Communication Technology and New Media Commons^™

Rasp-Qs: Efficient And Confidential Query Services In The Cloud, Zohreh S. Alavi, Lu Zhou, James L. Powers, Keke Chen

Kno.e.sis Publications

Hosting data query services in public clouds is an attractive solution for its great scalability and significant cost savings. However, data owners also have concerns on data privacy due to the lost control of the infrastructure. This demonstration shows a prototype for efficient and confidential range/kNN query services built on top of the random space perturbation (RASP) method. The RASP approach provides a privacy guarantee practical to the setting of cloudbased computing, while enabling much faster query processing compared to the encryption-based approach. This demonstration will allow users to more intuitively understand the technical merits of the RASP approach via …

A Crowdsourcing Approach To Identify Common Method Bias And Self-Representation, Margeret A. Hall, Simon Caton

Interdisciplinary Informatics Faculty Proceedings & Presentations

Pertinent questions on the measurement of social indicators are: the verification of data gained online (e.g., controlling for self-representation on social networks), and appropriate uses in community management and policy-making. Across platforms like Facebook, LinkedIn, Twitter, and blogging services, users (sub)consciously represent themselves in a way which is appropriate for their intended audience (Qui et al., 2012; Zhao et al., 2008). However, scholars in the social sciences and computer science have not yet adequately addressed controlling for self-representation, or the propensity to display or censor oneself, in their analyses (Zhao et al., 2008; Das and Kramer, 2013). As such researchers …

Campus Paper Waste, Joshua E. Randall

Journal of Undergraduate Research at Minnesota State University, Mankato

The fall of 2004 at Minnesota State University, a new program called MavPrint was introduced. The user submits a document to be printed at a computer, the expense is deducted from their account, and then their document can be retrieved from any MavPrint station. In years past printing had been free, but seeing how according to Bryan Schneider, the director of Technical Services at Minnesota State University – Mankato, from the year 2003 to the year 2004 the printing costs for the University rose 200 percent, they felt it was time to make a change. MSU students printed out over …

Document Retrieval Using Predication Similarity, Kalpa Gunaratna

Kno.e.sis Publications

Document retrieval has been an important research problem over many years in the information retrieval community. State-of-the-art techniques utilize various methods in matching documents to a given document including keywords, phrases, and annotations. In this paper, we propose a new approach for document retrieval that utilizes predications (subject-predicate-object triples) extracted from the documents. We represent documents as sets of predications. We measure the similarity between predications to compute the similarity between documents. Our approach utilizes the hierarchical information available in ontologies in computing concept-concept similarity, making the approach flexible. Predication-based document similarity is more precise and forms the basis for …

A Novel Web-Based Depth Video Rewind Approach Toward Fall Preventive Interventions In Hospitals, Moein Enayati, Tanvi Banerjee, Mihail Popescu, Marjorie Skubic, Marilyn J. Rantz

Kno.e.sis Publications

Falls in the hospital rooms are considered a huge burden on healthcare costs. They can lead to injuries, extended length of stay, and increase in cost for both the patients and the hospital. It can also lead to emotional trauma for the patients and their families [1]. Having Microsoft Kinects installed in the hospital rooms to capture and process every movement in the room, we deployed our previously developed fall-detection system to detect naturally occurring falls, generate a real-time fall alarm and broadcast it to hospital nurses for immediate intervention. These systems also store a processed and reduced version …

Assisting Coordination During Crisis: A Domain Ontology Based Approach To Infer Resource Needs From Tweets, Shreyansh Bhatt, Hemant Purohit, Andrew J. Hampton, Valerie L. Shalin, Amit P. Sheth, John Flach

Kno.e.sis Publications

Ubiquitous social media during crises provides citizen reports on the situation, needs and supplies. Previous research extracts resource needs directly from the text (e.g. "Power cut to Coney Island and Brighton beach" indicates a power need). This approach assumes that citizens derive and write about specific needs from their observations, properly specified for the emergency response system, an assumption that is not consistent with general conversational behavior. In our study, Twitter messages (tweets) from Hurricane Sandy in 2012 clearly indicate power blackouts, but not their probable implications (e.g. loss of power to hospital life support systems). We use a domain …

Libraries Respond To Mobile Ubiquity: Research And Assessment Of Mobile Device Usage Trends For Academic And Medical Libraries, Megan M. Hurst, Eleanor I. Cook, J. Michael Lindsay, Martha F. Earl

