A reliability-based approach for influence maximization using the evidence theory

The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks for example. In this paper, we propose an influence measure that combines many influence indicators. Besides, we consider the reliability of each influence indicator and we present a distance-based process that allows to estimate the reliability of each indicator. The proposed measure is defined under the framework of the theory of belief functions. Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network. Finally, we present a set of experiments on a dataset collected from Twitter. These experiments show the performance of the proposed solution in detecting social influencers with good quality.Comment: 14 pages, 8 figures, DaWak 2017 conferenc

A reliability-based approach for influence maximization using the evidence theory

International audienceThe influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social networks for example. In this paper, we propose an influence measure that combines many influence indicators. Besides, we consider the reliability of each influence indicator and we present a distance-based process that allows to estimate the reliability of each indicator. The proposed measure is defined under the framework of the theory of belief functions. Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network. Finally, we present a set of experiments on a dataset collected from Twitter. These experiments show the performance of the proposed solution in detecting social influencers with good quality

Efficiency in Spanish banking: A multistakeholder approach analysis

Searching for greater inter efficiency has been used as a reason tomodify the Spanish banking system since 2009. This paper aimsto contribute to quantify the magnitude of efficiency, but not onlythe economic one, but also social and overall efficiency from 2000to 2011. The case of Spain – compared to other banking systems –provides unique information regarding the stakeholder governancebanking literature because over the last century savings banks havebecome rooted in the Spanish culture. The results – confirmed bya two-stage frontiers analysis, a DEA and a model combined withbootstrapped tests – indicate that Spanish savings banks are notless efficient globally than banks and are more efficient socially.Moreover, our results – with potentially important implications –encourage the participation of stakeholders in banking systems andunderline the importance of attaining long-term efficiency gains tosupport financial stability objectives

Measuring Social Value Orientation

Narrow self-interest is often used as a simplifying assumption when studying people making decisions in social contexts. Nonetheless, people exhibit a wide range of different motivations when choosing unilaterally among interdependent outcomes. Measuring the magnitude of the concern people have for others, sometimes called Social Value Orientation (SVO), has been an interest of many social scientists for decades and several different measurement methods have been developed so far. Here we introduce a new measure of SVO that has several advantages over existent methods. A detailed description of the new measurement method is presented, along with norming data that provide evidence of its solid psychometric properties. We conclude with a brief discussion of the research streams that would benefit from a more sensitive and higher resolution measure of SVO, and extend an invitation to others to use this new measure which is freely availabl

Conceptualising the impact of information asymmetry on through-life cost: case study of machine tools sector

Information asymmetry (IA) in terms of contextual variety and importance is one of the most challenging aspects of through-life costing in product-service systems (PSS). IA is an imbalance in the information, data and knowledge shared among the parties involved in a contractual agreement. In manufacturing systems under PSS, interaction and effective communication among several parties who are involved in a contractual agreement, rely on the continuity and accuracy of information and context. In such systems, contextual variety exhibits complexity and uncertainty in through-life costing and subsequently in PSS cost assessment. Although the economic aspect of PSS has been studied previously, the impact of IA on through-life cost and for different PSS solutions has not been detailed. Considering manufacturing value chains, this paper introduces a new concept of PSS-hierarchy to perform through-life costing in the presence of IA for various PSS solutions. Moreover, this paper proposes a generic life-cycle model for different PSS solutions to assess the total cost of ownership (TCO). The proposed model has been developed to support decisions on contract design in manufacturing systems. This study considers the manufacturer, service provider and customer perspectives to develop the TCO model using a machine tool manufacturing case study

Stakeholder orientation and organizational performance in an emerging market

There has been research that studies Chinese firms’ stakeholder orientation but fails to identify Chinese firms’ specific stakeholder groups. In addition, little research in this line has been conducted so far to reflect recent Chinese constitutional transition. This study seeks to fill these gaps. It extends previous studies assuming that a fixed set of stakeholders is suitable for firms in different countries context, and identifies Chinese firms’ key stakeholder groups by adopting the descriptive approach of stakeholder theory. Based on this identification, the authors further examine how these stakeholder orientations influence organizational performance and how they interact. Interviews with managers from 107 firms show that customer, employee, shareholder, supplier, and competitors are perceived as Chinese firms’ most important stakeholders; empirical studies using data collected from 307 Chinese firms reveal that orientations towards these stakeholders enhance organizational performance. Moreover, there are synergy effects existing among customer orientation, supplier orientation, and competitor orientation, and between customer orientation and competitor orientation, while shareholder orientation has significant hindering effects upon competitor orientation as a reflection of recent institutional changes taking place in China

Bayesian Updating, Model Class Selection and Robust Stochastic Predictions of Structural Response

A fundamental issue when predicting structural response by using mathematical models is how to treat both modeling and excitation uncertainty. A general framework for this is presented which uses probability as a multi-valued conditional logic for quantitative plausible reasoning in the presence of uncertainty due to incomplete information. The fundamental probability models that represent the structure’s uncertain behavior are specified by the choice of a stochastic system model class: a set of input-output probability models for the structure and a prior probability distribution over this set that quantifies the relative plausibility of each model. A model class can be constructed from a parameterized deterministic structural model by stochastic embedding utilizing Jaynes’ Principle of Maximum Information Entropy. Robust predictive analyses use the entire model class with the probabilistic predictions of each model being weighted by its prior probability, or if structural response data is available, by its posterior probability from Bayes’ Theorem for the model class. Additional robustness to modeling uncertainty comes from combining the robust predictions of each model class in a set of competing candidates weighted by the prior or posterior probability of the model class, the latter being computed from Bayes’ Theorem. This higherlevel application of Bayes’ Theorem automatically applies a quantitative Ockham razor that penalizes the data-fit of more complex model classes that extract more information from the data. Robust predictive analyses involve integrals over highdimensional spaces that usually must be evaluated numerically. Published applications have used Laplace's method of asymptotic approximation or Markov Chain Monte Carlo algorithms

Quality of Information in Mobile Crowdsensing: Survey and Research Challenges

Smartphones have become the most pervasive devices in people's lives, and are clearly transforming the way we live and perceive technology. Today's smartphones benefit from almost ubiquitous Internet connectivity and come equipped with a plethora of inexpensive yet powerful embedded sensors, such as accelerometer, gyroscope, microphone, and camera. This unique combination has enabled revolutionary applications based on the mobile crowdsensing paradigm, such as real-time road traffic monitoring, air and noise pollution, crime control, and wildlife monitoring, just to name a few. Differently from prior sensing paradigms, humans are now the primary actors of the sensing process, since they become fundamental in retrieving reliable and up-to-date information about the event being monitored. As humans may behave unreliably or maliciously, assessing and guaranteeing Quality of Information (QoI) becomes more important than ever. In this paper, we provide a new framework for defining and enforcing the QoI in mobile crowdsensing, and analyze in depth the current state-of-the-art on the topic. We also outline novel research challenges, along with possible directions of future work.Comment: To appear in ACM Transactions on Sensor Networks (TOSN