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Articles 5071 - 5100 of 8481
Full-Text Articles in Computer Sciences
Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra
Demo: Ta$Ker: Campus-Scale Mobile Crowd-Tasking Platform, Nikita Jaiman, Thivya Kandappu, Randy Tandriansyah, Archan Misra
Research Collection School Of Computing and Information Systems
We design and develop TA$Ker, a real-world mobile crowd- sourcing platform to empirically study the worker responses to various task recommendation and selection strategies.
Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun
Condensing Class Diagrams With Minimal Manual Labeling Cost, Xinli Yang, David Lo, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
Traditionally, to better understand the design of a project, developers can reconstruct a class diagram from source code using a reverse engineering technique. However, the raw diagram is often perplexing because there are too many classes in it. Condensing the reverse engineered class diagram into a compact class diagram which contains only the important classes would enhance the understandability of the corresponding project. A number of recent works have proposed several supervised machine learning solutions that can be used for condensing reverse engineered class diagrams given a set of classes that are manually labeled as important or not. However, a …
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Automated Identification Of High Impact Bug Reports Leveraging Imbalanced Learning Strategies, Xinli Yang, David Lo, Qiao Huang, Xin Xia, Jianling Sun
Research Collection School Of Computing and Information Systems
In practice, some bugs have more impact than others and thus deserve more immediate attention. Due to tight schedule and limited human resource, developers may not have enough time to inspect all bugs. Thus, they often concentrate on bugs that are highly impactful. In the literature, high impact bugs are used to refer to the bugs which appear in unexpected time or locations and bring more unexpected effects, or break pre-existing functionalities and destroy the user experience. Unfortunately, identifying high impact bugs from the thousands of bug reports in a bug tracking system is not an easy feat. Thus, an …
Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad
Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad
Research Collection School Of Computing and Information Systems
Over the past decade, the number of mobile phones has increased dramatically, overtaking the world population in October 2014. In developing countries like India and China, mobile subscribers outnumber traditional landline users and account for over 90% of the active population. At the same time, convergence of telephony with the Internet with technologies like VoIP makes it possible to reach a large number of telephone users at a low or no cost via voice calls or SMS (short message service) messages. As a consequence, cybercriminals are abusing the telephony channel to launch attacks, e.g., scams that offer fraudulent services and …
Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor
Cace: Exploiting Behavioral Interactions For Improved Activity Recognition In Multi-Inhabitant Smart Homes, Mohammad Arif Ul Alam, Nirmalya Roy, Archan Misra, Joseph Taylor
Research Collection School Of Computing and Information Systems
We propose CACE (Constraints And Correlations mining Engine) which investigates the challenges of improving the recognition of complex daily activities in multi-inhabitant smart homes, by better exploiting the spatiotemporal relationships across the activities of different individuals. We first propose and develop a loosely-coupled Hierarchical Dynamic Bayesian Network (HDBN), which both (a) captures the hierarchical inference of complex (macro-activity) contexts from lower-layer microactivity context (postural and improved oral gestural context), and (b) embeds the various types of behavioral correlations and constraints (at both micro-and macro-activity contexts) across the individuals. While this model is rich in terms of accuracy, it is computationally …
Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo
Poster: Improving Communication And Communicability With Smarter Use Of Text-Based Messages On Mobile And Wearable Devices, Kenny T. W. Choo
Research Collection School Of Computing and Information Systems
While smartphones have undoubtedly afforded many modern conveniences such as emails, instant messaging or web search, the notifications from smartphones conversely impact our lives through a deluge of information, or stress arising from expectations that we should turn our immediate attention to them (e.g., work emails). In my latest research, we find that the glanceability of smartwatches may provide an opportunity to reduce the perceived disruption from mobile notifications. Text is a common medium for communication in smart devices, the application of natural language processing on text, together with the physical affordances of smartwatches, present exciting opportunities for research to …
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Poster: Air Quality Friendly Route Recommendation System, Savina Singla, Divya Bansal, Archan Misra
Research Collection School Of Computing and Information Systems
To model the overall personal inhalation of hazardous gases through the air (both indoor and outdoor) by an individual, provide air quality friendly route recommendations, thus raising the overall quality of urban movement and living healthy life.
Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi Radhakrishnan, Sharanya Eswaran, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan
Demo: Smartwatch Based Shopping Gesture Recognition, Meeralakshmi Radhakrishnan, Sharanya Eswaran, Sougata Sen, Vigneshwaran Subbaraju, Archan Misra, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
In the current retail segment, the retail store owners are keen to understand the browsing behavior and purchase pattern of the shoppers inside the physical stores. Profiling the behavior of the shopper is key to success for any marketing strategies that can optimize or personalize shopping-related services in real-time. We envision that exploiting the knowledge of real-time behavior of shopper’s in-store activities enables novel applications such as: (a) targeted advertising or recommendations: based on longer term shopper profiles, (b) proactive retail help to assist the shoppers who are confused in choosing between two items, (c) smart reminders that can remind …
Adaptable Key-Policy Attribute-Based Encryption With Time Interval, Siqi Ma, Junzuo Lai, Deng, Robert H., Xuhua Ding
Adaptable Key-Policy Attribute-Based Encryption With Time Interval, Siqi Ma, Junzuo Lai, Deng, Robert H., Xuhua Ding
Research Collection School Of Computing and Information Systems
In this paper, we introduce a new cryptographic primitive: adaptable KP-ABE with time interval (KP-TIABE), which is an extension of key-policy attribute-based encryption (KP-ABE). Adaptable KP-TIABE specifies a decryption time interval for every ciphertext such that the ciphertext can only be decrypted within this time interval. To be more flexible, the decryption time interval associated with a ciphertext can be adjusted on demand by a semi-trusted server. We propose a formal model for adaptable KP-TIABE, present a concrete adaptable KP-TIABE scheme and prove its security under the security model.
Value-Inspired Elderly Care Service Design For Aging-In-Place, Na Liu, Sandeep Purao, Hwee-Pink Tan
Value-Inspired Elderly Care Service Design For Aging-In-Place, Na Liu, Sandeep Purao, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Most current projects aimed at in-home monitoring for the elderly appear to focus on demonstrating technical feasibility and ensuring safety. In doing so, they often overlook the complexity of the interactions between the elderly and the caregivers. This study explores this complexity by adopting a value-inspired design perspective. Following an action design method, we describe the (re)design of the system and service protocol for an elderly-home monitoring effort. The work requires that we leverage the capabilities (of the technological infrastructure system as well as the service providers) to reconcile the values held by the participants (the elderly and their caregivers). …
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
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 …
Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina Singla, Archan Misra
Indoor Location Error-Detection Via Crowdsourced Multi-Dimensional Mobile Data, Savina Singla, Archan Misra
Research Collection School Of Computing and Information Systems
We explore the use of multi-dimensional mobile sensing data as a means of identifying errors in one or more of those data streams. More specifically, we look at the possibility of identifying indoor locations with likely incorrect/stale Wi-Fi fingerprints, by using concurrent readings from Wi-Fi and barometer sensors from a collection of mobile devices. Our key contribution is a novel two-step process: (i) using longitudinal, crowd-sourced readings of (possibly incorrect) Wi-Fi location estimates to statistically estimate the barometer calibration offset of individual mobile devices, and (ii) then, using such offset-corrected barometer readings from devices (that are supposedly collocated) to identify …
Recipient Revocable Identity-Based Broadcast Encryption: How To Revoke Some Recipients In Ibbe Without Knowledge Of The Plaintext, Willy Susilo, Guomin Yang, Rongmao Chen, Yi Mu, Fuchun Guo, Yang-Wai Chow
Recipient Revocable Identity-Based Broadcast Encryption: How To Revoke Some Recipients In Ibbe Without Knowledge Of The Plaintext, Willy Susilo, Guomin Yang, Rongmao Chen, Yi Mu, Fuchun Guo, Yang-Wai Chow
Research Collection School Of Computing and Information Systems
In this paper, we present the notion of recipient-revocable identity-based broadcast encryption scheme. In this notion, a content provider will produce encrypted content and send them to a third party (which is a broadcaster). This third party will be able to revoke some identities from the ciphertext. We present a security model to capture these requirements, as well as a concrete construction. The ciphertext consists of k + 3 group elements, assuming that the maximum number of revocation identities is k. That is, the ciphertext size is linear in the maximal size of R, where R is the revocation identity …
