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Articles 1 - 30 of 38
Full-Text Articles in Physical Sciences and Mathematics
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Anomaly Detection Through Enhanced Sentiment Analysis On Social Media Data, Zhaoxia Wang, Victor Joo, Chuan Tong, Xin Xin, Hoong Chor Chin
Research Collection School Of Computing and Information Systems
Anomaly detection in sentiment analysis refers to detecting abnormal opinions, sentiment patterns or special temporal aspects of such patterns in a collection of data. The anomalies detected may be due to sudden sentiment changes hidden in large amounts of text. If these anomalies are undetected or poorly managed, the consequences may be severe, e.g. A business whose customers reveal negative sentiments and will no longer support the establishment. Social media platforms, such as Twitter, provide a vast source of information, which includes user feedback, opinion and information on most issues. Many organizations also leverage social media platforms to publish information …
Extracting Interest Tags From Twitter User Biographies, Ying Ding, Jing Jiang
Extracting Interest Tags From Twitter User Biographies, Ying Ding, Jing Jiang
Research Collection School Of Computing and Information Systems
Twitter, one of the most popular social media platforms, has been studied from different angles. One of the important sources of information in Twitter is users’ biographies, which are short self-introductions written by users in free form. Biographies often describe users’ background and interests. However, to the best of our knowledge, there has not been much work trying to extract information from Twitter biographies. In this work, we study how to extract information revealing users’ personal interests from Twitter biographies. A sequential labeling model is trained with automatically constructed labeled data. The popular patterns expressing user interests are extracted and …
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Issues Of Social Data Analytics With A New Method For Sentiment Analysis Of Social Media Data, Zhaoxia Wang, Victor J. C. Tong, David Chan
Research Collection School of Social Sciences
Social media data consists of feedback, critiques and other comments that are posted online by internet users. Collectively, these comments may reflect sentiments that are sometimes not captured in traditional data collection methods such as administering a survey questionnaire. Thus, social media data offers a rich source of information, which can be adequately analyzed and understood. In this paper, we survey the extant research literature on sentiment analysis and discuss various limitations of the existing analytical methods. A major limitation in the large majority of existing research is the exclusive focus on social media data in the English language. There …
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
On Joint Modeling Of Topical Communities And Personal Interest In Microblogs, Tuan-Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we propose the Topical Communities and Personal Interest (TCPI) model for simultaneously modeling topics, topical communities, and users’ topical interests in microblogging data. TCPI considers different topical communities while differentiating users’ personal topical interests from those of topical communities, and learning the dependence of each user on the affiliated communities to generate content. This makes TCPI different from existing models that either do not consider the existence of multiple topical communities, or do not differentiate between personal and community’s topical interests. Our experiments on two Twitter datasets show that TCPI can effectively mine the representative topics for …
The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao
The Evolution Of Research On Multimedia Travel Guide Search And Recommender Systems, Junge Shen, Zhiyong Cheng, Jialie Shen, Tao Mei, Xinbo Gao
Research Collection School Of Computing and Information Systems
The importance of multimedia travel guide search and recommender systems has led to a substantial amount of research spanning different computer science and information system disciplines in recent years. The five core research streams we identify here incorporate a few multimedia computing and information retrieval problems that relate to the alternative perspectives of algorithm design for optimizing search/recommendation quality and different methodological paradigms to assess system performance at large scale. They include (1) query analysis, (2) diversification based on different criteria, (3) ranking and reranking, (4) personalization and (5) evaluation. Based on a comprehensive discussion and analysis of these streams, …
Historical Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis
