| 1. |
- Liao, Yuan, 1991, et al.
(författare)
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Impacts of charging behavior on BEV charging infrastructure needs and energy use
- 2023
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Ingår i: Transportation Research Part D: Transport and Environment. - : Elsevier BV. - 1361-9209. ; 116
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Tidskriftsartikel (refereegranskat)abstract
- Battery electric vehicles (BEVs) are vital in the sustainable future of transport systems. Increased BEV adoption makes the realistic assessment of charging infrastructure demand critical. The current literature on charging infrastructure often uses outdated charging behavior assumptions such as universal access to home chargers and the "Liquid-fuel" mental model. We simulate charging infrastructure needs using a large-scale agent-based simulation of Sweden with detailed individual characteristics, including dwelling types and activity patterns. The two state-of-art archetypes of charging behaviors, "Plan-ahead" and "Event-triggered," mirror the current infrastructure built-up, suggesting 2.3-4.5 times more public chargers per BEV than the "Liquid-fuel" mental model. We also estimate roughly 30-150 BEVs served by a slow charger may be needed for non-home residential overnight charging.
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| 2. |
- Tozluoglu, Çaglar, 1988, et al.
(författare)
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A synthetic population of Sweden: datasets of agents, households, and activity-travel patterns
- 2023
-
Ingår i: Data in Brief. - 2352-3409. ; 48
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Tidskriftsartikel (refereegranskat)abstract
- A synthetic population is a simplified microscopic representation of an actual population. Statistically representative at the population level, it provides valuable inputs to simulation models (especially agent-based models) in research areas such as transportation, land use, economics, and epidemiology. This article describes the datasets from the Synthetic Sweden Mobility (SySMo) model using the state-of-art methodology, including machine learning (ML), iterative proportional fitting (IPF), and probabilistic sampling. The model provides a synthetic replica of over 10 million Swedish individuals (i.e., agents), their household characteristics, and activity-travel plans. This paper briefly explains the methodology for the three datasets: Person, Households, and Activity-travel patterns. Each agent contains socio-demographic attributes, such as age, gender, civil status, residential zone, personal income, car ownership, employment, etc. Each agent also has a household and corresponding attributes such as household size, number of children ≤ 6 years old, etc. These characteristics are the basis for the agents’ daily activity-travel schedule, including type of activity, start-end time, duration, sequence, the location of each activity, and the travel mode between activities.
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| 3. |
- Tozluoglu, Çaglar, 1988, et al.
(författare)
-
Synthetic Sweden Mobility (SySMo) Model Documentation
- 2022
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This document describes a decision support framework using a combination of several state-of-the-art computing tools and techniques in synthetic information systems, and large-scale agent-based simulations. In this work, we create a synthetic population of Sweden and their mobility patterns that are composed of three major components: population synthesis, activity generation, and location assignment. The document describes the model structure, assumptions, and validation of results.
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| 4. |
- Altman, Eitan, et al.
(författare)
-
Blockchain Competition Between Miners: A Game Theoretic Perspective
- 2020
-
Ingår i: Frontiers in Blockchain. - : Frontiers Media SA. - 2624-7852. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- We model the competition over mining resources and over several cryptocurrencies as a non-cooperative game. Leveraging results about congestion games, we establish conditions for the existence of pure Nash equilibria and provide efficient algorithms for finding such equilibria. We account for multiple system models, varying according to the way that mining resources are allocated and shared and according to the granularity at which mining puzzle complexity is adjusted. When constraints on resources are included, the resulting game is a constrained resource allocation game for which we characterize a normalized Nash equilibrium. Under the proposed models, we provide structural properties of the corresponding types of equilibrium, e.g., establishing conditions under which at most two mining infrastructures will be active or under which no miners will have incentives to mine a given cryptocurrency.
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| 5. |
- Altman, Eitan, et al.
(författare)
-
Mining Competition in a Multi-Cryptocurrency Ecosystem at the Network Edge: A Congestion Game Approach
- 2019
-
Ingår i: Performance Evaluation Review. - : Association for Computing Machinery (ACM). - 0163-5999. ; 46:3, s. 114-117
-
Tidskriftsartikel (refereegranskat)abstract
- We model the competition over several blockchains characterizing multiple cryptocurrencies as a non-cooperative game. Then, we specialize our results to two instances of the general game, showing properties of the Nash equilibrium. In particular, leveraging results about congestion games, we establish the existence of pure Nash equilibria and provide efficient algorithms for finding such equilibria.
