Bridging the Gap Between the Least and the Most Influential Twitter Users

Social networks play an increasingly important role in shaping the behaviour of users of the Web. Conceivably Twitter stands out from the others, not only for the platform's simplicity but also for the great influence that the messages sent over the network can have. The impact of such messages determines the influence of a Twitter user and is what tools such as Klout, PeerIndex or TwitterGrader aim to calculate. Reducing all the factors that make a person influential into a single number is not an easy task, and the effort involved could become useless if the Twitter users do not know how to improve it. In this paper we identify what specific actions should be carried out for a Twitterer to increase their influence in each of above-mentioned tools applying, for this purpose, data mining techniques based on classification and regression algorithms to the information collected from a set of Twitter users.This work has been partially founded by the European Commission Project ”SiSOB: An Observatorium for Science in Society based in Social Models” (http://sisob.lcc.uma.es) (Contract no.: FP7 266588), ”Sistemas Inalámbricos de Gestión de Información Crítica” (with code number TIN2011-23795 and granted by the MEC, Spain) and ”3DTUTOR: Sistema Interoperable de Asistencia y Tutoría Virtual e Inteligente 3D” (with code number IPT-2011-0889- 900000 and granted by the MINECO, Spain

Anomalies: Ultimatums, Dictators and Manners

Economics can be distinguished from other social sciences by the belief that most (all?) behavior can be explained by assuming that agents have stable, well-defined preferences and make rational choices consistent with those preferences in markets that (eventually) clear. An empirical result qualifies as an anomaly if it is difficult to "rationalize" or if implausible assumptions are necessary to explain it within the paradigm. This column will resume, after a long rest, the investigation of such anomalies

Individual Tariffs for Mobile Communication Services

This paper introduces a conceptual framework and a computational model for individual tariffs for mobile communication services. The purpose is to provide guidance for implementation by communication service suppliers or user groups alike. The paper first examines the sociological and economic incentives for personalized services and individual tariffs. Then it introduces a framework for individual tariffs which is centered on user and supplier behaviours. The user, instead of being fully rational, has "bounded rationality" and his behaviours are subject to economic constraints and influenced by social needs. The supplier can belong to different types of entities such as firms and communities; each has his own goals which lead to different behaviors. Individual tariffs are decided through interactions between the user and the supplier and can be analyzed in a structured way using game theory. A numerical case in mobile music training is developed to illustrate the concepts.risks;mobile communication services;Individual tariffs;computational games

Machine learning : techniques and foundations

The field of machine learning studies computational methods for acquiring new knowledge, new skills, and new ways to organize existing knowledge. In this paper we present some of the basic techniques and principles that underlie AI research on learning, including methods for learning from examples, learning in problem solving, learning by analogy, grammar acquisition, and machine discovery. In each case, we illustrate the techniques with paradigmatic examples

Survey on Classification Algorithms for Data Mining:(Comparison and Evaluation)

Data mining concept is growing fast in popularity, it is a technology that involving methods at the intersection of (Artificial intelligent, Machine learning, Statistics and database system), the main goal of data mining process is to extract information from a large data into form which could be understandable for further use. Some algorithms of data mining are used to give solutions to classification problems in database. In this paper a comparison among three classification’s algorithms will be studied, these are (K- Nearest Neighbor classifier, Decision tree and Bayesian network) algorithms. The paper will demonstrate the strength and accuracy of each algorithm for classification in term of performance efficiency and time complexity required. For model validation purpose, twenty-four-month data analysis is conducted on a mock-up basis. Keywords: Decision tree, Bayesian network, k- nearest neighbour classifier

Impacts of planning rules, regulations, uncertainty and delay on residential property development

This paper proposes a framework for how houses could be developed, with a focus on how regulatory policies and practices affect decision making. The authors surveyed property developers in Auckland on how planning rules and regulations affect the cost of \u27affordable\u27 housing. Almost 90% of the developers surveyed had been affected by delays or uncertainties related to regulation. The typical cost range of regulations is estimated to be between $32,500 and$60,000 per dwelling in a subdivision and between $65,000 and$110,000 per apartment. Academic Abstract Dwelling prices are determined in the long run by the total costs of a development, where costs include regulatory costs, including costs of delay and uncertainty. We outline a conceptual framework for the development process and then develop a real options model of housing development that indicates more formally how regulatory policies and regulatory practices affect development decisions. We apply these insights to the design of a survey of property developers active in the Auckland market, with an emphasis on the ‘affordable’ part of the market. In surveying developers, we aim to elicit their views regarding the impacts that planning rules and regulations have on total development costs. We do not attempt to value the corresponding benefits of the planning rules and regulations, so this study is not a cost: benefit analysis of council planning approaches; rather it documents the costs of the rules and regulations – as perceived by developers – to provide a basis for benefits to be compared. Almost 90% of surveyed developers have been affected by delays or uncertainties related to regulation. Regulations that have had major effects on the actual building costs of apartments include: building height limits, balcony requirements, conforming to Council’s desired mix of apartment typologies and minimum floor to ceiling heights. Major cost effects on developing residential sections and standalone dwellings include: infrastructure contributions not related to the specific development, section size requirements, extended consent processes and urban design considerations stemming from Council’s urban designers. Reserve and development contributions and Watercare levies affect the costs of both types of development. Excluding the cost of Watercare and reserve and development contributions, the typical cost range of the total impact of regulations is estimated to vary between $32,500 and$60,000 per dwelling in a subdivision. In terms of affordable apartments, assuming the total internal floor area remains the same and no deck is built, the impact on total cost typically is estimated to range between $65,000 and$110,000 per apartment