Physical Sciences and Mathematics Commons^™

The Transition Experiences Of International Graduate Students In Clark University School Of Professional Studies, Xuesong Huang, Mingyang Lian, Dang Trung, Jay Sheth, Yuwei Yang, Irina Klimenko

School of Professional Studies

In the last decade, the School of Professional Studies at Clark University has witnessed a sharp increase in international students. More and more international students in the millennial generation have entered the School of Professional Studies pursuing one of the two-year graduate programs: Master of Science in Professional Studies, Master of Science in Public Administration, and Master of Science in Information Technology. In the past, working adult student dominant the program. These students already had a career outside the classrooms before them came to study. The millennial international students have generated new adjustment problems. Some of the transition issues of …

‘Tweetboard’ – A Case Study Of Developing A Micro-Blogging Platform For Higher Education, Shao Cheh Joyce Hsu, Gan, Benjamin, Jin Lee, Shu Hui Sheryl Lim, Xie Yan Jeremy Lim, Thomas Menkhoff, Si Xian Sherman Tan, Charles Jason Woodard, Qiu Cheng Yap

Research Collection School Of Computing and Information Systems

This paper reports experiences made at an Asian university in developing a social media platform based on Twitter in the context of a final year capstone project where information systems management students get an opportunity to solve ‘a real-world problem for a real client’. In this case study, the challenge was provided by a faculty member’s request for an interactive social media application which engages less outspoken students in class via a social medium they are familiar with: Twitter. We reconstruct the project’s evolution; describe the main features of the application called ‘TweetBoard’ and share lessons learned in developing a …

From Footprint To Evidence: An Exploratory Study Of Mining Social Data For Credit Scoring, Guangming Guo, Feida Zhu, Enhong Chen, Qi Liu, Le Wu, Chu Guan

Research Collection School Of Computing and Information Systems

With the booming popularity of online social networks like Twitter and Weibo, online user footprints are accumulating rapidly on the social web. Simultaneously, the question of how to leverage the large-scale user-generated social media data for personal credit scoring comes into the sight of both researchers and practitioners. It has also become a topic of great importance and growing interest in the P2P lending industry. However, compared with traditional financial data, heterogeneous social data presents both opportunities and challenges for personal credit scoring. In this article, we seek a deep understanding of how to learn users’ credit labels from social …

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

Domain Identification For Intention Posts On Online Social Media, Thai Le Luong, Quoc Tuan Truong, Hai-Trieu Dang, Xuan Hieu Phan

Research Collection School Of Computing and Information Systems

Today, more and more Internet users are willing to share their feeling, activities, and even their intention about what they plan to do on online social media. We can easily see posts like "I plan to buy an apartment this year", or "We are looking for a tour for 3 people to Nha Trang" on online forums or social networks. Recognizing those user intents on online social media is really useful for targeted advertising. However fully understanding user intents is a complicated and challenging process which includes three major stages: user intent filtering, intent domain identification, and intent parsing and …

On The Promotion Of The Social Web Intelligence, Taraneh Khazaei

Electronic Thesis and Dissertation Repository

Given the ever-growing information generated through various online social outlets, analytical research on social media has intensified in the past few years from all walks of life. In particular, works on social Web intelligence foster and benefit from the wisdom of the crowds and attempt to derive actionable information from such data. In the form of collective intelligence, crowds gather together and contribute to solving problems that may be difficult or impossible to solve by individuals and single computers. In addition, the consumer insight revealed from social footprints can be leveraged to build powerful business intelligence tools, enabling efficient and …

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 …

Media Reinvented, Geoff Tan

Asian Management Insights

The brave new world of digital media.

Tracking Virality And Susceptibility In Social Media, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

In social media, the magnitude of information propagation hinges on the virality and susceptibility of users spreading and receiving the information respectively, as well as the virality of information items. These users' and items' behavioral factors evolve dynamically at the same time interacting with one another. Previous works however measure the factors statically and independently in a restricted case: each user has only a single adoption on each item, and/or users' exposure to items are observable. In this work, we investigate the inter-relationship among the factors and users' multiple adoptions on items to propose both new static and temporal models …

A Statistical Approach To Characterize And Detect Degradation Within The Barabasi-Albert Network, Mohd-Fairul Mohd-Zaid

Theses and Dissertations

Social Network Analysis (SNA) is widely used by the intelligence community when analyzing the relationships between individuals within groups of interest. Hence, any tools that can be quantitatively shown to help improve the analyses are advantageous for the intelligence community. To date, there have been no methods developed to characterize a real world network as a Barabasi-Albert network which is a type of network with properties contained in many real-world networks. In this research, two newly developed statistical tests using the degree distribution and the L-moments of the degree distribution are proposed with application to classifying networks and detecting degradation …

When A Friend Online Is More Than A Friend In Life: Intimate Relationship Prediction In Microblogs, Yunshi Lan, Mengqi Zhang, Feida Zhu, Jing Jiang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Microblogging services such as Twitter and Sina Weibo have been an important, if not indespensible, platform for people around the world to connect to one another. The rich content and user interactions on these platforms reveal insightful information about each user that are valuable for various real-life applications. In particular, user offline relationships, especially those intimate ones such as family members and couples, offer distinctive value for many business and social settings. In this study, we focus on using Sina Weibo to discover intimate offline relationships among users. The problem is uniquely interesting and challenging due to the difficulty in …