Historical Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Historical traffic information is valuable for transportation analysis and planning, as well as for route search services. In view of these applications, we propose the k traffic-tolerant paths problem (TTP) on road networks, which takes a source-destination pair and historical traffic information as input, and returns k paths that minimize the aggregate (historical) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to compute. We propose an exact algorithm and a heuristic algorithm for this problem. Experiments on real traffic data demonstrate the effectiveness of TTP paths and …
Singapore Management University Establishes A New Research Centre On Secure Mobile Computing Technologies And Solutions, Singapore Management University
Singapore Management University Establishes A New Research Centre On Secure Mobile Computing Technologies And Solutions, Singapore Management University
SMU Press Releases
The Singapore Management University (SMU) has announced today the establishment of a new centre of research excellence that focuses on mobile computing security. Funded by Singapore’s National Research Foundation (NRF), the Secure Mobile Centre is developing efficient and scalable technologies and solutions that strengthen the security of mobile computing systems, applications and services. The Secure Mobile Centre is led by a team of five faculty members from SMU’s School of Information Systems who specialise in information security and trust: Professor Robert DENG (Centre Director), Professor PANG Hwee Hwa, Associate Professor LI Yingjiu, Associate Professor DING Xuhua and Assistant Professor Debin …
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Entity Linking On Microblogs With Spatial And Temporal Signals, Yuan Fang, Ming-Wei Chang
Research Collection School Of Computing and Information Systems
Microblogs present an excellent opportunity for monitoring and analyzing world happenings. Given that words are often ambiguous, entity linking becomes a crucial step towards understanding microblogs. In this paper, we re-examine the problem of entity linking on microblogs. We first observe that spatiotemporal (i.e., spatial and temporal) signals play a key role, but they are not utilized in existing approaches. Thus, we propose a novel entity linking framework that incorporates spatiotemporal signals through a weakly supervised process. Using entity annotations1 on real-world data, our experiments show that the spatiotemporal model improves F1 by more than 10 points over existing systems. …
Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Roy Ka Wei Lee, Tin Seong Kam
Time-Series Data Mining In Transportation: A Case Study On Singapore Public Train Commuter Travel Patterns, Roy Ka Wei Lee, Tin Seong Kam
Research Collection School Of Computing and Information Systems
The adoption of smart cards technologies and automated data collection systems (ADCS) in transportation domain had provided public transport planners opportunities to amass a huge and continuously increasing amount of time-series data about the behaviors and travel patterns of commuters. However the explosive growth of temporal related databases has far outpaced the transport planners’ ability to interpret these data using conventional statistical techniques, creating an urgent need for new techniques to support the analyst in transforming the data into actionable information and knowledge. This research study thus explores and discusses the potential use of time-series data mining, a relatively new …
The Use Of Geospatial Clustering In Analysing Health Risk Profile, Sue-Mae Yeo, Tin Seong Kam, Kai Xin Thia, Dan Wu
The Use Of Geospatial Clustering In Analysing Health Risk Profile, Sue-Mae Yeo, Tin Seong Kam, Kai Xin Thia, Dan Wu
Research Collection School Of Computing and Information Systems
Background & Hypothesis: The first law of geography states that “everything is related to everything else, but near things are more related than distant things”. This study aims to demonstrate how local indicator of spatial association (LISA) statistics are used to group patients with similar chronic diseases into natural clusters of hotspots found within northern Singapore by incorporating the proximity of their home locations explicitly. Methods: Anonymised chronic patient data collected from Khoo Teck Puat Hospital in 2013 were used for analyses. The data was mapped based on patients' residential addresses. A layer of hexagonal grid objects, each with a …
Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin
Clear: A Real-Time Online Observatory For Bursty And Viral Events, Runquan Xie, Feida Zhu, Hui Ma, Wei Xie, Chen Lin
Research Collection School Of Computing and Information Systems
We describe our demonstration of CLEar (Clairaudient Ear), a real-time online platform for detecting, monitoring, summarizing, contextualizing and visualizing bursty and viral events, those triggering a sudden surge of public interest and going viral on micro-blogging platforms. This task is challenging for existing methods as they either use complicated topic models to analyze topics in a off-line manner or define temporal structure of fixed granularity on the data stream for online topic learning, leaving them hardly scalable for real-time stream like that of Twitter. In this demonstration of CLEar, we present a three-stage system: First, we show …