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| 6. |
- Das, Shantanu, et al.
(författare)
-
Individual Fairness in Feature-Based Pricing for Monopoly Markets
- 2022
-
Ingår i: UAI 2022 - Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence. ; PMLR 180, s. 486-795
-
Konferensbidrag (refereegranskat)abstract
- We study fairness in the context of feature-based price discrimination in monopoly markets. We propose a new notion of individual fairness, namely, \alpha-fairness, which guarantees that individuals with similar features face similar prices. First, we study discrete valuation space and give an analytical solution for optimal fair feature-based pricing. We show that the cost of fair pricing is defined as the ratio of expected revenue in an optimal feature-based pricing to the expected revenue in an optimal fair feature-based pricing (CoF) can be arbitrarily large in general. When the revenue function is continuous and concave with respect to the prices, we show that one can achieve CoF strictly less than 2, irrespective of the model parameters. Finally, we provide an algorithm to compute fair feature-based pricing strategy that achieves this CoF.
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| 7. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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A Multi-phase Approach for Improving Information Diffusion in Social Networks
- 2015
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Ingår i: AAMAS 2015 - Proceedings of the 14th International Conference on Autonomous Agents and MultiAgent Systems. - 9781450334136 ; , s. 1787-1788
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Konferensbidrag (refereegranskat)abstract
- For maximizing influence spread in a social network, given a certain budget on the number of seed nodes, we investigate the effects of selecting and activating the seed nodes in multiple phases. In particular, we formulate an appropriate objective function for two-phase influence maximization under the independent cascade model, investigate its properties, and propose algorithms for determining the seed nodes in the two phases. We also study the problem of determining an optimal budget-split and delay between the two phases.
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| 8. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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A Two Phase Investment Game for Competitive Opinion Dynamics in Social Networks
- 2020
-
Ingår i: Information Processing and Management. - : Elsevier BV. - 0306-4573. ; 57:2
-
Tidskriftsartikel (refereegranskat)abstract
- We propose a setting for two-phase opinion dynamics in social networks, where a node's final opinion in the first phase acts as its initial biased opinion in the second phase. In this setting, we study the problem of two camps aiming to maximize adoption of their respective opinions, by strategically investing on nodes in the two phases. A node's initial opinion in the second phase naturally plays a key role in determining the final opinion of that node, and hence also of other nodes in the network due to its influence on them. However, more importantly, this bias also determines the effectiveness of a camp's investment on that node in the second phase. In order to formalize this two-phase investment setting, we propose an extension of Friedkin-Johnsen model, and hence formulate the utility functions of the camps. We arrive at a decision parameter which can be interpreted as two-phase Katz centrality. There is a natural tradeoff while splitting the available budget between the two phases. A lower investment in the first phase results in worse initial biases in the network for the second phase. On the other hand, a higher investment in the first phase spares a lower available budget for the second phase, resulting in an inability to fully harness the influenced biases. We first analyze the non-competitive case where only one camp invests, for which we present a polynomial time algorithm for determining an optimal way to split the camp's budget between the two phases. We then analyze the case of competing camps, where we show the existence of Nash equilibrium and that it can be computed in polynomial time under reasonable assumptions. We conclude our study with simulations on real-world network datasets, in order to quantify the effects of the initial biases and the weightage attributed by nodes to their initial biases, as well as that of a camp deviating from its equilibrium strategy. Our main conclusion is that, if nodes attribute high weightage to their initial biases, it is advantageous to have a high investment in the first phase, so as to effectively influence the biases to be harnessed in the second phase.
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| 9. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
A Two Phase Investment Game for Competitive Opinion Dynamics in Social Networks
- 2020
-
Ingår i: ALA 2020 - Adaptive and Learning Agents Workshop at AAMAS 2020.
