Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- Social media (7)
- Crowdsourcing (3)
- Analytics Master Program (2)
- Asia (2)
- Challenges and Solutions (2)
-
- Demographics (2)
- Lessons Learnt (2)
- Optimization (2)
- Sentiment analysis (2)
- Taxicabs (2)
- Topic model (2)
- Twitter (2)
- User Analytics (2)
- User Experience Research (2)
- Accessibility (1)
- Ageing-in-place (1)
- Air-gaps (1)
- Analytical models (1)
- Artificial intelligence (1)
- Attribute recognition (1)
- Autism Spectrum Disorder (1)
- Autonomous agents (1)
- Balise (1)
- Behavior mining (1)
- Bicycles (1)
- Bike route choice (1)
- Building model (1)
- Burst pattern (1)
- Burst topic (1)
- Catastrophic consequences (1)
Articles 31 - 50 of 50
Full-Text Articles in Social and Behavioral Sciences
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
A Multi-Agent System For Coordinating Vessel Traffic, Teck-Hou Teng, Hoong Chuin Lau, Akshat Kumar
Research Collection School Of Computing and Information Systems
Environmental, regulatory and resource constraints affects the safety and efficiency of vessels navigating in and out of the ports. Movement of vessels under such constraints must be coordinated for improving safety and efficiency. Thus, we frame the vessel coordination problem as a multi-agent path-finding (MAPF) problem. We solve this MAPF problem using a Coordinated Path-Finding (CPF) algorithm. Based on the local search paradigm, the CPF algorithm improves on the aggregated path quality of the vessels iteratively. Outputs of the CPF algorithm are the coordinated trajectories. The Vessel Coordination Module (VCM) described here is the module encapsulating our MAPF-based approach for …
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Discovering Your Selling Points: Personalized Social Influential Tags Exploration, Yuchen Li, Kian-Lee Tan, Ju Fan, Dongxiang Zhang
Research Collection School Of Computing and Information Systems
Social influence has attracted significant attention owing to the prevalence of social networks (SNs). In this paper, we study a new social influence problem, called personalized social influential tags exploration (PITEX), to help any user in the SN explore how she influences the network. Given a target user, it finds a size-k tag set that maximizes this user’s social influence. We prove the problem is NP-hard to be approximated within any constant ratio. To solve it, we introduce a sampling-based framework, which has an approximation ratio of 1−ǫ 1+ǫ with high probabilistic guarantee. To speedup the computation, we devise more …
Exploiting Contextual Information For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim
Exploiting Contextual Information For Fine-Grained Tweet Geolocation, Wen Haw Chong, Ee Peng Lim
Research Collection School Of Computing and Information Systems
The problem of fine-grained tweet geolocation is to link tweets to their posting venues. We solve this in a learning to rank framework by ranking candidate venues given a test tweet. The problem is challenging as tweets are short and the vast majority are non-geocoded, meaning information is sparse for building models. Nonetheless, although only a small fraction of tweets are geocoded, we find that they are posted by a substantial proportion of users. Essentially, such users have location history data. Along with tweet posting time, these serve as additional contextual information for geolocation. In designing our geolocation models, we …
On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim
On Analyzing User Topic-Specific Platform Preferences Across Multiple Social Media Sites, Roy Ka Wei Lee, Tuan Anh Hoang, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Topic modeling has traditionally been studied for single text collections and applied to social media data represented in the form of text documents. With the emergence of many social media platforms, users find themselves using different social media for posting content and for social interaction. While many topics may be shared across social media platforms, users typically show preferences of certain social media platform(s) over others for certain topics. Such platform preferences may even be found at the individual level. To model social media topics as well as platform preferences of users, we propose a new topic model known as …
Collective Entity Linking In Tweets Over Space And Time, Wen Haw Chong, Ee-Peng Lim, William Cohen
Collective Entity Linking In Tweets Over Space And Time, Wen Haw Chong, Ee-Peng Lim, William Cohen
Research Collection School Of Computing and Information Systems
We propose collective entity linking over tweets that are close in space and time. This exploits the fact that events or geographical points of interest often result in related entities being mentioned in spatio-temporal proximity. Our approach directly applies to geocoded tweets. Where geocoded tweets are overly sparse among all tweets, we use a relaxed version of spatial proximity which utilizes both geocoded and non-geocoded tweets linked by common mentions. Entity linking is affected by noisy mentions extracted and incomplete knowledge bases. Moreover, to perform evaluation on the entity linking results, much manual annotation of mentions is often required. To …
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Modeling Topics And Behavior Of Microbloggers: An Integrated Approach, Tuan Anh Hoang, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Microblogging encompasses both user-generated content and behavior. When modeling microblogging data, one has to consider personal and background topics, as well as how these topics generate the observed content and behavior. In this article, we propose the Generalized Behavior-Topic (GBT) model for simultaneously modeling background topics and users' topical interest in microblogging data. GBT considers multiple topical communities (or realms) with different background topical interests while learning the personal topics of each user and the user's dependence on realms to generate both content and behavior. This differentiates GBT from other previous works that consider either one realm only or content …
Vulnerabilities, Attacks, And Countermeasures In Balise-Based Train Control Systems, Yongdong Wu, Jian Weng, Zhe Tang, Xin Li, Robert H. Deng
Vulnerabilities, Attacks, And Countermeasures In Balise-Based Train Control Systems, Yongdong Wu, Jian Weng, Zhe Tang, Xin Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In modern rail transport systems, balises are widely used to exchange track-train information via air-gap interface. In this paper, we first present the vulnerabilities on the standard balise air-gap interface, and then conduct vulnerability simulations using the system parameters that were specified in the European Train Control System. The simulation results show that the vulnerabilities can be exploited to launch effective and practical attacks, which could lead to catastrophic consequences, such as train derailment or collision. To mitigate the vulnerabilities and attacks, we propose to implement a challenge-response authentication process in the air-gap interface in the existing transport infrastructure.