Press: A Novel Framework Of Trajectory Compression In Road Networks, Renchu Song, Weiwei Sun, Baihua Zheng, Yu Zheng
Press: A Novel Framework Of Trajectory Compression In Road Networks, Renchu Song, Weiwei Sun, Baihua Zheng, Yu Zheng
Research Collection School Of Computing and Information Systems
Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory Compression), to effectively compress trajectory data under road network constraints. Different from existing work, PRESS proposes a novel representation for trajectories to separate the spatial representation of a trajectory from the temporal representation, and proposes a Hybrid Spatial Compression (HSC) algorithm and error Bounded Temporal Compression (BTC) algorithm to compress the spatial and temporal information of trajectories respectively. PRESS also supports common spatial-temporal queries without fully decompressing the data. Through an extensive experimental study …
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Sharing Political News: The Balancing Act Of Intimacy And Socialization In Selective Exposure, Jisun An, Daniele Quercia, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft
Research Collection School Of Computing and Information Systems
One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification, selective exposure, socialization, and trust & intimacy. Using real instances of political news sharing in Twitter, we study the predictive power of these features. As one might expect, …
An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo
An Exploratory Study On Software Microblogger Behaviors, Yuan Tian, David Lo
Research Collection School Of Computing and Information Systems
Microblogging services are growing rapidly in the recent years. Twitter, one of the most popular microblogging sites, has gained more than 500 millions users. Thousands of developers are also using Twitter to communicate with one another and microblog about software-related topics such as programming languages, code libraries, etc. Understanding the behaviors of software microbloggers is one of the needed first steps toward building automated tools to encourage software microblogging activities and harness software microblogging to improve various software engineering activities. In this paper, we investigate the behaviors of software microbloggers in terms of their microblogging frequency, generated contents, and interactions …
Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos
Interestingness-Driven Diffussion Process Summarization In Dynamic Networks, Qiang Qu, Siyuan Liu, Christian Jensen, Feida Zhu, Christos Faloutsos
Research Collection School Of Computing and Information Systems
The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which render existing techniques inapplicable. We study the topic of dynamic …
A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang
A Study Of Age Gaps Between Online Friends, Lizi Liao, Jing Jiang, Ee Peng Lim, Heyan Huang
Research Collection School Of Computing and Information Systems
User attribute extraction on social media has gain considerable attention, while existing methods are mostly supervised which suffer great diffi- culty in insufficient gold standard data. In this paper, we validate a strong hypothesis based on homophily and adapt it to ensure the certainty of user attribute we extracted via weakly supervised propagation. Homophily, the theory which states that people who are similar tend to become friends, has been well studied in the setting of online social networks. When we focus on age attribute, based on this theory, online friends tend to have similar age. In this work, we take …
Social Tipping Points And Earth Systems Dynamics, R.A. Bentley, E. Maddison, P. Ranner, J. Bissell, C. Caiado, P. Bhatanacharoen, Timothy Adrian Robert Clark, Botha M., Akinbami F., Hollow M., Michie R., Huntley B., Curtis S., Garnett P.
Social Tipping Points And Earth Systems Dynamics, R.A. Bentley, E. Maddison, P. Ranner, J. Bissell, C. Caiado, P. Bhatanacharoen, Timothy Adrian Robert Clark, Botha M., Akinbami F., Hollow M., Michie R., Huntley B., Curtis S., Garnett P.
Research Collection Lee Kong Chian School Of Business
Recently, Early Warning Signals (EWS) have been developed to predict tipping points in Earth Systems. This discussion highlights the potential to apply EWS to human social and economic systems, which may also undergo similar critical transitions. Social tipping points are particularly difficult to predict, however, and the current formulation of EWS, based on a physical system analogy, may be insufficient. As an alternative set of EWS for social systems, we join with other authors encouraging a focus on heterogeneity, connectivity through social networks and individual thresholds to change.
Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang
Urban Planning Process: Can Technology Enhance Participatory Communication?, Rojin Vishkaie, Richard Levy, Anthony Tang
Research Collection School Of Computing and Information Systems
Oftentimes, within the urban planning process, urban planners and GIS experts must work together using desktop Computer-Aided Design (CAD) and Geographic Information System (GIS). However, participatory communication and visualization which are important in the urban planning process, are not a central focus in the design of current computer-aided planning technologies. This study tends to provide an understanding of technological challenges and complexities urban planners and GIS experts encounter while engaging in a participatory environment during the urban planning process. This study also explores the perceptions of urban planners and GIS experts about the potential impact and usefulness of interactive surfaces …
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter, Yazhe Wang, Baihua Zheng
On Macro And Micro Exploration Of Hashtag Diffusion In Twitter, Yazhe Wang, Baihua Zheng
Research Collection School Of Computing and Information Systems
This exploratory work studies hashtag diffusion in Twitter. The analysis is conducted from two aspects. From the macro perspective, we study general properties of hashtag diffusion, and classify hashtags into three main classes based on their temporal dynamics referred as 'single spike', 'multi-spikes', and 'fluctuation', and find that each of these classes has some unique characteristics. From the micro perspective, we investigate individual diffusion.We adopt Edelman's 'topology of influence' theory to identify four type of users with different influence levels in diffusion based on their dynamic retweet behaviors. The results of our study are useful for gaining more insights of …
Diversified Social Influence Maximization, Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu
Diversified Social Influence Maximization, Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu
Research Collection School Of Computing and Information Systems
For better viral marketing, there has been a lot of research on social influence maximization. However, the problem that who is influenced and how diverse the influenced population is, which is important in real-world marketing, has largely been neglected. To that end, in this paper, we propose to consider the magnitude of influence and the diversity of the influenced crowd simultaneously. Specifically, we formulate it as an optimization problem, i.e., diversified social influence maximization. First, we present a general framework for this problem, under which we construct a class of diversity measures to quantify the diversity of the influenced crowd. …
Generating Supplementary Travel Guides From Social Media, Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu, Lizi Liao
Generating Supplementary Travel Guides From Social Media, Liu Yang, Jing Jiang, Lifu Huang, Minghui Qiu, Lizi Liao
Research Collection School Of Computing and Information Systems
In this paper we study how to summarize travel-related information in forum threads to generate supplementary travel guides. Such summaries presumably can provide additional and more up-to-date information to tourists. Existing multi-document summarization methods have limitations for this task because (1) they do not generate structured summaries but travel guides usually follow a certain template, and (2) they do not put emphasis on named entities but travel guides often recommend points of interest to travelers. To overcome these limitations, we propose to use a latent variable model to align forum threads with the section structure of well-written travel guides. The …
On Predicting Religion Labels In Microblogging Networks, Minh Thap Nguyen, Ee Peng Lim
On Predicting Religion Labels In Microblogging Networks, Minh Thap Nguyen, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Religious belief plays an important role in how people behave, influencing how they form preferences, interpret events around them, and develop relationships with others. Traditionally, the religion labels of user population are obtained by conducting a large scale census study. Such an approach is both high cost and time consuming. In this paper, we study the problem of predicting users' religion labels using their microblogging data. We formulate religion label prediction as a classification task, and identify content, structure and aggregate features considering their self and social variants for representing a user. We introduce the notion of representative user to …
Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu
Influences Of Influential Users: An Empirical Study Of Music Social Network, Jing Ren, Zhiyong Cheng, Jialie Shen, Feida Zhu
Research Collection School Of Computing and Information Systems
Influential user can play a crucial role in online social networks. This paper documents an empirical study aiming at exploring the effects of influential users in the context of music social network. To achieve this goal, music diffusion graph is developed to model how information propagates over network. We also propose a heuristic method to measure users' influences. Using the real data from Last. fm, our empirical test demonstrates key effects of influential users and reveals limitations of existing influence identification/characterization schemes.
