Physical Sciences and Mathematics Commons^™

The Paradox Of Social Media Security: A Study Of It Students’ Perceptions Versus Behavior On Using Facebook, Zahra Y. Alqubaiti

Master of Science in Information Technology Theses

Social media plays an essential role in the modern society, enabling people to be better connected to each other and creating new opportunities for businesses. At the same time, social networking sites have become major targets for cyber-security attacks due to their massive user base. Many studies investigated the security vulnerabilities and privacy issues of social networking sites and made recommendations on how to mitigate security risks. Users are an integral part of any security mix. In this thesis, we explore the relationship between users’ security perceptions and their actual behavior on social networking sites. Protection motivation theory (PMT), initially …

Visual Analytics Of Location-Based Social Networks For Decision Support, Junghoon Chae

Open Access Dissertations

Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on …

Spiteful, One-Off, And Kind: Predicting Customer Feedback Behavior On Twitter, Agus Sulistya, Abhishek Sharma, David Lo

Research Collection School Of Computing and Information Systems

Social media provides a convenient way for customers to express their feedback to companies. Identifying different types of customers based on their feedback behavior can help companies to maintain their customers. In this paper, we use a machine learning approach to predict a customer’s feedback behavior based on her first feedback tweet. First, we identify a few categories of customers based on their feedback frequency and the sentiment of the feedback. We identify three main categories: spiteful, one-off, and kind. Next, we build a model to predict the category of a customer given her first feedback. We use profile and …

On Profiling Bots In Social Media, Richard J. Oentaryo, Arinto Murdopo, Philips K. Prasetyo, Ee Peng Lim

Research Collection School Of Computing and Information Systems

The popularity of social media platforms such as Twitter has led to the proliferation of automated bots, creating both opportunities and challenges in information dissemination, user engagements, and quality of services. Past works on profiling bots had been focused largely on malicious bots, with the assumption that these bots should be removed. In this work, however, we find many bots that are benign, and propose a new, broader categorization of bots based on their behaviors. This includes broadcast, consumption, and spam bots. To facilitate comprehensive analyses of bots and how they compare to human accounts, we develop a systematic profiling …

Cyberspace: A Venue For Terrorism, David Bieda, Leila Halawi

Leila A. Halawi

This paper discusses how cyberspace has become a venue for terrorists groups for recruiting and proliferating propaganda and terrorism. Moreover, this study explores how the low cost Internet infrastructure and social media sites (such as Facebook, Twitter, and YouTube) have contributed to their networking and operations due to the convenience, in terms of availability, accessibility, message redundancy, ease of use, and the inability to censor content. Concepts such as cyber-weapons, cyber-attacks, cyber-war, and cyber-terrorism are presented and explored to assess how terrorist groups are exploiting cyberspace.

Behavior Analysis In Social Networks: Challenges, Technologies, And Trends, Meng Wang, Ee-Peng Lim, Lei Li, Mehmet Orgun

Research Collection School Of Computing and Information Systems

The research on social networks has advanced significantly, which can be attributed to the prevalence of the online social websites and instant messaging systems as well as the popularity of mobile apps that support easy access to online social networks. These social networks are usually characterized by the complex network structures and rich contextual information. They now become the key platforms for, among others, content dissemination, professional networking, recommendation, alerting, and political campaigns. As online social network users perform activities on the social networks, they leave data traces of human behavior which allow the latter to be studied at scale. …

Automatically Characterizing Product And Process Incentives In Collective Intelligence, Allen Brockhurst Lavoie

McKelvey School of Engineering Theses & Dissertations

Social media facilitate interaction and information dissemination among an unprecedented number of participants. Why do users contribute, and why do they contribute to a specific venue? Does the information they receive cover all relevant points of view, or is it biased? The substantial and increasing importance of online communication makes these questions more pressing, but also puts answers within reach of automated methods. I investigate scalable algorithms for understanding two classes of incentives which arise in collective intelligence processes. Product incentives exist when contributors have a stake in the information delivered to other users. I investigate product-relevant user behavior changes, …

#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …

Social Customer Relationship Management In Higher Education, Victorian A. Farnsworth

Open Access Theses

Customer Relationship Management is a concept that has become a requirement for any successful entity to attract and retain desired constituents. It is a set of processes and tools that help track, analyze, and act upon customer related data. Over the last decade, the toolsets have evolved to include social media as another source of information and connection. Nowhere is this information and connection more important than in higher education where globalization and tighter budgets have created a competitive market. This research evaluated the use of this most recent social toolset and its effectiveness in a higher education institution, all …

A Business Zone Recommender System Based On Facebook And Urban Planning Data, Jovian Lin, Richard Jayadi Oentaryo, Ee Peng Lim, Casey Vu, Adrian Wei Liang Vu, Philips Kokoh And Prasetyo

Research Collection School Of Computing and Information Systems

We present ZoneRec—a zone recommendation system for physical businesses in an urban city,which uses both public business data from Facebook and urban planning data. The systemconsists of machine learning algorithms that take in a business’ metadata and outputs a list ofrecommended zones to establish the business in. We evaluate our system using data of foodbusinesses in Singapore and assess the contribution of different feature groups to therecommendation quality.

Empirical Analysis Of Socio-Cognitive Factors Affecting Security Behaviors And Practices Of Smartphone Users, Joseph P. Simpson

CCE Theses and Dissertations

The overall security posture of information systems (IS) depends on the behaviors of the IS users. Several studies have shown that users are the greatest vulnerability to IS security. The proliferation of smartphones is introducing an entirely new set of risks, threats, and vulnerabilities. Smartphone devices amplify this data exposure problem by enabling instantaneous transmission and storage of personally identifiable information (PII) by smartphone users, which is becoming a major security risk. Moreover, companies are also capitalizing on the availability and powerful computing capabilities of these smartphone devices and developing a bring-your-own-device (BYOD) program, which makes companies susceptible to divulgence …

Harnessing The Power Of Text Mining For The Detection Of Abusive Content In Social Media, Hao Chen, Susan Mckeever, Sarah Jane Delany

Conference papers

Abstract The issues of cyberbullying and online harassment have gained considerable coverage in the last number of years. Social media providers need to be able to detect abusive content both accurately and efficiently in order to protect their users. Our aim is to investigate the application of core text mining techniques for the automatic detection of abusive content across a range of social media sources include blogs, forums, media-sharing, Q&A and chat - using datasets from Twitter, YouTube, MySpace, Kongregate, Formspring and Slashdot. Using supervised machine learning, we compare alternative text representations and dimension reduction approaches, including feature selection and …

The Impact Of Information Technology On Patient Engagement And Health Behavior Change: A Systematic Review Of The Literature, Suhila Sawesi, Mohamed Rashrash, Kanitha Phalakornkule, Janet S. Carpenter, Josette F. Jones

Pharmacy Faculty Articles and Research

Background: Advancements in information technology (IT) and its increasingly ubiquitous nature expand the ability to engage patients in the health care process and motivate health behavior change.

Objective: Our aim was to systematically review the (1) impact of IT platforms used to promote patients’ engagement and to effect change in health behaviors and health outcomes, (2) behavior theories or models applied as bases for developing these interventions and their impact on health outcomes, (3) different ways of measuring health outcomes, (4) usability, feasibility, and acceptability of these technologies among patients, and (5) challenges and research directions for implementing …