Predicting The Impact Of Software Engineering Topics: An Empirical Study, Santonu Sarkar, Rumana Lakdawala, Subhajit Datta
Predicting The Impact Of Software Engineering Topics: An Empirical Study, Santonu Sarkar, Rumana Lakdawala, Subhajit Datta
Research Collection School Of Computing and Information Systems
Predicting the future is hard, more so in active research areas. In this paper, we customize an established model for citation prediction of research papers and apply it on research topics. We argue that research topics, rather than individual publications, have wider relevance in the research ecosystem, for individuals as well as organizations. In this study, topics are extracted from a corpus of software engineering publications covering 55,000+ papers written by more than 70,000 authors across 56 publication venues, over a span of 38 years, using natural language processing techniques. We demonstrate how critical aspects of the original paper-based prediction …
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim
Now You See It, Now You Don't! A Study Of Content Modification Behavior In Facebook, Fuxiang Chen, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
Social media, as a major platform to disseminate information, has changed the way users and communities contribute content. In this paper, we aim to study content modifications on public Facebook pages operated by news media, community groups, and bloggers. We also study the possible reasons behind them, and their effects on user interaction. We conducted a detailed study of Content Censorship (CC) and Content Edit (CE) in Facebook using a detailed longitudinal dataset consisting of 57 public Facebook pages over 3 weeks covering 145,955 posts and 9,379,200 comments. We detected many CC and CE activities between 28% and 56% of …
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Inferring User Consumption Preferences From Social Media, Yang Li, Jing Jiang, Ting Liu
Research Collection School Of Computing and Information Systems
Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly …
Bike Route Choice Modeling Using Gps Data Without Choice Sets Of Paths, Maëlle Zimmermann, Tien Mai, Emma Frejinger
Bike Route Choice Modeling Using Gps Data Without Choice Sets Of Paths, Maëlle Zimmermann, Tien Mai, Emma Frejinger
Research Collection School Of Computing and Information Systems
Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any …
Collective Multiagent Sequential Decision Making Under Uncertainty, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
Collective Multiagent Sequential Decision Making Under Uncertainty, Duc Thien Nguyen, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Multiagent sequential decision making has seen rapid progress with formal models such as decentralized MDPs and POMDPs. However, scalability to large multiagent systems and applicability to real world problems remain limited. To address these challenges, we study multiagent planning problems where the collective behavior of a population of agents affects the joint-reward and environment dynamics. Our work exploits recent advances in graphical models for modeling and inference with a population of individuals such as collective graphical models and the notion of finite partial exchangeability in lifted inference. We develop a collective decentralized MDP model where policies can be computed based …
Harnessing Twitter To Support Serendipitous Learning Of Developers, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, David Lo, Aiko Yamashita
Harnessing Twitter To Support Serendipitous Learning Of Developers, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, David Lo, Aiko Yamashita
Research Collection School Of Computing and Information Systems
Developers often rely on various online resources, such as blogs, to keep themselves up-to-date with the fast pace at which software technologies are evolving. Singer et al. found that developers tend to use channels such as Twitter to keep themselves updated and support learning, often in an undirected or serendipitous way, coming across things that they may not apply presently, but which should be helpful in supporting their developer activities in future. However, identifying relevant and useful articles among the millions of pieces of information shared on Twitter is a non-trivial task. In this work to support serendipitous discovery of …
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Dynamic Repositioning To Reduce Lost Demand In Bike Sharing Systems, Supriyo Ghosh, Pradeep Varakantham, Yossiri Adulyasak, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Bike Sharing Systems (BSSs) are widely adopted in major cities of the world due to concerns associated with extensive private vehicle usage, namely, increased carbon emissions, traffic congestion and usage of nonrenewable resources. In a BSS, base stations are strategically placed throughout a city and each station is stocked with a pre-determined number of bikes at the beginning of the day. Customers hire the bikes from one station and return them at another station. Due to unpredictable movements of customers hiring bikes, there is either congestion (more than required) or starvation (fewer than required) of bikes at base stations. Existing …
Discovering Burst Patterns Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang
Discovering Burst Patterns 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 broadcast burst topics. There have been many studies on how to detect burst topics. However, mining burst patterns in burst topics has not been solved by the existing works. In this paper, we investigate the problem of mining burst patterns of burst topic in Twitter. A burst topic user graph model is proposed, which can represent the topology structure of burst topic propagation across a large number of Twitter users. Based on the model, hierarchical clustering is applied to cluster burst topics and reveal burst patterns from the macro …
Discovering Historic Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis
Discovering Historic Traffic-Tolerant Paths In Road Networks, Pui Hang Li, Man Lung Yiu, Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
Historic traffic information is valuable in transportation analysis and planning, e.g., evaluating the reliability of routes for representative source-destination pairs. Also, it can be utilized to provide efficient and effective route-search services. In view of these applications, we propose the k traffic-tolerant paths (TTP) problem on road networks, which takes a source-destination pair and historic traffic information as input, and returns k paths that minimize the aggregate (historic) travel time. Unlike the shortest path problem, the TTP problem has a combinatorial search space that renders the optimal solution expensive to find. First, we propose an exact algorithm with effective pruning …
Viewed By Too Many Or Viewed Too Little: Using Information Dissemination For Audience Segmentation, Bernard J. Jansen, Soon-Gyu Jung, Joni Salminen, Jisun An, Haewoon Kwak
Viewed By Too Many Or Viewed Too Little: Using Information Dissemination For Audience Segmentation, Bernard J. Jansen, Soon-Gyu Jung, Joni Salminen, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
The identification of meaningful audience segments, such as groups of users, consumers, readers, audience, etc., has important applicability in a variety of domains, including for content publishing. In this research, we seek to develop a technique for determining both information dissemination and information discrimination of online content in order to isolate audience segments. The benefits of the technique include identification of the most impactful content for analysis. With 4,320 online videos from a major news organization, a set of audience attributes, and more than 58 million interactions from hundreds of thousands of users, we isolate the key pieces of content …
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Fine-Grained Sentiment Analysis Of Social Media With Emotion Sensing, Zhaoxia Wang, Chee Seng Chong, Landy Lan, Yinping Yang, Beng-Seng Ho, Joo Chuan Tong
Research Collection School Of Computing and Information Systems
Social media is arguably the richest source of human generated text input. Opinions, feedbacks and critiques provided by internet users reflect attitudes and sentiments towards certain topics, products, or services. The sheer volume of such information makes it effectively impossible for any group of persons to read through. Thus, social media sentiment analysis has become an important area of work to make sense of the social media talk. However, most existing sentiment analysis techniques focus only on the aggregate level, classifying sentiments broadly into positive, neutral or negative, and lack the capabilities to perform fine-grained sentiment analysis. This paper describes …
Sensor-Driven Detection Of Social Isolation In Community-Dwelling Elderly, W K P Neranjana Nadee Rodrigo Goonawardene, Xiaoping Toh, Hwee-Pink Tan
Sensor-Driven Detection Of Social Isolation In Community-Dwelling Elderly, W K P Neranjana Nadee Rodrigo Goonawardene, Xiaoping Toh, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
Ageing-in-place, the ability to age holistically in the community, is increasingly gaining recognition as a solution to address resource limitations in the elderly care sector. Effective elderly care models require a personalised and all-encompassing approach to caregiving. In this regard, sensor technologies have gained attention as an effective means to monitor the wellbeing of elderly living alone. In this study, we seek to investigate the potential of non-intrusive sensor systems to detect socially isolated community dwelling elderly. Using a mixed method approach, our results showed that sensor-derived features such as going-out behavior, daytime napping and time spent in the living …
The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong
The Making Of A Successful Analytics Master Degree Program: Experiences And Lessons Drawn For A Young And Small Asian University, Michelle L. F. Cheong
Research Collection School Of Computing and Information Systems
Singapore Management University’s School of Information Systems is a young school within a young and small university in Asia. Being young and small, establishing a successful analytics master degree program required extensive landscape research, assessment of its own strengths and weaknesses, having a committed team, and having a clear vision to meet the ever-changing needs of the industry. The Master of IT in Business (Analytics) program, established since 2011, has grown from an annual intake of 16 to 128 students in six years. This article attempts to describe the design process, challenges faced, decisions made, and the key actions taken, …