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Cdrep: Automatic Repair Of Cryptographic-Misuses In Android Applications, Siqi Ma, David Lo, Teng Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cryptography is increasingly being used in mobile applications to provide various security services; from user authentication, data privacy, to secure communications. However, there are plenty of mistakes that developers could accidentally make when using cryptography in their mobile apps and such mistakes can lead to a false sense of security. Recent research efforts indeed show that a significant portion of mobile apps in both Android and iOS platforms misused cryptographic APIs. In this paper, we present CDRep, a tool for automatically repairing cryptographic misuse defects in Android apps. We classify such defects into seven types and manually assemble the corresponding …
Qcri At Semeval-2016 Task 4: Probabilistic Methods For Binary And Ordinal Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani
Qcri At Semeval-2016 Task 4: Probabilistic Methods For Binary And Ordinal Quantification, Giovanni Da San Martino, Wei Gao, Fabrizio Sebastiani
Research Collection School Of Computing and Information Systems
. (2016). n. In , pages 58—63, San Diego, California, USA. Association for Computational Linguistics. (1st place in sub-task E of Sentiment Analysis in Twitter)
Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah
Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …
Smart Living For Elderly: Design And Human-Computer Interaction Considerations, Ranjana Sharma, Fiona Fui-Hoon Nah, Kavya Sharma, Teja S. Katta, Natalie Pang, Alvin Yong
Smart Living For Elderly: Design And Human-Computer Interaction Considerations, Ranjana Sharma, Fiona Fui-Hoon Nah, Kavya Sharma, Teja S. Katta, Natalie Pang, Alvin Yong
Research Collection School Of Computing and Information Systems
To address aging challenges, we examine the concept of smart living and its applications for the elderly. Smart living refers to improving quality of life by transforming environments to become more intelligent and adaptable to users. In this paper, we discuss how smart living applications can help to address the needs of the elderly, as well as the design and human-computer interaction considerations for such applications.
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
The Social Side Of Software Platform Ecosystems, Cleidson R. B. Da Souza, Fernando Figueira Filho, Müller Miranda, Renato Pina Ferreira, Christoph Treude, Leif Singer
Research Collection School Of Computing and Information Systems
Software ecosystems as a paradigm for large-scale software development encompass a complex mix of technical, business, and social aspects. While significant research has been conducted to understand both the technical and business aspects, the social aspects of software ecosystems are less well understood. To close this gap, this paper presents the results of an empirical study aimed at understanding the influence of social aspects on developers’ participation in software ecosystems. We conducted 25 interviews with mobile software developers and an online survey with 83 respondents from the mobile software development community. Our results point out a complex social system based …
An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan
An Autonomous Agent For Learning Spatiotemporal Models Of Human Daily Activities, Shan Gao, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Activities of Daily Living (ADLs) refer to activities performed by individuals on a daily basis. As ADLs are indicatives of a person’s habits, lifestyle, and well being, learning the knowledge of people’s ADL routine has great values in the healthcare and consumer domains. In this paper, we propose an autonomous agent, named Agent for Spatia-Temporal Activity Pattern Modeling (ASTAPM), being able to learn spatial and temporal patterns of human ADLs. ASTAPM utilises a self-organizing neural network model named Spatiotemporal - Adaptive Resonance Theory (ST-ART). ST-ART is capable of integrating multimodal contextual information, involving the time and space, wherein the ADL …
Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw
Euclidean Co-Embedding Of Ordinal Data For Multi-Type Visualization, Dung D. Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Embedding deals with reducing the high-dimensional representation of data into a low-dimensional representation. Previous work mostly focuses on preserving similarities among objects. Here, not only do we explicitly recognize multiple types of objects, but we also focus on the ordinal relationships across types. Collaborative Ordinal Embedding or COE is based on generative modelling of ordinal triples. Experiments show that COE outperforms the baselines on objective metrics, revealing its capacity for information preservation for ordinal data.
