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2. The influence of social networking sites on recruiting human resources in the Czech republicLucie Bohmova, Antonín Pavlíček, 2015, izvirni znanstveni članek Opis: Background: This paper is focused on the usage of social networking sites (SNS) for human resources departments in the process of hiring new employees. It also maps the development and influence of SNS on recruiter's behavior and customs. The main aim is to find out, whether SNS could/will replace traditional online job boards in the Czech Republic. The motivation for the research is to determine whether SNS can be used for serious and practical business purposes.
Methods: The paper presents authors’ empirical research with two interconnected instruments used for data collection: (1) Questionnaire with 15 questions devoted to usability, evaluation and comparison of SNS with job portals (N=286 HR specialists) and (2) Comparison of 3 online job advertising methods – job portals, SNS and business website.
Results: HR specialists regularly use publicly available information on candidates’ Facebook profiles. Similar results have been observed using both instruments. SNS's in the Czech Republic are not yet used by recruiters as the main tool for recruitment, however, are often used as a support tool for decision making in the final stage of recruitment. Use of SNS's by recruiters is universal; we have not found any significant differences in terms of demographics (men, women, old, young HR professionals). The rate of utilization of SNS's by recruiters in the Czech Republic is gradually increasing, but does not reach the US level.
Conclusion: Our findings confirm the rising importance of social networking sites (SNS) usage as a new recruiting technology. However, as a major player in the field of recruitment, job boards (eg. Jobs.cz) are still important. However, the expectation is that in the near future, this will change and SNS‘s may replace the job boards.
Ključne besede: human resources, new trends, social networks, social networking site, SNS, job boards, competitive advantage
Objavljeno v DKUM: 22.01.2018; Ogledov: 1141; Prenosov: 353
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3. Determinants of public cooperation in multiplex networksFederico Battiston, Matjaž Perc, Vito Latora, 2017, izvirni znanstveni članek Opis: Synergies between evolutionary game theory and statistical physics have significantly improved our understanding of public cooperation in structured populations. Multiplex networks, in particular, provide the theoretical framework within network science that allows us to mathematically describe the rich structure of interactions characterizing human societies. While research has shown that multiplex networks may enhance the resilience of cooperation, the interplay between the overlap in the structure of the layers and the control parameters of the corresponding games has not yet been investigated. With this aim, we consider here the public goods game on a multiplex network, and we unveil the role of the number of layers and the overlap of links, as well as the impact of different synergy factors in different layers, on the onset of cooperation. We show that enhanced public cooperation emerges only when a significant edge overlap is combined with at least one layer being able to sustain some cooperation by means of a sufficiently high synergy factor. In the absence of either of these conditions, the evolution of cooperation in multiplex networks is determined by the bounds of traditional network reciprocity with no enhanced resilience. These results caution against overly optimistic predictions that the presence of multiple social domains may in itself promote cooperation, and they help us better understand the complexity behind prosocial behavior in layered social systems.
Ključne besede: cooperation, public goods, networks, physics of social systems
Objavljeno v DKUM: 04.12.2017; Ogledov: 979; Prenosov: 367
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4. Link prediction in multiplex online social networksMahdi Jalili, Yasin Orouskhani, Milad Asgari, Nazanin Alipourfard, Matjaž Perc, 2017, izvirni znanstveni članek Opis: Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.
Ključne besede: social networks, complex networks, signed networks, link prediction, machine learning
Objavljeno v DKUM: 08.08.2017; Ogledov: 1298; Prenosov: 439
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5. Opinions and behavior of students in social aspects of internet use in Serbia and SloveniaBorislav Josanov, Andreja Pucihar, Ivana Jošanov-Vrgović, 2014, izvirni znanstveni članek Opis: Rapid involvement of Internet infrastructure and services brought a lot of new products based on information and communication technologies. In the focus of world's social interest at this time are social networks and WikiLeaks and their abuse. In this paper authors analyze opinions and behaviour of students at Novi Sad Business School, Serbia, and Faculty of Organizational Sciences in Kranj, Slovenia. This research focuses on different kinds of abuse of social networks and WikiLeaks. Results are presented and analyzed according to the place where examinees study. Conclusions about the differences found between the above-mentioned two groups are compared to the social states and events in these 2 countries which officially separated 25 years ago.
Ključne besede: social networks, abuse, students, Slovenia, Serbia, WikiLeaks
Objavljeno v DKUM: 24.07.2017; Ogledov: 987; Prenosov: 140
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6. Opinions and behavior of students about abuse of internet in social involvments : gender analysisBorislav Josanov, Andreja Pucihar, Ivana Jošanov-Vrgović, Zoran Marošan, 2016, izvirni znanstveni članek Opis: New Internet technologies brought new gamma of interests worldwide. In the focus of people are social networks, main usage and the abuse of Internet usage. Authors analyze the group of students in Higher School for Professional Business Studies in in Novi Sad, Serbia, and in Faculty of Organizational Sciences Kranj, Slovenia. In the focus of this research are opinions and behavior of students about social aspects of Internet general usage, and specificly opinions about social networks and WikiLeaks. This paper is the succesor of the sross-cultural research that was presented in this journal with the same data two years ago, but structured diferently, acording to the location where they were taken. Results of this research are analyzed and presented according to the gender of examinees.
