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Articles 5731 - 5760 of 9024
Full-Text Articles in Computer Sciences
Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau
Oriented Object Proposals, Shengfeng He, Rynson W. H. Lau
Research Collection School Of Computing and Information Systems
In this paper, we propose a new approach to generate oriented object proposals (OOPs) to reduce the detection error caused by various orientations of the object. To this end, we propose to efficiently locate object regions according to pixelwise object probability, rather than measuring the objectness from a set of sampled windows. We formulate the proposal generation problem as a generative probabilistic model such that object proposals of different shapes (i.e., sizes and orientations) can be produced by locating the local maximum likelihoods. The new approach has three main advantages. First, it helps the object detector handle objects of different …
On Top-K Selection In Multi-Armed Bandits And Hidden Bipartite Graphs, Wei Cao, Jian Li, Yufei Tao, Zhize Li
On Top-K Selection In Multi-Armed Bandits And Hidden Bipartite Graphs, Wei Cao, Jian Li, Yufei Tao, Zhize Li
Research Collection School Of Computing and Information Systems
This paper discusses how to efficiently choose from $n$ unknown distributions the $k$ ones whose means are the greatest by a certain metric, up to a small relative error. We study the topic under two standard settings---multi-armed bandits and hidden bipartite graphs---which differ in the nature of the input distributions. In the former setting, each distribution can be sampled (in the i.i.d. manner) an arbitrary number of times, whereas in the latter, each distribution is defined on a population of a finite size $m$ (and hence, is fully revealed after m samples). For both settings, we prove lower bounds on …
On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam Doan, Freddy Chong-Tat Chua, Ee-Peng Lim
On Neighborhood Effects In Location-Based Social Networks, Thanh-Nam Doan, Freddy Chong-Tat Chua, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
In this paper, we analyze factors that determine the check-in decisions of users on venues using a location-based social network dataset. Based on a Foursquare dataset constructed from Singapore-based users, we devise a stringent criteria to identify the actual home locations of a subset of users. Using these users' check-ins, we aim to ascertain the neighborhood effect on the venues visited, compared with the activity level of users. We further formulate the check-in count prediction and check-in prediction tasks. A comprehensive set of features have been defined and they encompass information from users, venues, their neighbors, and friendship networks. We …
Differentially Private Subspace Clustering, Yining Wang, Yu-Xiang Wang, Aarti Singh
Differentially Private Subspace Clustering, Yining Wang, Yu-Xiang Wang, Aarti Singh
Research Collection School Of Computing and Information Systems
Subspace clustering is an unsupervised learning problem that aims at grouping data points into multiple “clusters” so that data points in a single cluster lie approximately on a low-dimensional linear subspace. It is originally motivated by 3D motion segmentation in computer vision, but has recently been generically applied to a wide range of statistical machine learning problems, which often involves sensitive datasets about human subjects. This raises a dire concern for data privacy. In this work, we build on the framework of differential privacy and present two provably private subspace clustering algorithms. We demonstrate via both theory and experiments that …
A Bayesian Recommender Model For User Rating And Review Profiling, Mingming Jiang, Dandan Song, Lejian Liao, Feida Zhu
A Bayesian Recommender Model For User Rating And Review Profiling, Mingming Jiang, Dandan Song, Lejian Liao, Feida Zhu
Research Collection School Of Computing and Information Systems
Intuitively, not only do ratings include abundant information for learning user preferences, but also reviews accompanied by ratings. However, most existing recommender systems take rating scores for granted and discard the wealth of information in accompanying reviews. In this paper, in order to exploit user profiles' information embedded in both ratings and reviews exhaustively, we propose a Bayesian model that links a traditional Collaborative Filtering (CF) technique with a topic model seamlessly. By employing a topic model with the review text and aligning user review topics with "user attitudes" (i.e., abstract rating patterns) over the same distribution, our method achieves …
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan
Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Ronald Wai Hong Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin Cerdena Valera, Hwee Xian Tan
Research Collection School Of Computing and Information Systems
The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …
Robust Execution Strategies For Project Scheduling With Unreliable Resources And Stochastic Durations, Na Fu, Hoong Chuin Lau, Pradeep Varakantham
Robust Execution Strategies For Project Scheduling With Unreliable Resources And Stochastic Durations, Na Fu, Hoong Chuin Lau, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