-
Konferensbidrag (refereegranskat)abstract
- We study the problem of two competing camps aiming to maximize the adoption of their respective opinions, by optimally investing in nodes of a social network in two phases. The final opinion of a node in phase 1 acts as its bias in phase 2, and this bias determines the effectiveness of a camp’s investment on the node. Using an extension of Friedkin-Johnsen model of opinion dynamics, we formulate the camps’ utility functions. We show the existence and polynomial time computability of Nash equilibrium under reasonable assumptions. Using simulations, we quantify the effects of the nodes’ biases and the weightage attributed to them, as well as that of a camp deviating from its equilibrium strategy.
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| 10. |
- Dhamal, Swapnil Vilas, 1988
(författare)
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An Integrated Framework for Competitive Multi-channel Marketing of Multi-featured Products
- 2019
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Ingår i: COMSNETS 2019 - Proceedings of the 11th International Conference on Communication Systems & Networks. ; , s. 391-394
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Konferensbidrag (refereegranskat)abstract
- For any company, multiple channels are available for reaching a population in order to market its products. Some of the most well-known channels are (a) mass media advertisement, (b) recommendations using social advertisement, and (c) viral marketing using social networks. The company would want to maximize its reach while also accounting for simultaneous marketing of competing products, where the product marketings may not be independent. In this direction, we propose and analyze a multi-featured generalization of the classical linear threshold model. We hence develop a framework for integrating the considered marketing channels into the social network, and an approach for allocating budget among these channels.
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| 11. |
- Dhamal, Swapnil Vilas, 1988
(författare)
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Effectiveness of Diffusing Information through a Social Network in Multiple Phases
- 2018
-
Ingår i: 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings. - 2576-6813 .- 2334-0983. ; , s. 1-7
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Konferensbidrag (refereegranskat)abstract
- We study the effectiveness of using multiple phases for maximizing the extent of information diffusion through a social network, and present insights while considering various aspects. In particular, we focus on the independent cascade model with the possibility of adaptively selecting seed nodes in multiple phases based on the observed diffusion in preceding phases, and conduct a detailed simulation study on real-world network datasets and various values of seeding budgets. We first present a negative result that more phases do not guarantee a better spread, however the adaptability advantage of more phases generally leads to a better spread in practice, as observed on real-world datasets. We study how diffusing in multiple phases affects the mean and standard deviation of the distribution representing the extent of diffusion. We then study how the number of phases impacts the effectiveness of multiphase diffusion, how the diffusion progresses phase-by-phase, and what is an optimal way to split the total seeding budget across phases. Our experiments suggest a significant gain when we move from single phase to two phases, and an appreciable gain when we further move to three phases, but the marginal gain thereafter is usually not very significant. Our main conclusion is that, given the number of phases, an optimal way to split the budget across phases is such that the number of nodes influenced in each phase is almost the same.
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| 12. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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Formation of Stable Strategic Networks with Desired Topologies
- 2015
-
Ingår i: Studies in Microeconomics. - : SAGE Publications. - 2321-0222 .- 2321-8398. ; 3:2, s. 158-213
-
Tidskriftsartikel (refereegranskat)abstract
- Many real-world networks, such as social networks, consist of strategic agents. The topology of these networks often plays a crucial role in determining the ease and speed with which certain information-driven tasks can be accomplished. Consequently, growing a stable network of a certain desired topology is of interest. Motivated by this, we study the following important problem: Given a certain desired topology, under what conditions would best response link alteration strategies adopted by strategic agents lead to formation of a stable network having the given topology and no other topology. This problem is the inverse of the classical network formation problem where we are concerned with determining stable topologies, given the conditions on the network parameters. We study this interesting inverse problem by proposing (1) a recursive model of network formation and (2) a utility model that captures key determinants of network formation. Building upon these models, we explore relevant topologies such as star graph complete graph, bipartite Turán graph, and multiple stars with interconnected centres. We derive a set of sufficient conditions under which these topologies uniquely emerge, study their social welfare properties and investigate the effects of deviating from the derived conditions.
