Search results for "Information networks"
showing 10 items of 91 documents
Motivations, engagement and adoption of e-WOM in restaurants.
2022
Resumen El objetivo del presente trabajo fue estudiar el efecto que tienen las motivaciones para consultar y escribir e-WOM sobre el compromiso con el e-WOM y la influencia de dicho compromiso en la adopción del e-WOM consultado. Para analizar estas relaciones, se realizó una investigación empírica aplicada en el contexto de los restaurantes. El ámbito geográfico fue Ecuador, con una muestra de 461 consumidores. Se utilizó un modelo de ecuaciones estructurales y se validó la cadena de relaciones. Los resultados confirmaron las relaciones entre estas variables; además, se presentaron implicaciones académicas interesantes para profundizar en el estudio sobre el compromiso con el e-WOM, así co…
A New Intelligent Technique of Constructing Optimal Airline Seat Protection Levels for Multiple Nested Fare Classes of Single-Leg Flights
2019
A new, rigorous formulation of the optimization problem of airline seat protection levels for multiple nested fare classes is presented. A number of results useful for practical application are obtained. A numerical example is given.
Competition for long-haul connecting traffic among airports in Europe and the Middle East
2017
Abstract This paper analyzes the competitive position of major hub airports in Europe and the Middle East for long-haul connecting traffic. We apply a connection builder to construct competitive flight connections. A stand out feature of the proposed connection builder is the calibration of the model parameters using booking data, composed of actual passenger demand between a given origin and destination (O&D) market. The methodology is applied to measure competition between hubs using flight schedule data to calculate connectivity measures like the number of city-pairs connected via a hub airport. Our results show that the Middle Eastern hubs have improved their competitive position, while…
Analyzing the Correlation of Classical and Community-aware Centrality Measures in Complex Networks
2021
International audience; Identifying influential nodes in social networks is a fundamental issue. Indeed, it has many applications, such as inhibiting epidemic spreading, accelerating information diffusion, preventing terrorist attacks, and much more. Classically, centrality measures quantify the node's importance based on various topological properties of the network, such as Degree and Betweenness. Nonetheless, these measures are agnostic of the community structure, although it is a ubiquitous characteristic encountered in many real-world networks. To overcome this drawback, there is a growing trend to design so-called community-aware centrality measures. Although several works investigate…
Computation of Unstable Binodals Not Requiring Concentration Derivatives of the Gibbs Energy
1998
The equilibrium of three liquid phases in a binary mixture implies the existence of tie lines and binodals that are different from the normal experimentally observable ones. First of all, there are the metastable extensions of the binodal built up by S/S tie lines. These S/S tie lines fulfill the equilibrium condition of the minimum of the Gibbs energy of the entire two-phase system. Both coexisting phases are located within the meta(stable) region. There are two additional types of tie lines: U/U (maximum of the Gibbs energy; both end points within the unstable area) and U/S tie lines (saddle point; one end point within the (meta)stable, the other within the unstable region). All types of…
Investigating Centrality Measures in Social Networks with Community Structure
2021
Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures that exploit features of the community structure information encountered in most real-world complex networks. In this paper, we investigate the interactions between 5 popular classical centrality measures and 5 community-aware centrality measures using 8 real-world online networks. Correlation as well as similarity measures between both t…
World Influence of Infectious Diseases from Wikipedia Network Analysis
2019
AbstractWe consider the network of 5 416 537 articles of English Wikipedia extracted in 2017. Using the recent reduced Google matrix (REGOMAX) method we construct the reduced network of 230 articles (nodes) of infectious diseases and 195 articles of world countries. This method generates the reduced directed network between all 425 nodes taking into account all direct and indirect links with pathways via the huge global network. PageRank and CheiRank algorithms are used to determine the most influential diseases with the top PageRank diseases being Tuberculosis, HIV/AIDS and Malaria. From the reduced Google matrix we determine the sensitivity of world countries to specific diseases integrat…
Novel Version of PageRank, CheiRank and 2DRank for Wikipedia in Multilingual Network Using Social Impact
2020
International audience; Nowadays, information describing navigation behaviour of internet users are used in several fields, e-commerce, economy, sociology and data science. Such information can be extracted from different knowledge bases, including business-oriented ones. In this paper, we propose a new model for the PageRank, CheiRank and 2DRank algorithm based on the use of clickstream and pageviews data in the google matrix construction. We used data from Wikipedia and analysed links between over 20 million articles from 11 language editions. We extracted over 1.4 billion source-destination pairs of articles from SQL dumps and more than 700 million pairs from XML dumps. Additionally, we …
Percolation on correlated random networks
2011
We consider a class of random, weighted networks, obtained through a redefinition of patterns in an Hopfield-like model and, by performing percolation processes, we get information about topology and resilience properties of the networks themselves. Given the weighted nature of the graphs, different kinds of bond percolation can be studied: stochastic (deleting links randomly) and deterministic (deleting links based on rank weights), each mimicking a different physical process. The evolution of the network is accordingly different, as evidenced by the behavior of the largest component size and of the distribution of cluster sizes. In particular, we can derive that weak ties are crucial in o…
Criminal networks analysis in missing data scenarios through graph distances.
2021
Data collected in criminal investigations may suffer from: (i) incompleteness, due to the covert nature of criminal organisations; (ii) incorrectness, caused by either unintentional data collection errors and intentional deception by criminals; (iii) inconsistency, when the same information is collected into law enforcement databases multiple times, or in different formats. In this paper we analyse nine real criminal networks of different nature (i.e., Mafia networks, criminal street gangs and terrorist organizations) in order to quantify the impact of incomplete data and to determine which network type is most affected by it. The networks are firstly pruned following two specific methods: …