Top PDF From Information Cascade to Knowledge Transfer:Predictive Analyses on Social Networks

From Information Cascade to Knowledge Transfer:Predictive Analyses on Social Networks

From Information Cascade to Knowledge Transfer:Predictive Analyses on Social Networks

The study of influence maximization also introduces another problem, i.e., influ- ence estimation. A critical step in the greedy algorithm of influence maximization is to estimate the influence of a node or a set. Kempe et al. [29] left it as an open ques- tion of finding the exact influence, but noted that it can be approximated by Monte Carlo simulation. However, a reasonable approximation requires a large number of simulations (more than 10,000 times) for each seeds set. Subsequent studies in- vestigate various approaches to speed up such estimates [39], [41], [42], [43], [44], [45], [46], [47], by either decreasing the simulation times for Monte-Carlo-based estimations or finding an alternative algorithm. Kimura et al. [46] proposed two closely related algorithms based on shortest paths. Chen et al.’s algorithm [47] is a variant of the shortest path approach. Aggarwal [43] proposed a steady state spread method to estimate the influence. Yang et al. [44] proposed another way to estimate the influence by approximating the influence from in-neighbors as a linear com- bination. While most research worked on cascade size estimation in infinite time, Du [48] studied cascade size estimation within a time period. Cohen [49] proposed algorithm based on sketched method which is able to estimate the influence scale to huge network with billions of edges.
Show more

139 Read more

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

The impact of social networks on knowledge transfer in long-term care facilities: Protocol for a study

assessments are staggered so that roughly one-twelfth of all residents are being assessed each month. We distrib- uted monthly feedback reports to staff individually in the facilities, beginning in January 2009. We followed most rounds of feedback reports with surveys of members of all provider groups to ask about actions taken to modify care processes, with specific emphasis on the aspects of care included in the feedback reports. A sample post- feedback survey is attached in Additional file 1. A key component of this survey is the inclusion of items designed using the TPB [68-70]. There is considerable evidence about how well intentions predict observed behavior [71]. In addition to using the survey items designed using TPB, we are also asking respondents to discuss ways they would plan to use information in the feedback reports. In addition to self-report surveys, we will be conducting observations using time sampling to assess occurrences of discussion of feedback reports and observed changes in practice, following feedback report distribution. We will conduct trend analyses of the monthly data, and provide trend data, not just cross-sec- tional data, in later iterations of the feedback reports.
Show more

10 Read more

Energy information sharing in social networks:  The roles of objective knowledge and perceived understanding

Energy information sharing in social networks: The roles of objective knowledge and perceived understanding

Abstract: As sustainability educators and communication professionals consider various strategies to engage audiences with regard to household energy use, one option now seemingly available is to leverage social networks by encouraging people to share information with others they know. At the same time, we currently do not know enough about the potential spread of energy-related information in this fashion. Whether, when, or how people share energy-related information with peers or family members are crucial questions, for example. Using national survey data from U.S. residents (n=816), we predicted energy information sharing as a function of objective energy knowledge (measured using a factual energy knowledge index), perceived energy understanding, and demographic variables. Our analyses underscored the importance of assessing not only factual energy knowledge but also perceived understanding, as both are equally predictive of energy information sharing frequency (β=.11, p<.05, for objective knowledge and β=.11, p<.01 for perceived understanding). Number of children also predicted energy information sharing, β=.11, p<.01. We discuss the implications of these results for informal energy education efforts in the 21 st century.
Show more

7 Read more

MoL 2013 18: 
  Learning and Knowledge in Social Networks

MoL 2013 18: Learning and Knowledge in Social Networks

A clear area for future work is in creating logics which pay more attention to the interaction involved in information access. The kind of access studied in this thesis was a one-way transfer of information from a source to a learner, which is not how access typically proceeds. Access more commonly involves questions, permission or other kinds of intermediate steps. These in-between steps have epistemic consequences. At the very least, asking questions betrays my igno- rance to others. At the extreme end, asking questions could inform someone of my bad character (e.g.“Do you carry a lot of cash?”) and actually make the knowledge I seek unavailable. While questions and other features of communi- cation have been studied independently in several places [13], it is necessary to incorporate these approaches to get a nuanced picture of what information an agent can actually access.
Show more