The resource-constrained project scheduling problem with minimum and maximum time lags (RCPSP/max) is a general model for resource scheduling in many real-world problems (such as manufacturing and construction engineering). We consider RCPSP/max problems where the durations of activities are stochastic and resources can have unforeseen breakdowns. Given a level of allowable risk, (Formula presented.), our mechanisms aim to compute the minimum robust makespan execution strategy. Robust makespan for an execution strategy is any makespan value that has a risk less than (Formula presented.). The risk for a makespan value, (Formula presented.) given an execution strategy, is the probability that a …
On The Unreliability Of Bug Severity Data, Yuan Tian, Nasir Ali, David Lo, Ahmed E. Hassan
On The Unreliability Of Bug Severity Data, Yuan Tian, Nasir Ali, David Lo, Ahmed E. Hassan
Research Collection School Of Computing and Information Systems
Severity levels, e.g., critical and minor, of bugs are often used to prioritize development efforts. Prior research efforts have proposed approaches to automatically assign the severity label to a bug report. All prior efforts verify the accuracy of their approaches using human-assigned bug reports data that is stored in software repositories. However, all prior efforts assume that such human-assigned data is reliable. Hence a perfect automated approach should be able to assign the same severity label as in the repository – achieving a 100% accuracy. Looking at duplicate bug reports (i.e., reports referring to the same problem) from three open-source …
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Capstone Projects Mining System For Insights And Recommendations, Melvrivk Aik Chun Goh, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
In this paper, we present a classification based system to discover knowledge and trends in higher education students’ projects. Essentially, the educational capstone projects provide an opportunity for students to apply what they have learned and prepare themselves for industry needs. Therefore mining such projects gives insights of students’ experiences as well as industry project requirements and trends. In particular, we mine capstone projects executed by Information Systems students to discover patterns and insights related to people, organization, domain, industry needs and time. We build a capstone projects mining system (CPMS) based on classification models that leverage text mining, natural …
A Cooperative Coevolution Framework For Parallel Learning To Rank, Shuaiqiang Wang, Yun Wu, Byron J. Gao, Ke Wang, Hady W. Lauw, Jun Ma
A Cooperative Coevolution Framework For Parallel Learning To Rank, Shuaiqiang Wang, Yun Wu, Byron J. Gao, Ke Wang, Hady W. Lauw, Jun Ma
Research Collection School Of Computing and Information Systems
We propose CCRank, the first parallel framework for learning to rank based on evolutionary algorithms (EA), aiming to significantly improve learning efficiency while maintaining accuracy. CCRank is based on cooperative coevolution (CC), a divide-and-conquer framework that has demonstrated high promise in function optimization for problems with large search space and complex structures. Moreover, CC naturally allows parallelization of sub-solutions to the decomposed sub-problems, which can substantially boost learning efficiency. With CCRank, we investigate parallel CC in the context of learning to rank. We implement CCRank with three EA-based learning to rank algorithms for demonstration. Extensive experiments on benchmark datasets in …
Building Crowd Movement Model Using Sample-Based Mobility Survey, Larry J. J. Lin, Shih-Fen Cheng, Hoong Chuin Lau
Building Crowd Movement Model Using Sample-Based Mobility Survey, Larry J. J. Lin, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Crowd simulation is a well-studied topic, yet it usually focuses on visualization. In this paper, we study a special class of crowd simulation, where individual agents have diverse backgrounds, ad hoc objectives, and non-repeating visits. Such crowd simulation is particularly useful when modeling human agents movement in leisure settings such as visiting museums or theme parks. In these settings, we are interested in accurately estimating aggregate crowd-related movement statistics. As comprehensive monitoring is usually not feasible for a large crowd, we propose to conduct mobility surveys on only a small group of sampled individuals. We demonstrate via simulation that we …
A Layered Hidden Markov Model For Predicting Human Trajectories In A Multi-Floor Building, Qian Li, Hoong Chuin Lau
A Layered Hidden Markov Model For Predicting Human Trajectories In A Multi-Floor Building, Qian Li, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Tracking and modeling huge amount of users’ movement in a multi-floor building by using wireless devices is a challenging task, due to crowd movement complexity and signal sensing accuracy. In this paper, we use Layered Hidden Markov Model (LHMM) to fit the spatial-temporal trajectories (with large number of missing values). We decompose the problem into distinct layers that Hidden Markov Models (HMMs) are operated at different spatial granularities separately. Baum-Welch algorithm and Viterbi algorithm are used for finding the probable location sequences at each layer. By measuring the predicted result of trajectories, we compared the predicted results of both single …