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| 13. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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Forming Networks of Strategic Agents with Desired Topologies
- 2012
-
Ingår i: WINE 2012 - Proceedings of the 8th International Conference on Internet and Network Economics. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642353109 ; , s. 504-511
-
Konferensbidrag (refereegranskat)abstract
- Many networks such as social networks and organizational networks in global companies consist of self-interested agents. The topology of these networks often plays a crucial role in important tasks such as information diffusion and information extraction. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a stable network having that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation and a utility model that captures many key features. Based on this model, we analyze relevant network topologies and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks, wherein no node wants to delete any of its links and no two nodes would want to create a link between them.
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| 14. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Information Diffusion in Social Networks in Two Phases
- 2016
-
Ingår i: IEEE Transactions on Network Science and Engineering. - 2327-4697. ; 3:4, s. 197-210
-
Tidskriftsartikel (refereegranskat)abstract
- The problem of maximizing information diffusion, given a certain budget expressed in terms of the number of seed nodes, is an important topic in social networks research. Existing literature focuses on single phase diffusion where all seed nodes are selected at the beginning of diffusion and all the selected nodes are activated simultaneously. This paper undertakes a detailed investigation of the effect of selecting and activating seed nodes in multiple phases. Specifically, we study diffusion in two phases assuming the well-studied independent cascade model. First, we formulate an objective function for two-phase diffusion, investigate its properties, and propose efficient algorithms for finding seed nodes in the two phases. Next, we study two associated problems: (1) budget splitting which seeks to optimally split the total budget between the two phases and (2) scheduling which seeks to determine an optimal delay after which to commence the second phase. Our main conclusions include: (a) under strict temporal constraints, use single phase diffusion, (b) under moderate temporal constraints, use two-phase diffusion with a short delay while allocating most of the budget to the first phase, and (c) when there are no temporal constraints, use two-phase diffusion with a long delay while allocating roughly one-third of the budget to the first phase.
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| 15. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Investment Strategies for Competing Camps in a Social Network: A Broad Framework
- 2019
-
Ingår i: IEEE Transactions on Network Science and Engineering. - 2327-4697. ; 6:4, s. 628-645
-
Tidskriftsartikel (refereegranskat)abstract
- We study the problem of optimally investing in nodes of a social network in a competitive setting, wherein two camps aim to drive the average opinion of the population in their own favor. Using a well-established model of opinion dynamics, we formulate the problem as a zero-sum game with its players being the two camps. We derive optimal investment strategies for both camps, and show that a random investment strategy is optimal when the underlying network follows a popular class of weight distributions. We study a broad framework, where we consider various well-motivated settings of the problem, namely, when the influence of a camp on a node is a concave function of its investment on that node, when a camp aims at maximizing competitor's investment or deviation from its desired investment, and when one of the camps has uncertain information about the values of the model parameters. We also study a Stackelberg variant of this game under common coupled constraints on the combined investments by the camps and derive their equilibrium strategies, and hence quantify the first-mover advantage. For a quantitative and illustrative study, we conduct simulations on real-world datasets and provide results and insights.
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| 16. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Modeling Spread of Preferences in Social Networks for Sampling-based Preference Aggregation
- 2019
-
Ingår i: IEEE Transactions on Network Science and Engineering. - 2327-4697. ; 6:1, s. 46-59
-
Tidskriftsartikel (refereegranskat)abstract
- Given a large population, it is an intensive task to gather individual preferences over a set of alternatives and arrive at an aggregate or collective preference of the population. We show that social network underlying the population can be harnessed to accomplish this task effectively, by sampling preferences of a small subset of representative nodes. We first develop a Facebook app to create a dataset consisting of preferences of nodes and the underlying social network, using which, we develop models that capture how preferences are distributed among nodes in a typical social network. We hence propose an appropriate objective function for the problem of selecting best representative nodes. We devise two algorithms, namely, Greedy-min which provides a performance guarantee for a wide class of popular voting rules, and Greedy-sum which exhibits excellent performance in practice. We compare the performance of these proposed algorithms against random-polling and popular centrality measures, and provide a detailed analysis of the obtained results. Our analysis suggests that selecting representatives using social network information is advantageous for aggregating preferences related to personal topics (e.g., lifestyle), while random polling with a reasonable sample size is good enough for aggregating preferences related to social topics (e.g., government policies).