Hdidx: High-Dimensional Indexing For Efficient Approximate Nearest Neighbor Search, Ji Wan, Sheng Tang, Yongdong Zhang, Jintao Li, Pengcheng Wu, Steven C. H. Hoi
Hdidx: High-Dimensional Indexing For Efficient Approximate Nearest Neighbor Search, Ji Wan, Sheng Tang, Yongdong Zhang, Jintao Li, Pengcheng Wu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Fast Nearest Neighbor (NN) search is a fundamental challenge in large-scale data processing and analytics, particularly for analyzing multimedia contents which are often of high dimensionality. Instead of using exact NN search, extensive research efforts have been focusing on approximate NN search algorithms. In this work, we present "HDIdx", an efficient high-dimensional indexing library for fast approximate NN search, which is open-source and written in Python. It offers a family of state-of-the-art algorithms that convert input high-dimensional vectors into compact binary codes, making them very efficient and scalable for NN search with very low space complexity.
Capture: A New Predictive Anti-Poaching Tool For Wildlife Protection, Thanh H. Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
Capture: A New Predictive Anti-Poaching Tool For Wildlife Protection, Thanh H. Nguyen, Arunesh Sinha, Shahrzad Gholami, Andrew Plumptre, Lucas Joppa, Milind Tambe, Margaret Driciru, Fred Wanyama, Aggrey Rwetsiba, Rob Critchlow
Research Collection School Of Computing and Information Systems
Wildlife poaching presents a serious extinction threat to many animalspecies. Agencies (“defenders”) focused on protecting suchanimals need tools that help analyze, model and predict poacheractivities, so they can more effectively combat such poaching; suchtools could also assist in planning effective defender patrols, buildingon the previous security games research.To that end, we have built a new predictive anti-poaching tool,CAPTURE (Comprehensive Anti-Poaching tool with Temporaland observation Uncertainty REasoning). CAPTURE providesfour main contributions. First, CAPTURE’s modeling of poachersprovides significant advances over previous models from behavioralgame theory and conservation biology. This accounts for:(i) the defender’s imperfect detection of poaching signs; (ii) complextemporal dependencies in …
Semantic Proximity Search On Graphs With Metagraph-Based Learning, Yuan Fang, Wenqing Lin, Vincent W. Zheng, Min Wu, Kevin Chen-Chuan Chang, Xiao-Li Li
Semantic Proximity Search On Graphs With Metagraph-Based Learning, Yuan Fang, Wenqing Lin, Vincent W. Zheng, Min Wu, Kevin Chen-Chuan Chang, Xiao-Li Li
Research Collection School Of Computing and Information Systems
Given ubiquitous graph data such as the Web and social networks, proximity search on graphs has been an active research topic. The task boils down to measuring the proximity between two nodes on a graph. Although most earlier studies deal with homogeneous or bipartite graphs only, many real-world graphs are heterogeneous with objects of various types, giving rise to different semantic classes of proximity. For instance, on a social network two users can be close for different reasons, such as being classmates or family members, which represent two distinct classes of proximity. Thus, it becomes inadequate to only measure a …
Fast Weighted Histograms For Bilateral Filtering And Nearest Neighbor Searching, Shengfeng He, Qingxiong Yang, Rynson W. H. Lau, Ming-Hsuan Yang
Fast Weighted Histograms For Bilateral Filtering And Nearest Neighbor Searching, Shengfeng He, Qingxiong Yang, Rynson W. H. Lau, Ming-Hsuan Yang
Research Collection School Of Computing and Information Systems
The locality sensitive histogram (LSH) injects spatial information into the local histogram in an efficient manner, and has been demonstrated to be very effective for visual tracking. In this paper, we explore the application of this efficient histogram in two important problems. We first extend the LSH to linear time bilateral filtering, and then propose a new type of histogram for efficiently computing edge-preserving nearest neighbor fields (NNFs). While the existing histogram-based bilateral filtering methods are the state of the art for efficient grayscale image processing, they are limited to box spatial filter kernels only. In our first application, we …
Using Abstractions To Solve Opportunistic Crime Security Games At Scale, Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Qian. Yundi, Yevgeniy Vorobeychik, Milind Tambe
Using Abstractions To Solve Opportunistic Crime Security Games At Scale, Chao Zhang, Victor Bucarey, Ayan Mukhopadhyay, Arunesh Sinha, Qian. Yundi, Yevgeniy Vorobeychik, Milind Tambe
Research Collection School Of Computing and Information Systems
