Pass it on: towards a political economy of propensity

The paper argues that the work of Gabriel Tarde on imitation provides a fertile means of understanding how capitalism is forging a new affective technology which conforms to a logic of propensity rather than to means-end reasoning. This it does by drawing together a biological understanding of semiconscious cognition with various practical geometric arts so as to re-stage the world as a series of susceptible situations which can be ridden rather than rigidly controlled. The paper examines the advent of technologies which attend to the variable geometry of so-called animal spirits in the realm of business and then, using Tarde's work as a springboard, considers some alternative means of understanding imitative rays which have less instrumental undertones. The paper is an illustration of the way in which biology and culture have increasingly become intertwined

Alter ego, state of the art on user profiling: an overview of the most relevant organisational and behavioural aspects regarding User Profiling.

This report gives an overview of the most relevant organisational and\ud behavioural aspects regarding user profiling. It discusses not only the\ud most important aims of user profiling from both an organisation’s as\ud well as a user’s perspective, it will also discuss organisational motives\ud and barriers for user profiling and the most important conditions for\ud the success of user profiling. Finally recommendations are made and\ud suggestions for further research are given

Recommender Systems

The ongoing rapid expansion of the Internet greatly increases the necessity of effective recommender systems for filtering the abundant information. Extensive research for recommender systems is conducted by a broad range of communities including social and computer scientists, physicists, and interdisciplinary researchers. Despite substantial theoretical and practical achievements, unification and comparison of different approaches are lacking, which impedes further advances. In this article, we review recent developments in recommender systems and discuss the major challenges. We compare and evaluate available algorithms and examine their roles in the future developments. In addition to algorithms, physical aspects are described to illustrate macroscopic behavior of recommender systems. Potential impacts and future directions are discussed. We emphasize that recommendation has a great scientific depth and combines diverse research fields which makes it of interests for physicists as well as interdisciplinary researchers.Comment: 97 pages, 20 figures (To appear in Physics Reports

Using Text Mining to Analyze Quality Aspects of Unstructured Data: A Case Study for “stock-touting” Spam Emails

The growth in the utilization of text mining tools and techniques in the last decade has been primarily driven by the increase in the sheer volume of unstructured texts and the need to extract useful and more importantly, quality information from them. The impetus to analyse unstructured data efficiently and effectively as part of the decision making processes within an organization has further motivated the need to better understand how to use text mining tools and techniques. This paper describes a case study of a stock spam e-mail architecture that demonstrates the process of refining linguistic resources to extract relevant, high quality information including stock profile, financial key words, stock and company news (positive/negative), and compound phrases from stock spam e-mails. The context of such a study is to identify high quality information patterns that can be used to support relevant authorities in detecting and analyzing fraudulent activities

Mobile information access in the real world: A story of three wireless devices

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2008 ElsevierThe importance of the user perspective to the wireless information access experience cannot be understated: simply put, users will not indulge in devices that are perceived to be difficult to use and in technologies that do not offer quality infotainment – combined information and entertainment – content. In this paper, we investigate the impact that mobile devices have on the user wireless infotainment access experience in practice. To this end, we have undertaken an empirical study placed in a ‘real-world’ setting, in which participants undertook typical infotainment access tasks on three different wireless-enabled mobile devices: a laptop, a personal digital assistant and a head mounted display device. Results show that, with the exception of participants’ level of self-consciousness when using such devices in public environments, the user wireless information access experience is generally unaffected by device type. Location was shown, though, to be a significant factor when users engage in tasks such as listening to online music or navigation. Whilst the interaction between device and environment was found to influence entertainment-related tasks in our experiments, the informational ones were not affected. However, the interaction effects between device and user type was found to affect both types of tasks. Lastly, a user’s particular computing experience was shown to influence the perceived ease of wireless information access only in the case of online searching, irrespective of whether this is done for primarily informational purposes or entertainment ones

Factors influencing the use of privacy settings in location-based social networks