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| 17. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Optimal Multiphase Investment Strategies for Influencing Opinions in a Social Network
- 2018
-
Ingår i: AAMAS 2018 - Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems. ; , s. 1927-1929
-
Konferensbidrag (refereegranskat)abstract
- We study the problem of two competing camps aiming to maximize the adoption of their respective opinions, by optimally investing in nodes of a social network in multiple phases. The final opinion of a node in a phase acts as its biased opinion in the following phase. Using an extension of Friedkin-Johnsen model, we formulate the camps' utility functions, which we show to involve what can be interpreted as multiphase Katz centrality. We hence present optimal investment strategies of the camps, and the loss incurred if myopic strategy is employed. Simulations affirm that nodes attributing higher weightage to bias necessitate higher investment in initial phase. The extended version of this paper analyzes a setting where a camp's influence on a node depends on the node's bias; we show existence and polynomial time computability of Nash equilibrium.
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| 18. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Resource Allocation Polytope Games: Uniqueness of Equilibrium, Price of Stability, and Price of Anarchy
- 2018
-
Ingår i: AAAI 2018 - Proceedings of the 32nd AAAI Conference on Artificial Intelligence. ; , s. 997-1006
-
Konferensbidrag (refereegranskat)abstract
- We consider a two-player resource allocation polytope game, in which the strategy of a player is restricted by the strategy of the other player, with common coupled constraints. With respect to such a game, we formally introduce the notions of independent optimal strategy profile, which is the profile when players play optimally in the absence of the other player; and common contiguous set, which is the set of top nodes in the preference orderings of both the players that are exhaustively invested on in the independent optimal strategy profile. We show that for the game to have a unique PSNE, it is a necessary and sufficient condition that the independent optimal strategies of the players do not conflict, and either the common contiguous set consists of at most one node or all the nodes in the common contiguous set are invested on by only one player in the independent optimal strategy profile. We further derive a socially optimal strategy profile, and show that the price of anarchy cannot be bound by a common universal constant. We hence present an efficient algorithm to compute the price of anarchy and the price of stability, given an instance of the game. Under reasonable conditions, we show that the price of stability is 1. We encounter a paradox in this game that higher budgets may lead to worse outcomes.
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| 19. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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Scalable Preference Aggregation in Social Networks
- 2013
-
Ingår i: HCOMP 2013 - Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing. ; , s. 42-50
-
Konferensbidrag (refereegranskat)abstract
- In social choice theory, preference aggregation refers to computing an aggregate preference over a set of alternatives given individual preferences of all the agents. In real-world scenarios, it may not be feasible to gather preferences from all the agents. Moreover, determining the aggregate preference is computationally intensive. In this paper, we show that the aggregate preference of the agents in a social network can be computed efficiently and with sufficient accuracy using preferences elicited from a small subset of critical nodes in the network. Our methodology uses a model developed based on real-world data obtained using a survey on human subjects, and exploits network structure and homophily of relationships. Our approach guarantees good performance for aggregation rules that satisfy a property which we call expected weak insensitivity. We demonstrate empirically that many practically relevant aggregation rules satisfy this property. We also show that two natural objective functions in this context satisfy certain properties, which makes our methodology attractive for scalable preference aggregation over large scale social networks. We conclude that our approach is superior to random polling while aggregating preferences related to individualistic metrics, whereas random polling is acceptable in the case of social metrics.
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| 20. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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Strategic Investments in Distributed Computing: A Stochastic Game Perspective
- 2022
-
Ingår i: Journal of Parallel and Distributed Computing. - : Elsevier BV. - 1096-0848 .- 0743-7315. ; 169, s. 317-333
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Tidskriftsartikel (refereegranskat)abstract
- We study a stochastic game with a dynamic set of players, for modeling and analyzing their computational investment strategies in distributed computing. Players obtain a certain reward for solving a problem, while incurring a certain cost based on the invested time and computational power. We present our framework while considering a contemporary application of blockchain mining, and show that the framework is applicable to certain other distributed computing settings as well. For an in-depth analysis, we consider a particular yet natural scenario where the rate of solving the problem is proportional to the total computational power invested by the players. We show that, in Markov perfect equilibrium, players with cost parameters exceeding a certain threshold, do not invest; while those with cost parameters less than this threshold, invest maximal power. We arrive at an interesting conclusion that the players need not have information about the system state as well as each others' parameters, namely, cost parameters and arrival/departure rates. With extensive simulations and insights through mean field approximation, we study the effects of players' arrival/departure rates and the system parameters on the players' utilities.