Efficient Community Maintenance For Dynamic Social Networks, Hongchao Qin, Ye Yuan, Feida Zhu, Guoren Wang

Research Collection School Of Computing and Information Systems

Community detection plays an important role in a wide range of research topics for social networks including personalized recommendation services and information dissemination. The highly dynamic nature of social platforms, and accordingly the constant updates to the underlying network, all present a serious challenge for efficient maintenance of the identified communities. How to avoid computing from scratch the whole community detection result in face of every update, which constitutes small changes more often than not. To solve this problem, we propose a novel and efficient algorithm to maintain the communities in dynamic social networks by identifying and updating only those …

Microblogging Content Propagation Modeling Using Topic-Specific Behavioral Factors, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

When a microblogging user adopts some content propagated to her, we can attribute that to three behavioral factors, namely, topic virality, user virality, and user susceptibility. Topic virality measures the degree to which a topic attracts propagations by users. User virality and susceptibility refer to the ability of a user to propagate content to other users, and the propensity of a user adopting content propagated to her, respectively. In this paper, we study the problem of mining these behavioral factors specific to topics from microblogging content propagation data. We first construct a three dimensional tensor for representing the propagation instances. …

Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang

Research Collection School Of Computing and Information Systems

Twitter has become one of largest social networks for users to broad-cast burst topics. Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. There have been many studies on how to detect influential users. However, traditional influential users detection approaches have largely ignored influential users in user community. In this paper, we investigate the problem of detecting community pacemakers. Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic. To solve this problem, we present DCPBT, a framework that can …

Passive Visual Analytics Of Social Media Data For Detection Of Unusual Events, Kush Rustagi, Junghoon Chae

The Summer Undergraduate Research Fellowship (SURF) Symposium

Now that social media sites have gained substantial traction, huge amounts of un-analyzed valuable data are being generated. Posts containing images and text have spatiotemporal data attached as well, having immense value for increasing situational awareness of local events, providing insights for investigations and understanding the extent of incidents, their severity, and consequences, as well as their time-evolving nature. However, the large volume of unstructured social media data hinders exploration and examination. To analyze such social media data, the S.M.A.R.T system provides the analyst with an interactive visual spatiotemporal analysis and spatial decision support environment that assists in evacuation planning …

Extending The Network: The Influence Of Offline Friendship On Twitter Network, Young Soo Kim, Kyungsub Stephen Choi, Felicia Natali

Research Collection School Of Computing and Information Systems

Twitter effectively provides a communication platform that allows users to strengthen or augment relationships with their close ones. It is a common scene to see groups of people in continuing group communication from offline to online using tools such as Twitter. Furthermore, it is also possible to meet new friends via online encounter. Under these circumstances, there would be friends who are both offline and online, or only in online. Many of earlier Twitter network studies focused on the network effects’ direction going from online to offline network. This paper explores the opposite direction, going from offline to online network. …

Profiling Social Media Users With Selective Self-Disclosure Behavior, Wei Gong

Dissertations and Theses Collection

Social media has become a popular platform for millions of users to share activities and thoughts. Many applications are now tapping on social media to disseminate information (e.g., news), to promote products (e.g., advertisements), to manage customer relationship (e.g., customer feedback), and to source for investment (e.g., crowdfunding). Many of these applications require user profile knowledge to select the target social media users or to personalize messages to users. Social media user profiling is a task of constructing user profiles such as demographical labels, interests, and opinions, etc., using social media data. Among the social media user profiling research works, …

Latent Semantic Indexing In The Discovery Of Cyber-Bullying In Online Text, Jacob L. Bigelow

Computer Science Summer Fellows

The rise in the use of social media and particularly the rise of adolescent use has led to a new means of bullying. Cyber-bullying has proven consequential to youth internet users causing a need for a response. In order to effectively stop this problem we need a verified method of detecting cyber-bullying in online text; we aim to find that method. For this project we look at thirteen thousand labeled posts from Formspring and create a bank of words used in the posts. First the posts are cleaned up by taking out punctuation, normalizing emoticons, and removing high and low …

Detection Of Cyberbullying In Sms Messaging, Bryan W. Bradley

Computer Science Summer Fellows

Cyberbullying is a type of bullying that uses technology such as cell phones to harass or malign another person. To detect acts of cyberbullying, we are developing an algorithm that will detect cyberbullying in SMS (text) messages. Over 80,000 text messages have been collected by software installed on cell phones carried by participants in our study. This paper describes the development of the algorithm to detect cyberbullying messages, using the cell phone data collected previously. The algorithm works by first separating the messages into conversations in an automated way. The algorithm then analyzes the conversations and scores the severity and …

Can Instagram Posts Help Characterize Urban Micro-Events?, Kasthuri Jayarajah, Archan Misra

