunarayan, Pramod Anantharam, Cory Andrew Henson, Amit P. Sheth

Kno.e.sis Publications

Trust relationships occur naturally in many diverse contexts such as collaborative systems, e-commerce, interpersonal interactions, social networks, and semantic sensor web. As agents providing content and services become increasingly removed from the agents that consume them, the issue of robust trust inference and update becomes critical. There is a need to find online substitutes for traditional (direct or face-to-face) cues to derive measures of trust, and create efficient and robust systems for managing trust in order to support decision-making. Unfortunately, there is neither a universal notion of trust that is applicable to all domains nor a clear explication of its …

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 …

Social Correlation In Latent Spaces For Complex Networks, Freddy Chong Tat Chua

Dissertations and Theses Collection (Open Access)

This dissertation addresses the subject of measuring social correlation among users within a complex social network. Social correlation is closely related to the measurement of social influence in social sciences. While social influence focuses on the existence of causal influence among users, we take a computational approach to measure correlation strength among users based on their shared interactions. We call this social correlation. To formally model social correlation, we propose a framework which contains two major parts. The first part is that of representing users behavior in a computationally efficient and accurate manner. For example, social media users perform many …

What Information About Cardiovascular Diseases Do People Search Online?, Ashutosh Sopan Jadhav, Stephen Wu, Amit P. Sheth, Jyotishman Pathak

Kno.e.sis Publications

The objective of this study is to understand the types of health information (health topics) that users search online for Cardiovascular Diseases, by performing categorization of health search queries (from Mayoclinic.com) using UMLS MetaMap based on UMLS concepts and semantic types.

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 …

Alignment And Dataset Identification Of Linked Data In Semantic Web, Kalpa Gunaratna, Sarasi Lalithsena, Amit P. Sheth

Kno.e.sis Publications

The Linked Open Data (LOD) cloud has gained significant attention in the Semantic Web community over the past few years. With rapid expansion in size and diversity, it consists of over 800 interlinked datasets with over 60 billion triples. These datasets encapsulate structured data and knowledge spanning over varied domains such as entertainment, life sciences, publications, geography, and government. Applications can take advantage of this by using the knowledge distributed over the interconnected datasets, which is not realistic to find in a single place elsewhere. However, two of the key obstacles in using the LOD cloud are the limited support …

Industrial Wireless Sensor Networks, Shancang Li, Hongjian Sun, Arumugam Nallanathan, Li Xu, Shanshan Zhao, Qindong Sun

Information Technology & Decision Sciences Faculty Publications

(First Paragraph) Industrial wireless sensor networks (IWSNs) incorporate wireless sensor networks with intelligent industrial systems providing many advantages over existing industrial applications, such as wireless communication, low cost, rapid deployment, self-organization, intelligent controlling, and processing capability. With the proliferation of wireless sensor networks in industrial applications, IWSNs technologies promise to play a significant role in developing more reliable, efficient, stable, flexible, and application-centric industrial systems.

[Introduction To] Identity And Leadership In Virtual Communities: Establishing Credibility And Influence, Dona J. Hickey, Joe Essid

Bookshelf

The presence and ubiquity of the internet continues to transform the way in which we identify ourselves and others both online and offline. The development of virtual communities permits users to create an online identity to interact with and influence one another in ways that vary greatly from face-to-face interaction.

Identity and Leadership in Virtual Communities: Establishing Credibility and Influence explores the notion of establishing an identity online, managing it like a brand, and using it with particular members of a community. Bringing together a range of voices exemplifying how participants in online communities influence one another, this book serves …

Proceedings Of The 1st Annual Cuny Games Festival, Robert O. Duncan, Joe Bisz, Francesco Crocco, Carlos Hernandez, Kathleen Offenholley, Leah Potter, Maura A. Smale, Cuny Games Network

Publications and Research

Proceedings of the CUNY Games Conference, held from January 17-18, 2014, at the CUNY Graduate Center and Borough of Manhattan Community College.

Topics in Game Design - Teaching with Virtual and Augmented Realities - Writing with Games - Breaking the Magic Circle: Games & Real Life - Interactive Game Design (What's Your Game Plan? - Designing Ethical Games - Games and Gender - Gaming English Language and Literature - Game, Narrative, Literacy - Teaching with Games - Games, Storytelling, and Narrative - Games and STEM - Learning by Design - Students as Game Designers - Experiencing Reality in Popular Games …