Erika Fille Legara

Tweeting Supertyphoon Haiyan: Evolving Functions of Twitter during and after a Disaster Event

When disaster events capture global attention users of Twitter form transient interest communities that disseminate information and other messages online. This paper examines content related to Typhoon Haiyan (locally known as Yolanda) as it hit the Philippines and triggered international humanitarian response and media attention. It reveals how Twitter conversations about disasters evolve over time, showing an issue attention cycle on a social media platform. The paper examines different functions of Twitter and the information hubs that drive and sustain conversation about the event. Content analysis shows that the majority of tweets contain information about the typhoon or its damage, and disaster relief activities. There are differences in types of content between the most retweeted messages and posts that are original tweets. Original tweets are more likely to come from ordinary users, who are more likely to tweet emotions, messages of support, and political content compared with official sources and key information hubs that include news organizations, aid organization, and celebrities. Original tweets reveal use of the site beyond information to relief coordination and response.

Inferring Passenger Type from Commuter Eigentravel Matrices

ABSTRACT A sufficient knowledge of the demographics of a commuting public is essential in formulating and implementing more targeted transportation policies. Here, a procedure is demonstrated that classifies passengers (Adult, Child/Student, and Senior Citizen) based on their three-month travel patterns. The method proceeds by constructing distinct commuter matrices, we refer to as eigentravel matrices, that capture a commuters characteristic travel routine. Comparing various classification models, we show that the gradient boosting method gives the best prediction with 76% accuracy, 81% better than the minimum model accuracy (42%) computed using proportional chance criterion. The models are verified and validated; consequently, the procedure demonstrated should serve as a benchmark for problems of this type. The generally intuitive pattern of the demographic classification also points to a possible universal ‘travelprint’ of commuters, and can inspire development of unsupervised machine learning methods for automated fare collection systems that do not provide additional demographic detail.

Simulating Congestion Dynamics of Train Rapid Transit Using Smart Card Data

Investigating congestion in train rapid transit systems (RTS) in todays urban cities is a challenge compounded by limited data availability and difficulties in model validation. Here, we integrate information from travel smart card data, a mathematical model of route choice, and a full-scale agent-based model of the Singapore RTS to provide a more comprehensive understanding of the congestion dynamics than can be obtained through analytical modelling alone. Our model is empirically validated, and allows for close inspection of the dynamics including station crowdedness, average travel duration, and frequency of missed trains---all highly pertinent factors in service quality. Using current data, the crowdedness in all 121 stations appears to be distributed log-normally. In our preliminary scenarios, we investigate the effect of population growth on service quality. We find that the current population (2 million) lies below a critical point; and increasing it beyond a factor of

Mechanism-based model of a mass rapid transit system: A perspective

\sim10\%

Non-invasive Procedure to Probe the Route Choices of Commuters in Rail Transit Systems

leads to an exponential deterioration in service quality. We also predict that incentivizing commuters to avoid the most congested hours can bring modest improvements to the service quality provided the population remains under the critical point. Finally, our model can be used to generate simulated data for analytical modelling when such data are not empirically available, as is often the case.

News Framing Of Population And Family Planning Issues Via Syntactic Network Analysis

In this paper, we discuss our findings on the spatiotemporal dynamics within the mass rapid transit (MRT) system of Singapore. We show that the trip distribution of Origin-Destination (OD) station pairs follows a power-law, implying the existence of critical OD pairs. We then present and discuss the empirically validated agent-based model (ABM) we have developed. The model allows recreation of the observed statistics and the setting up of various scenarios and their effects on the system, such as increasing the commuter population and the propagation of travel delays within the transportation network. The proposed model further enables identification of bottlenecks that can cause the MRT to break down, and consequently provide foresight on how such disruptions can possibly be managed. This can potentially provide a versatile approach for transport planners and government regulators to make quantifiable policies that optimally balance cost and convenience as a function of the number of the commuting public.

Criticality of forcing directions on the fragmentation and resilience of grid networks

Accurately determining the probability of various route choices is critical in understanding the actual spatiotemporal flow of commuters and the instantaneous capacity of trains and stations. Here, we report a novel procedure, based solely on the recorded tap-in tap-out ticketing data, that dictates the route choice of commuters in a rail transit system (RTS). We show that there exists a signature travel time distribution, in the form of Gumbel type 1 function, from a given origin O to a destination D. Any particular route can then be considered as a superposition of this mapping function and one can compute the probability that a specific path, over other possible paths, is taken by a commuter from O to D. The procedure is demonstrated by considering different scenarios using travel data from smart fare cards from Singapores RTS; results show that the forecasted characteristic profile deviates by less than 105 from the actual distribution. We note that our method utilizes only two parameters that can be experimentally accounted for.

On centripetal flows of entities in scale-free networks with nodes of finite capability

Contentious political debates regarding the issues on population and family planning have been perennial over the past four decades especially in developing countries. While its prominence in the public agenda varies depending on other national issues vying for public attention, its presence in policy and political agendas is constant. Here, a computational approach to framing analysis is developed that examines the pattern of media coverage on the population issue in the Philippines. The content of 146 articles sampled from 1988 to 2007 in Manila Bulletin (one of the leading newspapers in the Philippines) is analyzed by creating a syntactic network of concept co-occurrences. The topological properties of the network indicates that the discussion of an article revolves around few central ideas. Moreover, cluster analysis of the network suggests three well-defined frame themes, namely: (1) Development Frame; (2) Maternal Health Frame; and (3) Framing by the Catholic Church. Our results support the thesis that the inability to fruitfully discuss points of contention to reach agreement about suitable population policies in the Philippines is due to the mismatched frames within which it is discussed.

POWER LAW MAPPING IN HUMAN AREA PERCEPTION

A general framework for probing the dynamic evolution of spatial networks comprised of nodes applying force amongst each other is presented. Aside from the already reported magnitude of forces and elongation thresholds, we show that preservation of links in a network is also crucially dependent on how nodes are connected and how edges are directed. We demonstrate that the time it takes for the networks to reach its equilibrium network structure follows a robust power law relationship consistent with Basquins law with an exponent that can be tuned by changing only the force directions. Further, we illustrate that networks with different connection structures, node positions and edge directions have different Basquins exponent which can be used to distinguish spatial directed networks from each other. Using an extensive waiting time simulation that spans up to over 16 orders of magnitude, we establish that the presence of memory combined with the scale-free bursty dynamics of edge breaking at the micro level leads to the evident macroscopic power law distribution of network lifetime.

Earning potential in multilevel marketing enterprises

We examine the transmission of entities from the peripheries of scale-free networks toward their centers when the nodes of the network have finite processing capabilities. We look at varying network utilization, U and find that clogging of the network sets in after a threshold value has been exceeded, and that the congestion sets in at the downstream nodes those nearer to the collector having large numbers of upstream neighbors. Investigation of the question of the degree of correlation of several characteristics of scale-free networks such as the average path length to the collector and the average clustering coefficient with the dynamics of centripetal flow in them reveals a negative answer: any correlation is indirect and will manifest in the number of producer nodes which dictate the effective heaviness of the flow and the interconnectedness of the feeder nodes, those nodes which are immediate neighbors of the collector node. An examination of reinforcement strategies shows dramatic improvements in both the finishing rate, λf and the average total transmission time, when the more centrally-placed nodes are reinforced first, showing that the entities spend a large amount of their lifetime waiting in line at those nodes which constitute the bottlenecks in the network compared to the nodes in the periphery. Our results reinforce the importance of a networks hubs and their immediate environs, and suggest strategies for prioritizing elements of a network for optimization.