The growth of location-based social networks (LBSN) such as Facebook and Twitter has been rapid in recent years. In LBSNs, users provide location information on public profiles that potentially can be used in harmful ways. LBSNs have privacy settings that allow users to control the privacy level of their profiles, thus limiting access to location information by other users; but for various reasons users seldom make use of them. Using the protection motivation theory (PMT) as a theoretical lens, this dissertation examines whether users can be encouraged to use LBSN privacy settings through fear appeals. Fear appeals have been used in various studies to arouse fear in users, in order to motivate them to comply to an adaptive behaviour through the threat of impending danger. However, within the context of social networking, it is not yet clear how fear-inducing arguments will ultimately influence the use of privacy settings by users. The purpose of this study is to investigate the influence of fear appeals on user compliance, with recommendations to enact the use of privacy settings toward the alleviation of privacy threats. Using a survey methodology, 248 social-network users completed an instrument measuring the variables conceptualized by PMT. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to test the validity and reliability, and to analyze the data. Analysis of the responses show that PMT provides an explanation for the intention to use privacy settings by social-network users. Risk susceptibility, response efficacy, self-efficacy and response cost were found to have a positive impact on the intention to use privacy settings, while sharing benefits and maladaptive behaviours were found to have a negative impact on the intention to use privacy settings. However, risk severity and fear were not found to be significant predictors of the intention to use privacy settings. This study contributes to existing research on PMT in a sense that fear appeal should focus more on coping appraisal, rather than on threat appraisal which is consistent with the results of most studies on protection motivation

Learning validation in the european union policy-making: the case of social impact evaluation in the open resources project

Il presente elaborato indaga l’evoluzione del progetto pilota “Open RESOURCES” di Treviso analizzata in termini di innovazione sociale nel quadro di regolazione multilivello. Tale progetto rappresenta una risposta ai bisogni emergenti del territorio, coniugando l’esigenza lavorativa e abitativa dei rifugiati con quella dei giovani disoccupati locali che, in cambio di un lavoro di ristrutturazione e di efficientamento energetico nelle abitazioni private, potranno godere di un alloggio nelle stesse a titolo gratuito. In particolare, il fil rouge della tesi è la validazione degli apprendimenti nel policy making dell’Unione Europea. L’obiettivo generale dell’elaborato è quello di affermare che, nell’innovazione sociale, un apprendimento validato, continuo e collettivo, assicura risultati significativi per tutti i beneficiari del progetto, diretti e indiretti, diventando inoltre un’opportunità positiva per il livello di regolazione europeo. L’emersione a livello comunitario della pratica in via di sperimentazione a Treviso garantirebbe una serie di rilevanti vantaggi, quali: favorire l’attrazione di investimenti pubblici e privati; accrescere la scalabilità e la replicabilità dell’esperienza in una strategia solidale, sostenibile e intelligente; collegare top-down e bottom-up nel ciclo di policy; e di rinsaldare i principi di un’Europa Sociale attenta ai bisogni della popolazione. Per favorire tale processo, si offre una proposta di valutazione di impatto sociale incentrata sulla validazione degli apprendimenti. L’elaborazione segue le direttrici metodologiche di due approcci distinti: la Lean Startup di Eric Ries e il Collective Impact di John Kania e Mark Kramer. L’impianto valutativo è inteso divenire linguaggio comune a tutti gli stakeholder volto a conferire una maggiore visibilità e accrescere l’eventuale replicabilità e scalabilità del progetto, attirando possibili ulteriori partner ed aprendolo a forme di finanziamento derivanti dal Quadro Finanziario Pluriennale dell’Unione Europe

Semantic discovery and reuse of business process patterns

Patterns currently play an important role in modern information systems (IS) development and their use has mainly been restricted to the design and implementation phases of the development lifecycle. Given the increasing significance of business modelling in IS development, patterns have the potential of providing a viable solution for promoting reusability of recurrent generalized models in the very early stages of development. As a statement of research-in-progress this paper focuses on business process patterns and proposes an initial methodological framework for the discovery and reuse of business process patterns within the IS development lifecycle. The framework borrows ideas from the domain engineering literature and proposes the use of semantics to drive both the discovery of patterns as well as their reuse