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| 21. |
- Ghalme, Ganesh, et al.
(författare)
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Ballooning Multi-Armed Bandits
- 2020
-
Ingår i: Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS. - 1548-8403 .- 1558-2914. ; , s. 1849-1851
-
Konferensbidrag (refereegranskat)abstract
- We introduce ballooning multi-armed bandits (BL-MAB), a novel extension to the classical stochastic MAB model. In the BL-MAB model, the set of available arms grows (or balloons) over time. The regret in a BL-MAB setting is computed with respect to the best available arm at each time. We first observe that the existing stochastic MAB algorithms are not regret-optimal for the BL-MAB model. We show that if the best arm is equally likely to arrive at any time, a sub-linear regret cannot be achieved, irrespective of the arrival of other arms. We further show that if the best arm is more likely to arrive in the early rounds, one can achieve sub-linear regret. Making reasonable assumptions on the arrival distribution of the best arm in terms of the thinness of the distribution's tail, we prove that the proposed algorithm achieves sub-linear instance-independent regret. We further quantify explicit dependence of regret on the arrival distribution parameters.
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| 22. |
- Ghalme, Ganesh, et al.
(författare)
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Ballooning multi-armed bandits
- 2021
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Ingår i: Artificial Intelligence. - : Elsevier BV. - 0004-3702. ; 296
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, we introduce ballooning multi-armed bandits (BL-MAB), a novel extension of the classical stochastic MAB model. In the BL-MAB model, the set of available arms grows (or balloons) over time. In contrast to the classical MAB setting where the regret is computed with respect to the best arm overall, the regret in a BL-MAB setting is computed with respect to the best available arm at each time. We first observe that the existing stochastic MAB algorithms result in linear regret for the BL-MAB model. We prove that, if the best arm is equally likely to arrive at any time instant, a sub-linear regret cannot be achieved. Next, we show that if the best arm is more likely to arrive in the early rounds, one can achieve sub-linear regret. Our proposed algorithm determines (1) the fraction of the time horizon for which the newly arriving arms should be explored and (2) the sequence of arm pulls in the exploitation phase from among the explored arms. Making reasonable assumptions on the arrival distribution of the best arm in terms of the thinness of the distribution's tail, we prove that the proposed algorithm achieves sub-linear instance-independent regret. We further quantify explicit dependence of regret on the arrival distribution parameters. We reinforce our theoretical findings with extensive simulation results. We conclude by showing that our algorithm would achieve sub-linear regret even if (a) the distributional parameters are not exactly known, but are obtained using a reasonable learning mechanism or (b) the best arm is not more likely to arrive early, but a large fraction of arms is likely to arrive relatively early.
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| 23. |
- Mondal, Sneha, et al.
(författare)
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Two-Phase Influence Maximization in Social Networks with Seed Nodes and Referral Incentives
- 2017
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Ingår i: ICWSM 2017 - Proceedings of the 11th International AAAI Conference on Web and Social Media. - 2334-0770 .- 2162-3449. - 9781577357889 ; 11:1, s. 620-623
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Konferensbidrag (refereegranskat)abstract
- The problem of maximizing the spread of influence with a limited budget is central to social networks research. Most solution approaches available in the existing literature devote the entire budget towards triggering diffusion at seed nodes. This paper investigates the effect of splitting the budget across two different, sequential phases. In phase 1, we adopt the classical approach of initiating diffusion at a selected seed-set. In phase 2, we use the remaining budget to offer referral incentives. We formulate this problem and explore suitable ways to split the budget between the two phases, with detailed experiments on synthetic and real-world datasets. The principal findings from our study are: (a) when the budget is low, it is prudent to use the entire budget for phase 1; (b) when the budget is moderate to high, it is preferable to use much of the budget for phase 1, while allocating the remaining budget to phase 2; (c) in the presence of moderate to strict temporal constraints, phase 2 is not warranted; (d) if the temporal constraints are low or absent, phase 2 yields a decisive improvement in influence spread.
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