Mopeye: Monitoring Per-App Network Performance With Zero Measurement Traffic, Daoyuan Wu, Weichao Li, Rocky K. C. Chang, Debin Gao
Mopeye: Monitoring Per-App Network Performance With Zero Measurement Traffic, Daoyuan Wu, Weichao Li, Rocky K. C. Chang, Debin Gao
Research Collection School Of Computing and Information Systems
Mobile network performance measurement is important for understanding mobile user experience, problem diagnosis, and service comparison. A number of crowdsourcing measurement apps (e.g., MobiPerf and Netalyzr) have been embarked for the last few years. Unlike existing apps that use active measurement methods, we employ a novel passive-active approach to continuously monitor per-app network performance on unrooted smartphones without injecting additional network traffic. By leveraging the VpnService API on Android, MopEye, our measurement app, intercepts all network traffic and then relays them to their destinations using socket APIs. Therefore, not only MopEye can measure the round-trip time accurately, it can do …
Learning And Controlling Network Diffusion In Dependent Cascade Models, Jiali Du, Pradeep Varakantham, Akshat Kumar, Shih-Fen Cheng
Learning And Controlling Network Diffusion In Dependent Cascade Models, Jiali Du, Pradeep Varakantham, Akshat Kumar, Shih-Fen Cheng
Research Collection School Of Computing and Information Systems
Diffusion processes have increasingly been used to represent flow of ideas, traffic and diseases in networks. Learning and controlling the diffusion dynamics through management actions has been studied extensively in the context of independent cascade models, where diffusion on outgoing edges from a node are independent of each other. Our work, in contrast, addresses (a) learning diffusion taking management actions to alter the diffusion dynamics to achieve a desired outcome in dependent cascade models. A key characteristic of such dependent cascade models is the flow preservation at all nodes in the network. For example, traffic and people flow is preserved …
Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang
Modeling Social Media Content With Word Vectors For Recommendation, Ying Ding, Jing Jiang
Research Collection School Of Computing and Information Systems
In social media, recommender systems are becoming more and more important. Different techniques have been designed for recommendations under various scenarios, but many of them do not use user-generated content, which potentially reflects users’ opinions and interests. Although a few studies have tried to combine user-generated content with rating or adoption data, they mostly reply on lexical similarity to calculate textual similarity. However, in social media, a diverse range of words is used. This renders the traditional ways of calculating textual similarity ineffective. In this work, we apply vector representation of words to measure the semantic similarity between text. We …
Aesthetic Experience And Acceptance Of Human Computation Games, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Adrian Wei Liang Vu
Aesthetic Experience And Acceptance Of Human Computation Games, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim, Adrian Wei Liang Vu
Research Collection School Of Computing and Information Systems
Human computation games (HCGs) are applications that leverage games to solve computational problems that are out reach of the capacity of computers. Game aesthetics are critical for HCG acceptance, and the game elements should motivate users to contribute time and effort. In this paper, we examine the effect of aesthetic experience on intention to use HCGs. A between-subjects experiment was conducted to compare a HCG and a human computation system (HCS). Results demonstrated that HCGs provided a greater sense of aesthetic experience and attracted more intentional usage than HCSs. Implications of this study are discussed.
Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig
Incremental Dcop Search Algorithms For Solving Dynamic Dcop Problems, William Yeoh, Pradeep Varakantham, Xiaoxun Sun, Sven Koenig
Research Collection School Of Computing and Information Systems
Distributed constraint optimization (DCOP) problems are well-suited for modeling multi-agent coordination problems. However, it only models static problems, which do not change over time. Consequently, researchers have introduced the Dynamic DCOP (DDCOP) model to model dynamic problems. In this paper, we make two key contributions: (a) a procedure to reason with the incremental changes in DDCOPs and (b) an incremental pseudo-tree construction algorithm that can be used by DCOP algorithms such as any-space ADOPT and any-space BnB-ADOPT to solve DDCOPs. Due to the incremental reasoning employed, our experimental results show that any-space ADOPT and any-space BnB-ADOPT are up to 42% …
Active Crowdsourcing For Annotation, Shuji Hao, Chunyan Miao, Steven C. H. Hoi, Peilin Zhao
Active Crowdsourcing For Annotation, Shuji Hao, Chunyan Miao, Steven C. H. Hoi, Peilin Zhao
Research Collection School Of Computing and Information Systems