Charleston Library Conference

The authors consider trends in mobile device usage for the Internet as a whole, for EBSCO Discovery Service across all client libraries, and at two specific libraries: Preston Medical Library, serving the University of Tennessee (UT) Graduate School of Medicine and UT Medical Center, and the Joyner Library at East Carolina University, serving students and faculty on the main campus. Librarians at Preston Medical Library conducted a survey to determine which mobile devices, platforms, and apps were used by their patrons in 2012. East Carolina University piloted an iPad and e-reader lending program in 2010–2011. The results of each are …

Active Learning With Efficient Feature Weighting Methods For Improving Data Quality And Classification Accuracy, Justin Martineau, Lu Chen, Doreen Cheng, Amit P. Sheth

Kno.e.sis Publications

Many machine learning datasets are noisy with a substantial number of mislabeled instances. This noise yields sub-optimal classification performance. In this paper we study a large, low quality annotated dataset, created quickly and cheaply using Amazon Mechanical Turk to crowdsource annotations. We describe computationally cheap feature weighting techniques and a novel non-linear distribution spreading algorithm that can be used to iteratively and interactively correcting mislabeled instances to significantly improve annotation quality at low cost. Eight different emotion extraction experiments on Twitter data demonstrate that our approach is just as effective as more computationally expensive techniques. Our techniques save a considerable …

Semantic Modelling Of Smart City Data, Stefan Bischof, Athanasios Karapantelakis, Cosmin-Septimiu Nechifor, Amit P. Sheth, Alessandra Mileo, Payam Barnaghi

Kno.e.sis Publications

Cities present an opportunity for rendering Web of Things-enabled services. According to the World Health Organization, population in cities will double by the middle of this century, while cities deal with increasingly pressing issues such as environmental sustainability, economic growth and citizen mobility. In this paper, we propose a discussion around the need for common semantic descriptions for smart city data to facilitate future services in "smart cities". We present examples of data that can be collected from cities, discuss issues around this data and put forward some preliminary thoughts for creating a semantic description model to describe and help …

Semantics-Enhanced Geoscience Interoperability, Analytics, And Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

We present our research ideas for developing cyberinfrastructure for Geoscience applications developed in the context of the EarthCube initiative, and our NSF-sponsored work on incorporating spatial-temporal-thematic semantics for enhanced querying and feature extraction from sensor data streams.

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 …

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 …

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 …

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 …

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 …

A Look Into The Industry Of Video Games Past, Present, And Yet To Come, Chad Hadzinsky

CMC Senior Theses

Since its inception, the video game industry has been both a new medium for art and innovation as well as a major driving force in the advancements of many technologies. The often overlooked video game industry has turned from a hobby to a multi-billion dollar industry in its short, forty year life. People of all ages and genders across the world are playing video games at a higher clip than ever before. With so many new gamers and emerging technologies, it is an exciting time for the industry. The landscape is constantly changing and successful business models of the past …

[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 …

A Social Dimensional Cyber Threat Model With Formal Concept Analysis And Fact-Proposition Inference, Anup Sharma, Robin Gandhi, Qiuming Zhu, William Mahoney, William Sousan

Computer Science Faculty Publications

Cyberspace has increasingly become a medium to express outrage, conduct protests, take revenge, spread opinions, and stir up issues. Many cyber attacks can be linked to current and historic events in the social, political, economic, and cultural (SPEC) dimensions of human conflicts in the physical world. These SPEC factors are often the root cause of many cyber attacks. Understanding the relationships between past and current SPEC events and cyber attacks can help understand and better prepare people for impending cyber attacks. The focus of this paper is to analyze these attacks in social dimensions and build a threat model based …

Two Formulas For Success In Social Media: Social Learning And Network Effects, Liangfei Qiu, Qian Tang, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

This paper examines social learning and network effects that are particularly important for online videos, considering the limited marketing campaigns of user-generated content. Rather than combining both social learning and network effects under the umbrella of social contagion or peer influence, we develop a theoretical model and empirically identify social learning and network effects separately. Using a unique data set from YouTube, we find that both mechanisms have statistically and economically significant effects on video views, and which mechanism dominates depends on the specific video type.

Automatic Domain Identification For Linked Open Data, Sarasi Lalithsena, Pascal Hitzler, Amit P. Sheth, Prateek Jain

Kno.e.sis Publications

Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose …

Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing …