Erika Fille Tupas Legara
Sex: Female
Education:
Doctor of Philosophy in Physics Complex Systems, University of the Philippines, 2011
Deep Learning Nanodegree Certification, Udacity, 2017
Non-Degree, Complexity Science, Santa Fe Institute’s Complex Systems Summer School, 2010
Master of Science in Physics, University of the Philippines, 2008
Bachelor of Science in Physics, University of the Philippines, 2006
Field of Specialization
Complex Systems
Network Science
Urban Science
Artificial Intelligence
Computational Physics
Researches:
Article title: Characterisation and comparison of spatial patterns in urban systems: A case study of U.S. cities
Authors: Hoai Nguyen Huynh, Evgeny Makarov, Erika Fille Tupas Legara, Christopher Monterola, et al.
Publication title: Journal of Computational Science 24, December 2017
Abstract:
Understanding the morphology of an urban system is an important step towards unveiling the dynamical processes of its growth and development, which can be achieved through a study of its transportation system. Without doubt, transportation is the foundation of every urban system, and it is a crucial component that enables diverse social and economic functions within a city. In this paper, we studied the spatial pattern of 53 cities in the U.S. by analysing its distribution of public transport points, using a method based upon clusters of percolation known in statistical physics. Our analysis revealed that different spatial distributions of points can generally be classified into four groups with distinctive features: clustered, dispersed, or regularly distributed. From visual inspection, we observed that cities with regularly distributed patterns do not have apparent centre. This is in contrast to the other two types where monocentric (or star-node structure) can be clearly observed. In particular, our results provide quantitative evidence on the existence of two different forms of urban system: well-planned and organically grown. In addition, we had also investigated into the spatial distribution of another important urban entity—the amenities, and found that it possessed universal properties regardless of the city's spatial pattern type. This result has an important implication: urban dynamics cannot be controlled at the local scale even though regulation has been meted out at the scale of the entire urban system. Furthermore, interesting relationships between the distribution of amenities within the city and its spatial pattern are detailed in the paper.
Full text available upon request to the author
Article title: Non-invasive Procedure to Probe the Route Choices of Commuters in Rail Transit Systems
Authors: Christopher Monterola, Erika Fille Tupas Legara, Lee Kk, Pan Di, et al.
Publication title: Procedia Computer Science 80:2387-2391, December 2016
Abstract:
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 Singapore's RTS; results show that the forecasted characteristic profile deviates by less than 10-5 from the actual distribution. We note that our method utilizes only two parameters that can be experimentally accounted for.
Article title: Impacts of land use and amenities on public transport use, urban planning and design
Authors: Hu, Nan, Erika Fille Tupas Legara, Kee Khoon Lee, Terence Gih Guang Hung, et al.
Publication title: Land Use Policy 57, November 2016
Abstract:
Various land-use configurations are known to have wide-ranging effects on the dynamics of and within other city components including the transportation system. In this work, we particularly focus on the complex relationship between land-use and transport offering an innovative approach to the problem by using land-use features at two differing levels of granularity (the more general land-use sector types and the more granular amenity structures) to evaluate their impact on public transit ridership in both time and space. To quantify the interdependencies, we explored three machine learning models and demonstrate that the decision tree model performs best in terms of overall performance—good predictive accuracy, generality, computational efficiency, and “interpretability”. Results also reveal that amenity-related features are better predictors than the more general ones, which suggests that high-resolution geo-information can provide more insights into the dependence of transit ridership on land-use. We then demonstrate how the developed framework can be applied to urban planning for transit-oriented development by exploring practicable scenarios based on Singapore's urban plan toward 2030, which includes the development of “regional centers” (RCs) across the city-state. Results show an initial increase in transit ridership as the amount of amenities is increased. This trend, on the other hand, eventually reverses (particularly during peak hours) with continued strategic increase in amenities; a tipping point at 55% increase is identified where ridership begins to decline and at 110%, the predicted ridership begins to fall below current levels. Our in-silico experiments support one of the medium-term land-use transport goals of stakeholders—to alleviate future strains in the transportation system of Singapore through the development of RCs. The model put forward can serve as a good foundation in building decision-support tools that can assist planners in better strategizing and planning land-use configurations, in particular the amenity resource distribution, to influence and shape public transportation demand.
Article title: Tweeting Supertyphoon Haiyan: Evolving Functions of Twitter during and after a Disaster Event
Authors: Clarissa C. David, Jonathan Corpus Ong, Erika Fille Tupas Legara
Publication title: PLoS ONE 11(3): e0150190, March 2016
Abstract:
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.
Full text available upon request to the author
Article title: Generalized Cross Entropy Method for estimating joint distribution from incomplete information
Authors: Hai-Yan Xu, Shyh-Hao Kuo, Erika Fille Tupas Legara, Guoqi Li, et al.
Publication title: Physica A: Statistical Mechanics and its Applications 453, February 2016
Abstract:
Obtaining a full joint distribution from individual marginal distributions with incomplete information is a non-trivial task that continues to challenge researchers from various domains including economics, demography, and statistics. In this work, we develop a new methodology referred to as “Generalized Cross Entropy Method” (GCEM) that is aimed at addressing the issue. The objective function is proposed to be a weighted sum of divergences between joint distributions and various references. We show that the solution of the GCEM is unique and global optimal. Furthermore, we illustrate the applicability and validity of the method by utilizing it to recover the joint distribution of a household profile of a given administrative region. In particular, we estimate the joint distribution of the household size, household dwelling type, and household home ownership in Singapore. Results show a high-accuracy estimation of the full joint distribution of the household profile under study. Finally, the impact of constraints and weight on the estimation of joint distribution is explored.
Full text available upon request to the author
Article title: How Voters Combine Candidates on the Ballot: The Case of the Philippine Senatorial Elections
Authors: Erika Fille Tupas Legara, Clarissa C. David
Publication title: International Journal of Public Opinion Research 29(1), December 2015
Abstract:
In the Philippines, senators are nationally elected officials, and citizens vote for 12 candidates every three years. The country's electoral features include a weak party system, a low-information environment for voters, and a history of political dynasty rule and preponderance of media celebrities in elected political offices. The article first applies cluster analysis on exit poll data for the 2010 Senatorial Election and then examines predictors of Senatorial candidate sets. Hypotheses are proposed based on theories and evidence that name recall has important consequences in voter decision-making under low information circumstances, and that media celebrities and members of political dynasties benefit from the name recall vote. Findings support predictions that voters put media celebrities and members of national political dynasties together often on a ballot and that the voters who are likely to operate with little information are more likely to vote for these candidates. These are voters with low education and low income, who live in rural areas, and who exhibit high abstention rates. © The Author 2015. Published by Oxford University Press on behalf of The World Association for Public Opinion Research. All rights reserved.
Article title: Inferring Passenger Type from Commuter Eigentravel Matrices
Authors: Erikka Fille Tupas Legara, Christopher P. Monterola
Publication title: Transportmetrica B, August 2015
Abstract:
A sufficient knowledge of the demographics of a commuting public is essential in formulating and implementing more targeted transportation policies, as commuters exhibit different ways of traveling. With the advent of the Automated Fare Collection system (AFC), probing the travel patterns of commuters has become less invasive and more accessible. Consequently, numerous transport studies related to human mobility have shown that these observed patterns allow one to pair individuals with locations and/or activities at certain times of the day. However, classifying commuters using their travel signatures is yet to be thoroughly examined. Here, we contribute to the literature by demonstrating a procedure to characterize passenger types (Adult, Child/Student, and Senior Citizen) based on their three-month travel patterns taken from a smart fare card system. We first establish a method to construct distinct commuter matrices, which we refer to as eigentravel matrices, that capture the characteristic travel routines of individuals. From the eigentravel matrices, we build classification models that predict the type of passengers traveling. Among the models explored, the gradient boosting method (GBM) gives the best prediction accuracy at 76%, which is 84% better than the minimum model accuracy (41%) required vis-\`a-vis the proportional chance criterion. In addition, we find that travel features generated during weekdays have greater predictive power than those on weekends. This work should not only be useful for transport planners, but for market researchers as well. With the awareness of which commuter types are traveling, ads, service announcements, and surveys, among others, can be made more targeted spatiotemporally. Finally, our framework should be effective in creating synthetic populations for use in real-world simulations that involve a metropolitan's public transport system.
Article title: A Data-Driven Agent-Based Model of Congestion and Scaling Dynamics of Rapid Transit Systems
Authors: Nasri Bin Othman, Erika Fille Tupas Legara, Vicknesh Selvam, Christopher Monterola
Publication title: Journal of Computational Science 10, March 2015
Abstract:
Investigating congestion in train rapid transit systems (RTS) in today's 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 congestion and scaling dynamics. By adjusting our model, we can estimate the effective capacity of the RTS trains as well as replicate the penultimate station effect, where commuters travel backwards to the preceding station to catch a seat, sacrificing time for comfort. Using current data, the crowdedness in all 121 stations appears to be distributed log-normally. We find that increasing the current population (2 million) beyond a factor of approximately 10% leads to an exponential deterioration in service quality. We also show that incentivizing commuters to avoid the most congested hours can bring modest improvements to the service quality. Finally, our model can be used to generate simulated data for statistical analysis when such data are not empirically available, as is often the case.
Full text available upon request to the author
Article title: Mechanism-based model of a mass rapid transit system: A perspective
Authors: Erika Fille Tupas Legara, Lee Kee Khoon, Terence Gih Guang Hung, Christopher Monterola
Publication title: International Journal of Modern Physics Conference Series 36:1560011, January 2015
Abstract:
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.
Article title: Criticality of forcing directions on the fragmentation and resilience of grid networks
Authors: Cheryl Abundo, Christopher Monterola, Erika Fille Tupas Legara
Publication title: Scientific Reports 4(1):6195, August 2014
Abstract:
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 Basquin's 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 Basquin's 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.
Article title: Critical capacity, travel time delays and travel time distribution of rapid mass transit systems
Authors: Erika Fille Tupas Legara, Christopher Monterola, Kee Khoon Lee, Terence Gih Guang Hung
Publication title: Physica A: Statistical Mechanics and its Applications 406:100-106, July 2014
Abstract:
We set up a mechanistic agent-based model of a rapid mass transit system. Using empirical data from Singapore’s unidentifiable smart fare card, we validate our model by reconstructing actual travel demand and duration of travel statistics. We subsequently use this model to investigate two phenomena that are known to significantly affect the dynamics within the RTS: (1) overloading in trains and (2) overcrowding in the RTS platform. We demonstrate that by varying the loading capacity of trains, a tipping point emerges at which an exponential increase in the duration of travel time delays is observed. We also probe the impact on the rail system dynamics of three types of passenger growth distribution across stations: (i) Dirac delta, (ii) uniform and (iii) geometric, which is reminiscent of the effect of land use on transport. Under the assumption of a fixed loading capacity, we demonstrate the dependence of a given origin–destination (OD) pair on the flow volume of commuters in station platforms.
Full text available upon request to the author
Article title: On Centripetal Flows of Entities in Scale-Free Networks with Nodes of Finite Capability
Authors: Jesus Feliz Valenzuela, Christopher Monterola, Erika Fille Tupas Legara, Xiuju Fu, et al.
Publication title: Complexity 21(1), July 2014
Abstract:
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 <l(min)> 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, 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 network's hubs and their immediate environs, and suggest strategies for prioritizing elements of a network for optimization. © 2014 Wiley Periodicals, Inc. Complexity, 2014
Full text available upon request to the author
Article title: A network perspective on the calamity, induced inaccessibility of communities and the robustness of centralized, landbound relief efforts
Authors: Jesus Felix Valenzuela, Erika Fille Tupas Legara, Xiuju Fu, Rick Siow Mong Goh, et al.
Publication title: International Journal of Modern Physics C 25(6), March 2014
Abstract:
We examine the robustness of centralized, landbound relief operations' capability to promptly reach areas affected by a disaster event from a network perspective. We initially look at two idealized road networks: a two-dimensional grid and a scale-free network, and compare them to an actual road network obtained from OpenStreetMap. We show that, from a node designated as the center for relief operations (a "relief center"), damage to a road network causes a substantial fraction of the other nodes (about 20% in the three networks we examined) to become initially inaccessible from any relief effort, although the remaining majority can still be reached readily. Furthermore, we show the presence of a threshold in the two idealized road networks but not in the real one. Below this threshold, all nodes can robustly be reached in a short span of time, and above it, not only the partitioning mentioned above sets in, but also the time needed to reach the nodes becomes susceptible to the amount of damage sustained by the road network. Under damage sustained by random segments of the network, this threshold is higher in the scale-free network compared to the grid, due to the robustness of the former against random attacks. Our results may be of importance in formulating contingency plans for the logistics of disaster relief operations.
Full text available upon request to the author
Article title: Simulating Congestion Dynamics of Train Rapid Transit Using Smart Card Data
Authors: Nasri Bin Othman, Erika Fille Tupas Legara, Vicknesh Selvam, Christopher Monterola
Publication title: Procedia Computer Science 29, February 2014
Abstract:
Investigating congestion in train rapid transit systems (RTS) in today's 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 $\sim10\%$ 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.
Article title: News Frames of the Population Issue in the Philippines
Authors: Clarissa C. David, Erika Fille Tupas Legara, Jenna Mae Atun, Christopher P. Monterola
Publication title: International Journal of Communication 8(1): 1247-1267, January 2014
Abstract:
Using automated semantic network analysis, this study examines media framing of the population issue in the Philippines through the different labels used to refer to it in public discourse. The population issue has been relabeled and repackaged in legislation and other policy documents. This article examines how each relabeling of the issue was reflected in the media. Analysis of news articles published from 1987 to 2007 reveals that word clusters around each label reflect strategic framing of the terms population control, population management, family planning, reproductive health, responsible parenthood, and pro-life. Whereas population control and population management are associated with developmental and economic goals, reproductive health and family planning are more linked with women's and youth's health issues. The terms responsible parenthood and pro-life are mostly identified with the Catholic Church, with the latter more identified with positions on abortion and contraception.
Full text available upon request to the author
Article title: Complex network tools in building expert systems that perform framing analysis
Authors: Erika Fille Tupas Legara, Christopher P. Monterola, Clarissa David
Publication title: Expert Systems with Applications 40(11): 4600-4608, September 2013
Abstract:
Framing, in its specific application to media research, is defined as the “central organizing idea for making sense of an issue or conflict and suggesting what is at stake.” It can be found in various disciplines of the social sciences, most notably in political science, psychology, and communication research. Due to the fuzzy nature of frames, identifying them has proven to be quite complex. Here, we perform framing analysis on a corpus of news texts on the population and family planning issue in the Philippines by operating two varying approaches: human-based and computer-assisted. A singular holistic approach to framing is initially implemented where coders/domain experts classify each news text to a specific pre-defined frame. This traditional approach is known to raise serious issues on the reliability and validity of the results mainly due to human’s intrinsic biases. To address such issues, we propose a novel technique that synergically combines the method of Matthes and Kohring (2008) and complex networks approach. In our model, the codings of texts are cast as a network of content analytic variables (CAVs). Our proposed method tackles the clustering issue that MK raised, which plagues framing scholars in the quantitative identification of news frames in texts. Moreover, the research is significant on a societal level as it also aims to gain perspective for reasons on the lack of progress in discussions about suitable population policies in most developing countries like the Philippines.
Full text available upon request to the author
Article title: Finding Frames: Comparing Two Methods of Frame Analysis
Authors: Clarissa C. David, Jenna Mae Atun, Erika Fille Tupas Legara, Christopher Monterola
Publication title: Communication Methods and Measures 5(4): 329-351, December 2011
Abstract:
Detecting media frames has spawned a variety of methods, but very little has been done to investigate whether these methods provide comparable results. This article compares the results of two kinds of human coding framing analysis. The first is a method developed by Matthes and Kohring (2008) involving human coding of elements based on Entman's (1993) definition of frames, and the second coding is based on an extracted set of frames. Cluster analysis of news articles on population published from 1987–2007 in the Philippines yielded an optimum number of three communities or frames that agree with the holistic predetermined frames. Results indicate support for the validity of both procedures. Methodological implications are further discussed.
Article title: Power Law Mapping in Human Area Perception
Authors: Anthony Longjas, Erika Fille Tupas Legara, Christopher Monterola
Publication title: International Journal of Modern Physics C 22(5):495-503, May 2011
Abstract:
We investigate how humans visually perceive and approximate area or space allocation through visual area experiments. The participants are asked to draw a circle concentric to the reference circle on the monitor screen using a computer mouse with area measurements relative to the area of the reference circle. The activity is repeated for triangle, square and hexagon. The area estimated corresponds to the area estimates of a participant (perceived) for a corresponding requested area to be drawn (stimulus). The area estimated fits very well (goodness of fit R2 > 0.97) to a power law given by r2alpha where r is the radius of the circle or the distance of the edge for triangle, square and hexagon. The power law fit demonstrates that for all shapes sampled, participants underestimated area for stimulus that are less than ~100% of the reference area and overestimated area for stimulus greater than ~100% of the reference area. The value of alpha is smallest for the circle (alphao ≈ 1.33) and largest for triangle (alpha△ ≈ 1.56) indicating that in the presence of a reference area with the same shape, circle is perceived to be smallest among the figures considered when drawn bigger than the reference area, but largest when drawn smaller than the reference area. We also conducted experiments on length estimation and consistent with the results of Dehaene et al., Science 2008, we recover a linear relationship between the perceived length and the stimulus. We show that contrary to number mapping into space and/or length perception, human's perception of area is not corrected by the introduction of cultural interventions such as formal education.