Crowdsourcing has shown great potential in obtaining large-scale and cheap labels for different tasks. However, obtaining reliable labels is challenging due to several reasons, such as noisy annotators, limited budget and so on. The state-of-the-art approaches, either suffer in some noisy scenarios, or rely on unlimited resources to acquire reliable labels. In this article, we adopt the learning with expert~(AKA worker in crowdsourcing) advice framework to robustly infer accurate labels by considering the reliability of each worker. However, in order to accurately predict the reliability of each worker, traditional learning with expert advice will consult with external oracles~(AKA domain experts) …
Incorporating Analytics Into A Business Process Modelling Course, Gottipati Swapna, Shankararaman, Venky
Incorporating Analytics Into A Business Process Modelling Course, Gottipati Swapna, Shankararaman, Venky
Research Collection School Of Computing and Information Systems
Embedding analytics is about integrating data analytics into operational systems that are part of an organization’s business processes. Currently, most organizations focus on automation business processes and enhancing productivity. However, going forward, in order to stay competitive, organizations have to go beyond automating their processes, by making them more intelligent, by embedding analytics into their processes and business applications. Therefore, there is need for enhancing the knowledge and skills of BPM professionals with know-how on improving a business process by embedding analytics into the workflow. In this paper contribution, the authors share their experience on how an existing process modelling, …
Understanding Psychophysiological Correlates Of User Experience Using Electroencephalogram (Eeg), Fiona Fui-Hoon Nah, Keng Siau, Randall Minas, Nathan W. Twyman, Nicholas A. Rollins, Wenbo Wang, Xi Wang
Understanding Psychophysiological Correlates Of User Experience Using Electroencephalogram (Eeg), Fiona Fui-Hoon Nah, Keng Siau, Randall Minas, Nathan W. Twyman, Nicholas A. Rollins, Wenbo Wang, Xi Wang
Research Collection School Of Computing and Information Systems
The objective of this research is to understand psychophysiological correlates of user experience using electroencephalogram (EEG). We will conduct an experimental study to assess the psychophysiological differences across three states of user experience – flow, boredom, and anxiety – and compare them with the neutral state as a baseline. EEG measurement provides a plethora of data that can be decomposed using different analytical procedures. We will utilize one type of analysis, timefrequency decomposition, to examine changes in frequency (e.g., alpha/beta/theta band) over time. These frequency bands correlate with different cognitive states. In this study, we will use Event Related Spectral …
Flow Experience In Virtual Worlds: Individuals Versus Dyads, Fiona Fui-Hoon Nah, Brenda Eschenbrenner
Flow Experience In Virtual Worlds: Individuals Versus Dyads, Fiona Fui-Hoon Nah, Brenda Eschenbrenner
Research Collection School Of Computing and Information Systems
Flow is a state of mind in which one is deeply absorbed and immersed in an activity to the point where nothing else matters. Although flow can occur in solitary and social contexts, which context fosters greater flow is unclear. Consistent with self-determination theory, dyads working collaboratively achieved higher states of flow than individuals working alone. In other words, dyads achieved higher states of focused concentration and experienced greater temporal dissociation than individuals working alone. Surprisingly and contradictory to previous findings, dyads did not experience greater enjoyment than individuals working alone. We attributed this surprising finding to the hedonic nature …
Bring-Your-Own-Application (Byoa): Optimal Stochastic Application Migration In Mobile Cloud Computing, Jonathan David Chase, Dusit Niyato, Sivadon Chaisiri
Bring-Your-Own-Application (Byoa): Optimal Stochastic Application Migration In Mobile Cloud Computing, Jonathan David Chase, Dusit Niyato, Sivadon Chaisiri
Research Collection School Of Computing and Information Systems
The increasing popularity of using mobile devices in a work context, has led to the need to be able to support more powerful computation. Users no longer remain in an office or at home to conduct their activities, preferring libraries and cafes. In this paper, we consider a mobile cloud computing scenario in which users bring their own mobile devices and are offered a variety of equipment, e.g., desktop computer, smart- TV, or projector, to migrate their applications to, so as to save battery life, improve usability and performance. We formulate a stochastic optimization problem to optimize the allocation of …
Content-Based Visual Landmark Search Via Multimodal Hypergraph Learning, Lei Zhu, Jialie Shen, Hai Jin, Ran Zheng, Liang Xie
Content-Based Visual Landmark Search Via Multimodal Hypergraph Learning, Lei Zhu, Jialie Shen, Hai Jin, Ran Zheng, Liang Xie
Research Collection School Of Computing and Information Systems
While content-based landmark image search has recently received a lot of attention and became a very active domain, it still remains a challenging problem. Among the various reasons, high diverse visual content is the most significant one. It is common that for the same landmark, images with a wide range of visual appearances can be found from different sources and different landmarks may share very similar sets of images. As a consequence, it is very hard to accurately estimate the similarities between the landmarks purely based on single type of visual feature. Moreover, the relationships between landmark images can be …