Research Collection School Of Computing and Information Systems

Social media content, from platforms such as Twitter and Foursquare, has enabled an exciting new field of social sensing, where participatory content generated by users has been used to identify unexpected emerging or trending events. In contrast to such text-based channels, we focus on image-sharing social applications (specifically Instagram), and investigate how such urban social sensing can leverage upon the additional multi-modal, multimedia content. Given the significantly higher fraction of geotagged content on Instagram, we aim to use such channels to go beyond identification of long-lived events (e.g., a marathon) to achieve finer-grained characterization of multiple micro-events (e.g., a person …

Magnopark, Smart Parking Detection Based On Cellphone Magnetic Sensor, Maryam Arab

Computer Science Theses & Dissertations

We introduce a solution that uses the availability of heavy crowds and their smart devices, to gain more result as to where potential parking is possible. By leveraging the raw magnetometer, gyroscope, and accelerometer data, we are able to detect parking spots through the natural movement exerted by the walking pedestrians on the sidewalks beside the streets. Dating back as far as 2013, a very large portion of pedestrians composing the crowds on the sidewalk, possessed at least one smart device in their hand or pocket14]. It is this statistic that fuels our application, in which we depend on crowds …

User Behavior Mining In Microblogging, Tuan Anh Hoang

Dissertations and Theses Collection (Open Access)

This dissertation addresses the modeling of factors concerning microblogging users' content and behavior. We focus on two sets of factors. The first set includes behavioral factors of users and content items driving content propagation in microblogging. The second set consists of latent topics and communities of users as the users are engaged in content generation and behavior adoptions. These two sets of factors are extremely important in many applications, e.g., network monitoring and recommender systems. In the first part of this dissertation, we identify user virality, user susceptibility, and content virality as three behavioral factors that affect users' behaviors in …

Collective Rumor Correction On The Death Hoax Of A Political Figure In Social Media, Alton Y. K. Chua, Sin-Mei Cheah, Dion Hoe-Lian Goh, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Conversations on social media networks that discuss a crisis incident as it unfolds have become a norm in recent years. Left to its own devices, such conversations could quickly degenerate into rumor mills. Little research has thus far examined the correction of rumors on social media. Using the third person effect as a theoretical underpinning, we developed a model of collective rumor correction on social media based on an incident surrounding the death hoax of a political figure. Tweets from Twitter were collected and analyzed for the period when a spike of circulating rumors speculating the demise of Singapore's first …

Cest: City Event Summarization Using Twitter, Deepa Mallela

Computer Science Graduate Projects and Theses

Twitter, with 288 million active users, has become the most popular platform for continuous real-time discussions. This leads to huge amounts of information related to the real-world, which has attracted researchers from both academia and industry. Event detection on Twitter has gained attention as one of the most popular domains of interest within the research community. Unfortunately, existing event detection methodologies have yet to fully explore Twitter metadata and instead rely solely on identifying events based on prior information or focus on events that belong to specific categories. Given the heavy volume of tweets that discuss events, summarization techniques can …

Information Technology Proposal For The Town Of Spencer, Vijay Basava, Corey Kenyon, Mahdi Soltani

School of Professional Studies

The Town of Spencer came to us looking for a plan to build and maintain their own personal fiber network for connection between departments and to improve data security for important information. After assessing the existing landscape and determining the various paths forward, we created network diagrams and plans for the movement forward of this project.

After assessing a variety of plans, we found that a full single-mode fiber network would be the best system for the implementation in Spencer. While it was the highest cost, it also scored the highest in our assessment.

Charlton Fire Department Resident Expectations: Survey And Analysis, Natalie Omary, Jingxin Wen, Junchen Chen, Denis Kornev

School of Professional Studies

The Town of Charlton is located in the heart of the Massachusetts with a resident population of just under 14,000 people. The Charlton Fire Department serves the town for needs related to fire fighting, fire prevention, burning permits and inspection services along with emergency medical services. The Department has requested the assistance of the Clark University COPACE Capstone students in creating and conducting survey in order to get a sense of what the resident of the town know about the fire department and to better gauge their expectations about what the department can provide for them. The survey was formulated …

Cybersecurity Awareness Shrewsbury Public Schools, Brittany Crompton, David Thompson, Manuel Reyes, Xueyan Zhao, Xueke Zou

School of Professional Studies

In the 21st Century, technology reaches every aspect of our lives. As “digital citizens” we must be aware of the dangers both to our technological equipment and our personal information stored, transmitted, and processed on this equipment. The Cybersecurity Awareness curriculum developed for the Shrewsbury Public School district is designed to meet this need, as well as foster an interest in technology and ethical computer use.

Analysis Of The Point Of Sales System At Tower Hill Botanical Garden And Suggested Courses Of Action, Brian Dunn, Keerthi Bandi, Chantal Kopwa Epse Kassa, F.N.U Shelly

School of Professional Studies

As Tower Hill Botanic Garden continues to improve on its operations and enhance the experience of its visitors and members, they are on a quest for a new Point-Of-Sale (POS) system that not only works with its existing hardware and interface with Raiser’s Edge, a smartcloud fundraising and relationship management software central to the garden’s operations but also, have a restaurant module and the capability of operating both in a wireless and hard-wired environment.