BeFriend: platforma za kontekstno-svjesno ad-hoc društveno umrežavanje

Ad-hoc social networks, focused on managing user social relationships in a novel fashion based on establishment of temporary social connections among users with mutual interests and/or needs, provide an innovative medium for upgrading existing, as well as developing new social relationships. This paper describes the BeFriend, a context-aware ad-hoc social networking platform based on Facebook and Google+ social graphs. The BeFriend platform is for mobile users equipped with a smartphone -- after installing and activating the BeFriend client, they are able to receive push notifications when a certain rule is triggered (e.g. it is Friday evening, Ewan and Luke are drinking beer in a bar and one of their Facebook/Google+ friends passes nearby). Personal agents within the BeFriend platform provide autonomous decision-making in the platform, decrease the need for user input and enable automated social discovery of new community members. The proof of-concept BeFriend platform presented in this paper is available in form of BeFriend application for users possessing Android-based smartphones.Ad-hoc društvene mreže su usmjerene na novi pristup upravljanju društvenim odnosima koji se temelji na uspostavi privremene društvene povezanosti među korisnicima sa zajedničkim interesima i/ili potrebama. Na taj način ad-hoc društvene mreže predstavljaju inovativni medij za nadogradnju postojećih te razvoj novih društvenih odnosa. Ovaj rad opisuje platformu za kontekstno-svjesno ad-hoc društveno umrežavanje BeFriend, koja je zasnovana na društvenim grafovima Facebook i Google+. Platforma BeFriend je namijenjena korisnicima pametnih pokretnih uređaja te omogućuje, nakon instalacije i aktivacije klijenta BeFriend, primanje push-obavijesti potaknuto aktiviranjem određenog pravila (primjerice, Ewan i Luke piju pivu u kafiću u petak navečer te njihov Facebook/Google+ prijatelj upravo prolazi pokraj kafića). Osobni agenti koji su dio platforme BeFriend omogućuju samostalno donošenje odluka unutar platforme, što smanjuje potrebu za korisničkim akcijama ili intervencijama i omogućuje automatski pronalazak novih članova društvene zajednice. Prototip platforme BeFriend koji je opisan u ovome radu dostupan je kao aplikacija BeFriend korisnicima koji posjeduju pametne pokretne uređaje zasnovane na operacijskom sustavu Android

Implicit Social Networking: Discovery of Hidden Relationships, Roles and Communities among Consumers

AbstractThis paper proposes the implicit social networking as an innovative methodology for approaching consumers who possess information-rich user profiles based on aplethora of online services they use. An implicit social network is not explicitly built by consumers themselves, but implicitly calculated by third parties based on a level of a common interest between consumers (i.e., profile matchmaking). The analysis of aconsumer social network created in such a manner enables discovery of hidden roles, relationships and communities among consumers and represents a basis for provisioning of innovative services (e.g., personalized and/or context-aware services such as recommender systems). The implicit social networking methodology is evaluated through two pilot cases: (i) implicit social networking based on the SmartSocial platform; and (ii) implicit social networking of IPTV users. The generalizability of the implicit social networking is demonstrated through additional example aimed not at external company stakeholders (e.g., company consumers), but at internal stakeholders (i.e., company employees) through the implicit corporate social networking pilot case

Agent-Based Modelling and Simulation of Product Development Teams

The success of product development highly depends on the quality of cooperation among members of a team involved in the process. Thus, a tool capable of simulating product development team may be beneficial for researchers interested in teamwork, as well as useful for managers struggling with team formation during process planning phase. This work aims at providing a detailed overview of agent-based simulators of product development teams. Specifically, the scientific databases Web of Science, Scopus, ACM DL, and IEEE were searched to extract relevant agent-based models of teamwork in mechanical engineering and aerospace context and obtained models were reviewed to identify their key advantages and limitations

Sublinear scaling of country attractiveness observed from Flickr dataset

The number of people who decide to share their photographs publicly increases every day, consequently making available new almost real-time insights of human behavior while traveling. Rather than having this statistic once a month or yearly, urban planners and touristic workers now can make decisions almost simultaneously with the emergence of new events. Moreover, these datasets can be used not only to compare how popular different touristic places are, but also predict how popular they should be taking into an account their characteristics. In this paper we investigate how country attractiveness scales with its population and size using number of foreign users taking photographs, which is observed from Flickr dataset, as a proxy for attractiveness. The results showed two things: to a certain extent country attractiveness scales with population, but does not with its size; and unlike in case of Spanish cities, country attractiveness scales sublinearly with population, and not superlinearly.Singapore-MIT Alliance for Research and Technology (SMART)Accenture (Firm)Air liquide (Firm)Coca-Cola CompanyEricsson (Firm)Volkswagen Electronics Research LabUber (Firm)MIT Senseable City Lab Consortiu

A survey-based assessment of how existing and potential electric vehicle owners perceive range anxiety