An Adaptive Markov Strategy For Effective Network Intrusion Detection, Jianye Hao, Yinxing Xue, Mahinthan Chandramohan, Yang Liu, Jun Sun
An Adaptive Markov Strategy For Effective Network Intrusion Detection, Jianye Hao, Yinxing Xue, Mahinthan Chandramohan, Yang Liu, Jun Sun
Research Collection School Of Computing and Information Systems
Network monitoring is an important way to ensure the security of hosts from being attacked by malicious attackers. One challenging problem for network operators is how to distribute the limited monitoring resources (e.g., intrusion detectors) among the network to detect attacks effectively, especially when the attacking strategies can be changing dynamically and unpredictable. To this end, we adopt Markov game to model the interactions between the network operator and the attacker and propose an adaptive Markov strategy (AMS) to determine how the detectors should be placed on the network against possible attacks to minimize the network’s accumulated cost over time. …
Security Slicing For Auditing Xml, Xpath, And Sql Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Lionel Briand
Security Slicing For Auditing Xml, Xpath, And Sql Injection Vulnerabilities, Julian Thome, Lwin Khin Shar, Lionel Briand
Research Collection School Of Computing and Information Systems
XML, XPath, and SQL injection vulnerabilities are among the most common and serious security issues for Web applications and Web services. Thus, it is important for security auditors to ensure that the implemented code is, to the extent possible, free from these vulnerabilities before deployment. Although existing taint analysis approaches could automatically detect potential vulnerabilities in source code, they tend to generate many false warnings. Furthermore, the produced traces, i.e. dataflow paths from input sources to security-sensitive operations, tend to be incomplete or to contain a great deal of irrelevant information. Therefore, it is difficult to identify real vulnerabilities and …
Shopminer: Mining Customer Shopping Behavior In Physical Clothing Stores With Passive Rfids, Longfei Shangguan, Zimu Zhou, Xiaolong Zheng, Lei Yang, Yunhao Liu, Jinsong Han
Shopminer: Mining Customer Shopping Behavior In Physical Clothing Stores With Passive Rfids, Longfei Shangguan, Zimu Zhou, Xiaolong Zheng, Lei Yang, Yunhao Liu, Jinsong Han
Research Collection School Of Computing and Information Systems
Shopping behavior data are of great importance to understand the effectiveness of marketing and merchandising efforts. Online clothing stores are capable capturing customer shopping behavior by analyzing the click stream and customer shopping carts. Retailers with physical clothing stores, however, still lack effective methods to identify comprehensive shopping behaviors. In this paper, we show that backscatter signals of passive RFID tags can be exploited to detect and record how customers browse stores, which items of clothes they pay attention to, and which items of clothes they usually match with. The intuition is that the phase readings of tags attached on …
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Direct Or Indirect Match? Selecting Right Concepts For Zero-Example Case, Yi-Jie Lu, Maaike De Boer, Hao Zhang, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Vireo-Tno @ Trecvid 2015: Multimedia Event Detection, Hao Zhang, Yi-Jie Lu, Maaike De Boer, Frank Ter Haar, Zhaofan Qiu, Klamer Schutte, Wessel Kraaij, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper presents an overview and comparative analysis of our systems designed for the TRECVID 2015 [1] multimedia event detection (MED) task. We submitted 17 runs, of which 5 each for the zeroexample, 10-example and 100-example subtasks for the Pre-Specified (PS) event detection and 2 runs for the 10-example subtask for the Ad-Hoc (AH) event detection. We did not participate in the Interactive Run. This year we focus on three different parts of the MED task: 1) extending the size of our concept bank and combining it with improved dense trajectories; 2) exploring strategies for semantic query generation (SQG); and …
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Multimedia Event Detection: Strong By Integration, Hao Zhang, Maaike De Boer, Yi-Jie Lu, Klamer Schutte, Chong-Wah Ngo, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
No abstract provided.
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Whom Should We Sense In 'Social Sensing' - Analyzing Which Users Work Best For Social Media Now-Casting, Jisun An, Ingmar Weber
Research Collection School Of Computing and Information Systems
Given the ever increasing amount of publicly available social media data, there is growing interest in using online data to study and quantify phenomena in the offline 'real' world. As social media data can be obtained in near real-time and at low cost, it is often used for 'now-casting' indices such as levels of flu activity or unemployment. The term 'social sensing' is often used in this context to describe the idea that users act as 'sensors', publicly reporting their health status or job losses. Sensor activity during a time period is then typically aggregated in a 'one tweet, one …