Predicting The Popularity Of Web 2.0 Items Based On User Comments, Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama
Predicting The Popularity Of Web 2.0 Items Based On User Comments, Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, Kazunari Sugiyama
Research Collection School Of Computing and Information Systems
In the current Web 2.0 era, the popularity of Web resources fluctuates ephemerally, based on trends and social interest. As a result, content-based relevance signals are insufficient to meet users' constantly evolving information needs in searching for Web 2.0 items. Incorporating future popularity into ranking is one way to counter this. However, predicting popularity as a third party (as in the case of general search engines) is difficult in practice, due to their limited access to item view histories. To enable popularity prediction externally without excessive crawling, we propose an alternative solution by leveraging user comments, which are more accessible …
Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee Peng Lim
Lifetime Lexical Variation In Social Media, Lizi Liao, Jing Jiang, Ying Ding, Heyan Huang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
As the rapid growth of online social media attracts a large number of Internet users, the large volume of content generated by these users also provides us with an opportunity to study the lexical variation of people of different ages. In this paper, we present a latent variable model that jointly models the lexical content of tweets and Twitter users’ ages. Our model inherently assumes that a topic has not only a word distribution but also an age distribution. We propose a Gibbs-EM algorithm to perform inference on our model. Empirical evaluation shows that our model can learn meaningful age-specific …
New A*Star-Smu Centre Combines High-Powered Computing And Behavioural Sciences To Study People-Centric Issues, Singapore Management University
New A*Star-Smu Centre Combines High-Powered Computing And Behavioural Sciences To Study People-Centric Issues, Singapore Management University
SMU Press Releases
The Agency for Science, Technology and Research (A*STAR) and the Singapore Management University (SMU) will establish a Centre for Technology and Social-Behavioural Insights (CTSBI) to tap on high performance computing technology, big data analytics and behavioural sciences to study people-centric issues and human behaviour including how people think, feel and act in different settings. Such information can be used to enhance planning and address issues in different areas such as retail, logistics, urban planning, education and community development.
Does Latitude Hurt While Longitude Kills? Geographical And Temporal Separation In A Large Scale Software Development Project, Patrick Wagstrom, Subhajit Datta
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 …
Socio-Physical Analytics: Challenges & Opportunities, Archan Misra, Kasthuri Jayarajah, Shriguru Nayak, Philips Kokoh Prasetyo, Ee-Peng Lim
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 …
An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu
An Air Index For Spatial Query Processing In Road Networks, Weiwei Sun, Chunan Chen, Baihua Zheng, Chong Chen, Peng Liu
Research Collection School Of Computing and Information Systems
Spatial queries such as range query and kNN query in road networks have received a growing number of attention in real life. Considering the large population of the users and the high overhead of network distance computation, it is extremely important to guarantee the efficiency and scalability of query processing. Motivated by the scalable and secure properties of wireless broadcast model, this paper presents an air index called Network Partition Index (NPI) to support efficient spatial query processing in road networks via wireless broadcast. The main idea is to partition the road network into a number of regions and then …
Evolving An Information Systems Capstone Course To Align With The Fast Changing Singapore Marketplace, Chris Boesch, Benjamin Kok Siew Gan
Evolving An Information Systems Capstone Course To Align With The Fast Changing Singapore Marketplace, Chris Boesch, Benjamin Kok Siew Gan
Research Collection School Of Computing and Information Systems
Every year, around fifty-five undergraduate teams of four to six students are required to complete a capstone course for the School of Information Systems at Singapore Management University. Each team spends approximately five months working with an industry sponsor using the latest tools and techniques. Students actively learn by implementing the system to solve a real world problem. In addition to delivering value to the local sponsor, our students learn specialized skills currently needed in the marketplace, which might not yet be incorporated into electives and core courses. In this paper, we discuss the tradeoffs of providing students and project …