Electric vehicle (EV) owners enjoy many positive aspects when driving their cars, including low running costs and zero tailpipe gas emissions, which makes EVs a clean technology provided that they are sourced through renewable sources, e.g., biomass, solar power, or wind energy. However, their driving behaviour is often negatively affected by the so-called range anxiety phenomenon, i.e., a concern that an EV might not have enough driving range to reach the desired destination due to its limited battery size. The perception of range anxiety may also affect potential buyers in their decisions on whether to purchase an internal combustion engine vehicle as opposed to an EV. This paper investigates some factors that influence range anxiety through a comparative analysis of two target groups: (i) existing EV owners, and (ii) non-EV owners (i.e., potential EV owners). The specially crafted survey was used to collect range anxiety data from more than 200 participants. In particular, participants provided their perceptions on (i) the potential relationship between existing gas station infrastructure and the desired EV charging station infrastructure, and (ii) the potential relationship between range anxiety and two influencing variables, namely the current state of charge and remaining range. Concerning the existing gas station infrastructure, evidence suggests that both target groups think that the distances between gas stations could be increased. Moreover, our analysis shows that the desired distances between charging stations correspond to the distances between the existing gas stations, which indicates that both EV owners and non-EV owners have a common view on the optimal gas station and charging station topology. Furthermore, we find that the type of settlement (urban vs rural) influences preferred distances, where both target groups living in cities desire shorter distances, and that non-EV owners, as opposed to EV owners, are more prone to be affected by the state of charge and remaining range. Quantitatively, we are able to define a measure for range anxiety, which is connected with the preferred distance between two neighbouring charging stations. Throughout our analyses, we find that the mean preferred distance between two neighbouring charging stations is 7 km, but this value significantly differs based on the settlement type of a (potential) EV owner

Mining Social Networks for Calculation of SmartSocial Influence

In today's networked society where everybody and everything becomes inter-connected, it is very important to be able to identify key actors and key relationships in such a complex multi-layered eco-system. This paper focuses on the specific research challenge of identifying the most influential actors in a social network built through combining relationships among same actors in two different domains - communication domain (proxied through real-world mobile phone communication data) and social networking service domain (proxied through real-world Facebook data). A practical aspect of the paper is evaluated through the SmartSocial Platform, which uses methodology and implements algorithms that enable: i) joining multiple relations among actors across different social networks into the single unified social network; as well as ii) mining created unified social network for identification of most influential actors. Evaluation of the proposed approach is based on the social experiment with 465 users. Experiment results underline two important paper contributions: i) posting frequency sensitivity analysis shows a significant effect of posting frequency on social influence scores; and ii) interdependency analysis shows a synergic effect of combining data from communication and social networking service domains when it comes to calculating influence scores

A Methodology for Evaluating Algorithms That Calculate Social Influence in Complex Social Networks

Online social networks are complex systems often involving millions or even billions of users. Understanding the dynamics of a social network requires analysing characteristics of the network (in its entirety) and the users (as individuals). This paper focuses on calculating user’s social influence, which depends on (i) the user’s positioning in the social network and (ii) interactions between the user and all other users in the social network. Given that data on all users in the social network is required to calculate social influence, something not applicable for today’s social networks, alternative approaches relying on a limited set of data on users are necessary. However, these approaches introduce uncertainty in calculating (i.e., predicting) the value of social influence. Hence, a methodology is proposed for evaluating algorithms that calculate social influence in complex social networks; this is done by identifying the most accurate and precise algorithm. The proposed methodology extends the traditional ground truth approach, often used in descriptive statistics and machine learning. Use of the proposed methodology is demonstrated using a case study incorporating four algorithms for calculating a user’s social influence

Electric Vehicles: A Data Science Perspective Review

Current trends are showing that the popularity of electric vehicles (EVs) has significantly increased over the last few years, causing changes not only in the transportation industry but generally in business and society. This paper covers one possible angle to the (r) evolution instigated by EVs, i.e., it provides the data science perspective review of the interdisciplinary area at the intersection of green transportation, energy informatics, and economics. Namely, the review summarizes data-driven research in EVs by identifying two main research streams: (i) socio–economic, and (ii) socio–technical. The socio–economic stream includes research in: (i) acceptance of green transportation in countries and among different populations, (ii) current trends in the EV market, and (iii) forecasting future sales for the green transportation. The socio–technical stream includes research in: (i) electric vehicle battery price and capacity and (ii) charging station management. This kind of study is especially important now when the question is no longer whether the transition from internal-combustion engine vehicles to clean-fuel vehicles is going to happen but how fast it will happen and what are going to be implications for society, governmental policies, and industry. Based on the presented literature review, the paper also outlines the most significant open questions and challenges that are yet to be solved: (i) scarcity of trustworthy (open) data, and (ii) designing a generalized methodology for charging station deployment

An Agent-Based Solution for Dynamic Supply Chain Management

Supply chain management (SCM) deals with planning and coordinating activities such as material procurement, product assembly, and the distribution of manufactured products. This paper offers an agent-based solution as a potentially adequate approach for the automation of supply chain management. The greatest obstacle in SCM research is obtaining benchmark designed solutions since it is difficult to simulate real business environments, while live testing in real-world systems is not an option. The Trading Agent Competition Supply Chain Management (TAC SCM) scenario provides a unique testbed for studying and prototyping SCM agents by providing a challenging game environment where competing agents engage in complex decision-making activities with the purpose of maximizing their profit. In this paper, we describe the TAC SCM environment and present the main features of the CrocodileAgent, our TAC SCM 2007 entry. Additionally, the CrocodileAgent’s performance in the competition, as well as in a series of controlled experiments, is discussed