In this paper, we aim to deter urban crime by recommending optimal police patrol strategies against opportunistic criminals in large scale urban problems. While previous work has tried to learn criminals' behavior from real world data and generate patrol strategies against opportunistic crimes, it cannot scale up to large-scale urban problems. Our first contribution is a game abstraction framework that can handle opportunistic crimes in large-scale urban areas. In this game abstraction framework, we model the interaction between officers and opportunistic criminals as a game with discrete targets. By merging similar targets, we obtain an abstract game with fewer total …
Learning Adversary Behavior In Security Games: A Pac Model Perspective, Arunesh Sinha, Debarun Kar, Milind Tambe
Learning Adversary Behavior In Security Games: A Pac Model Perspective, Arunesh Sinha, Debarun Kar, Milind Tambe
Research Collection School Of Computing and Information Systems
Recent applications of Stackelberg Security Games (SSG), from wildlife crime to urban crime, have employed machine learning tools to learn and predict adversary behavior using available data about defender-adversary interactions. Given these recent developments, this paper commits to an approach of directly learning the response function of the adversary. Using the PAC model, this paper lays a firm theoretical foundation for learning in SSGs (e.g., theoretically answer questions about the numbers of samples required to learn adversary behavior) and provides utility guarantees when the learned adversary model is used to plan the defender's strategy. The paper also aims to answer …
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Optimizing Selection Of Competing Services With Probabilistic Hierarchical Refinement, Tian Huat Tan, Manman Chen, Jun Sun, Yang Liu, Étienne André, Yinxing Xue, Jin Song Dong
Research Collection School Of Computing and Information Systems
Recently, many large enterprises (e.g., Netflix, Amazon) have decomposed their monolithic application into services, and composed them to fulfill their business functionalities. Many hosting services on the cloud, with different Quality of Service (QoS) (e.g., availability, cost), can be used to host the services. This is an example of competing services. QoS is crucial for the satisfaction of users. It is important to choose a set of services that maximize the overall QoS, and satisfy all QoS requirements for the service composition. This problem, known as optimal service selection, is NPhard. Therefore, an effective method for reducing the search space …
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Approximating The Performance Of A "Last Mile" Transportation System, Hai Wang, Amedeo Odoni
Research Collection School Of Computing and Information Systems
The Last Mile Problem (LMP) refers to the provision of travel service from the nearest public transportation node to a home or office. We study the supply side of this problem in a stochastic setting, with batch demands resulting from the arrival of groups of passengers who request last-mile service at urban rail stations or bus stops. Closedform approximations are derived for the performance of Last Mile Transportations Systems as a function of the fundamental design parameters of such systems. An initial set of results is obtained for the case in which a fleet of vehicles of unit capacity provides …
Online Passive-Aggressive Active Learning, Jing Lu, Peilin Zhao, Steven C. H. Hoi
Online Passive-Aggressive Active Learning, Jing Lu, Peilin Zhao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
We investigate online active learning techniques for online classification tasks. Unlike traditional supervised learning approaches, either batch or online learning, which often require to request class labels of each incoming instance, online active learning queries only a subset of informative incoming instances to update the classification model, aiming to maximize classification performance with minimal human labelling effort during the entire online learning task. In this paper, we present a new family of online active learning algorithms called Passive-Aggressive Active (PAA) learning algorithms by adapting the Passive-Aggressive algorithms in online active learning settings. Unlike conventional Perceptron-based approaches that employ only the …
On Unravelling Opinions Of Issue Specific-Silent Users In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu, Pei Hua Cher
On Unravelling Opinions Of Issue Specific-Silent Users In Social Media, Wei Gong, Ee-Peng Lim, Feida Zhu, Pei Hua Cher
Research Collection School Of Computing and Information Systems
Social media has become a popular platform for people toshare opinions. Among the social media mining researchprojects that study user opinions and issues, most focus onanalyzing posted and shared content. They could run into thedanger of non-representative findings as the opinions of userswho do not post content are overlooked, which often happensin today’s marketing, recommendation, and social sensing research.For a more complete and representative profiling ofuser opinions on various topical issues, we need to investigatethe opinions of the users even when they stay silent onthese issues. We call these users the issue specific-silent users(i-silent users). To study them and their …