Article title: Ranking of predictor variables based on effect size criterion provides an accurate means of automatically classifying opinion column articles
Authors: Erika Fille Tupas Legara, Christopher Monterola, Cheryl Abundo
Publication title: Physica A: Statistical Mechanics and its Applications 390(1): 110-119, January 2011
Abstract:
We demonstrate an accurate procedure based on linear discriminant analysis that allows automatic authorship classification of opinion column articles. First, we extract the following stylometric features of 157 column articles from four authors: statistics on high frequency words, number of words per sentence, and number of sentences per paragraph. Then, by systematically ranking these features based on an effect size criterion, we show that we can achieve an average classification accuracy of 93% for the test set. In comparison, frequency size based ranking has an average accuracy of 80%. The highest possible average classification accuracy of our data merely relying on chance is ∼31%. By carrying out sensitivity analysis, we show that the effect size criterion is superior than frequency ranking because there exist low frequency words that significantly contribute to successful author discrimination. Consistent results are seen when the procedure is applied in classifying the undisputed Federalist papers of Alexander Hamilton and James Madison. To the best of our knowledge, the work is the first attempt in classifying opinion column articles, that by virtue of being shorter in length (as compared to novels or short stories), are more prone to over-fitting issues. The near perfect classification for the longer papers supports this claim. Our results provide an important insight on authorship attribution that has been overlooked in previous studies: that ranking discriminant variables based on word frequency counts is not necessarily an optimal procedure.
Full text available upon request to the author
Article title: News Framing of Population and Family Planning Issues via Syntactic Network Analysis
Authors: Erika Fille Tupas Legara, Christopher Monterola, Clarissa David, Jenna Mae Atun
Publication title: International Journal of Modern Physics C 21 (1): 51-65, January 2010
Abstract:
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.
Full text available upon request to the author
Article title: Competition in a Social Structure
Authors: Erika Fille Tupas Legara, Anthony Longjas, Rene Batac
Publication title: International Journal of Modern Physics C 20(01):1-7, January 2009
Abstract:
Complex adaptive agents develop strategies in the presence of competition. In modern human societies, there is an inherent sense of locality when describing inter-agent dynamics because of its network structure. One then wonders whether the traditional advertising schemes that are globally publicized and target random individuals are as effective in attracting a larger portion of the population as those that take advantage of local neighborhoods, such as "word-of-mouth" marketing schemes. Here, we demonstrate using a differential equation model that schemes targeting local cliques within the network are more successful at gaining a larger share of the population than those that target users randomly at a global scale (e.g., television commercials, print ads, etc.). This suggests that success in the competition is dependent not only on the number of individuals in the population but also on how they are connected in the network. We further show that the model is general in nature by considering examples of competition dynamics, particularly those of business competition and language death.
Full text available upon request to the author
Article title: Earning potential in multilevel marketing enterprises
Authors: Erika Fille Tupas Legara, Christopher Monterola, Dranreb Earl Juanico, Marisciel Litong-Palima, et al.
Publication title: Physica A: Statistical Mechanics and its Applications 387(19): 4889-4895, August 2008
Abstract:
Government regulators and other concerned citizens warily view multilevel marketing enterprises (MLM) because of their close operational resemblance to exploitative pyramid schemes. We analyze two types of MLM network architectures — the unilevel and binary, in terms of growth behavior and earning potential among members. We show that network growth decelerates after reaching a size threshold, contrary to claims of unrestricted growth by MLM recruiters. We have also found that the earning potential in binary MLM’s obey the Pareto “80 20” rule, implying an earning opportunity that is strongly biased against the most recent members. On the other hand, unilevel MLM’s do not exhibit the Pareto earning distribution and earning potential is independent of member position in the network. Our analytical results agree well with field data taken from real-world MLM’s in the Philippines. Our analysis is generally valid and can be applied to other MLM architectures.
Full text available upon request to the author