Ključne besede: social networks, internet, gender, abuse, students, WikiLeaks
Objavljeno v DKUM: 24.07.2017; Ogledov: 852; Prenosov: 199
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7. Self-organization towards optimally interdependent networks by means of coevolutionZhen Wang, Attila Szolnoki, Matjaž Perc, 2014, izvirni znanstveni članek Opis: Coevolution between strategy and network structure is established as a means to arrive at the optimal conditions needed to resolve social dilemmas. Yet recent research has highlighted that the interdependence between networks may be just as important as the structure of an individual network. We therefore introduce the coevolution of strategy and network interdependence to see whether this can give rise to elevated levels of cooperation in the prisonerʼs dilemma game. We show that the interdependence between networks self-organizes so as to yield optimal conditions for the evolution of cooperation. Even under extremely adverse conditions, cooperators can prevail where on isolated networks they would perish. This is due to the spontaneous emergence of a two-class society, with only the upper class being allowed to control and take advantage of the interdependence. Spatial patterns reveal that cooperators, once arriving at the upper class, are much more competent than defectors in sustaining compact clusters of followers. Indeed, the asymmetric exploitation of interdependence confers to them a strong evolutionary advantage that may resolve even the toughest of social dilemmas.
Ključne besede: coevolution, cooperation, interdependent networks, evolutionary games, collective phenomena, self-organization, phase transitions, physics of social systems
Objavljeno v DKUM: 03.07.2017; Ogledov: 1098; Prenosov: 389
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8. Probabilistic sharing solves the problem of costly punishmentXiaojie Chen, Attila Szolnoki, Matjaž Perc, 2014, izvirni znanstveni članek Opis: Cooperators that refuse to participate in sanctioning defectors create the secondorder free-rider problem. Such cooperators will not be punished because they contribute to the public good, but they also eschew the costs associated with punishing defectors. Altruistic punishers - those that cooperate and punish - are at a disadvantage, and it is puzzling how such behaviour has evolved. We show that sharing the responsibility to sanction defectors rather than relying on certain individuals to do so permanently can solve the problem of costly punishment. Inspired by the fact that humans have strong but also emotional tendencies for fair play, we consider probabilistic sanctioning as the simplest way of distributing the duty. In well-mixed populations the public goods game is transformed into a coordination game with full cooperation and defection as the two stable equilibria, while in structured populations pattern formation supports additional counterintuitive solutions that are reminiscent of Parrondoʼs paradox.
Ključne besede: social dynamics, networks, punishment, public goods, econophysics
Objavljeno v DKUM: 03.07.2017; Ogledov: 1036; Prenosov: 391
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9. Information sharing promotes prosocial behaviourAttila Szolnoki, Matjaž Perc, 2013, izvirni znanstveni članek Opis: More often than not, bad decisions are bad regardless of where and when they are made. Information sharing might thus be utilized to mitigate them. Here we show that sharing information about strategy choice between players residing on two different networks reinforces the evolution of cooperation. In evolutionary games, the strategy reflects the action of each individual that warrants the highest utility in a competitive setting. We therefore assume that identical strategies on the two networks reinforce themselves by lessening their propensity to change. Besides network reciprocity working in favour of cooperation on each individual network, we observe the spontaneous emergence of correlated behaviour between the two networks, which further deters defection. If information is shared not just between individuals but also between groups, the positive effect is even stronger, and this despite the fact that information sharing is implemented without any assumptions with regard to content.
Ključne besede: cooperation, information, social dilemma, public goods, interdependent networks, statistical physics of social systems
Objavljeno v DKUM: 03.07.2017; Ogledov: 1048; Prenosov: 388
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10. Evolution of cooperation on scale-free networks subject to error and attackMatjaž Perc, 2009, izvirni znanstveni članek Opis: We study the evolution of cooperation in the prisoner's dilemma and the snowdrift game on scale-free networks that are subjected to intentional and random removal of vertices. We show that, irrespective of the game type, cooperation on scale-free networks is extremely robust against random deletionof vertices, but declines quickly if vertices with the maximal degree are targeted. In particular, attack tolerance is lowest if the temptation to defect is largest, whereby a small fraction of removed vertices suffices to decimate cooperators. The decline of cooperation can be directly linked to the decrease of heterogeneity of scale-free networks that sets in due to the removal of high degree vertices. We conclude that the evolution of cooperation is characterized by similar attack and error tolerance as was previously reported for information readiness and spread of viruses on scale-free networks.
Ključne besede: evolutionary game theory, social dilemma, spatial games, complex networks
Objavljeno v DKUM: 30.06.2017; Ogledov: 1378; Prenosov: 350
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