62 Read more

Visualization Through Knowledge Representation Model for Social Networks

Visualization Through Knowledge Representation Model for Social Networks

Abstract –Knowledge management is a systematic and organizationally specified process and knowledge management system is all those technological com- ponents; software, hardware, people and processes supporting knowledge management initiative. These initiatives includes work flow maps, web sites, por- tals, document/team management system, data ware- houses, data mining processes, databases, contact lists, virtual teams, collaboration tools, customer re- lationship management, applications and news (Dav- enport and Prusak 1998, Jashapara 2004) [1, 2]. Knowledge is not important per se [3] (Agostini et al 2003) instead the process of knowing, learning and creating knowledge is the relevant aspect [4] (Non- aka and Takeuchi 1995). In this paper knowledge representation is presented in 3D style for the under- standing and visualization of dynamics of complex so- cial networks by developing a TANetworkTool (Task Analysis Network Tool). The standard or normal rep- resentation of a typical social network is through a graph data structure in 2D. The dynamics of larger social networks is so complex some time it becomes difficult to understand the various levels of interac- tions and dependencies just by mere representation through a tree or graph. Although, many analyti- cal methods provide relationship dependencies, role of different nodes and their importance in the net- work. In this paper we are presenting a visualization of networks by rotating the network through vari- ous dimensions to provide a more realistic view to understand the dynamics of complex social networks and complimenting the analytical results. This rep- resentation can also help authorities not necessarily having specific scientific background to understand and perhaps take preventive actions required in cer- tain specific scenarios for example dealing with ter- rorist/covert networks.
Show more

6 Read more

Money, information and heat in social networks dynamics

Money, information and heat in social networks dynamics

The model is a microcanonical ensemble of states and particles. The states are the possible pairs of nodes (i.e. people, sites and alike) which exchange information. The particles are the information bits, which may interpreted as money. In this case money transfer is simulated by bits transfer which is heat (energy). With analogy to bosons gas, we define for these networks’ model: entropy, volume, pressure and temperature. We show that these definitions are consistent with Carnot efficiency (the second law) and ideal gas law. Therefore, if we have two large networks: hot and cold, having temperatures T H and T C , and we remove Q bits (money)
Show more

11 Read more

THE INFORMATION REVELATION AND PRIVACY IN ONLINE SOCIAL NETWORKS

THE INFORMATION REVELATION AND PRIVACY IN ONLINE SOCIAL NETWORKS

The icpm and the ippm do not reveal the result at all and provide full anonymity. Users require more extensive privacy-preservation because they are unfamiliar with the neighbors in close vicinity who may eavesdrop, store, and correlate their personal information at different time periods and locations. The improved protocol only reveals whether the dot product is above or below a given threshold. The threshold value is selected by the user who initiates the profile matching. They pointed out the potential anonymity risk of their protocols. The threshold value must be larger than a pre-defined lower bound (a system parameter) to guarantee user anonymity. The homomorphic encryption schemes that support different operations such as addition and multiplication on cipher texts. The user is able to process the encrypted plaintext without knowing the secret keys. The dot product protocol is lack of verifiable secure computation. The Protocol only reveals whether the dot product is above or below a given threshold. They pointed out the potential anonymity risk of their protocols; an adversary may adaptively adjust the threshold value to quickly narrow down the value range of the victim profile. It Present an enhanced version of the ecpm, called ecpm+, by combining the ecpm with a novel prediction-based adaptive pseudonym change strategy. The performance of the ecpm and the ecpm+ are comparatively studied through extensive trace-based simulations. The ecpm+ achieves significantly higher anonymity strength with slightly larger number of pseudonyms than the ecpm. The msns, users are able to not only surf the Internet but also communicate with peers in close vicinity using short-range wireless communications. The social features exhibited from the behaviour of users, such as, social friendship social selfishness and social morality. It is encouraging that the traditional solutions can be further extended to solve the MSN problems by considering the unique social features. The homomorphic encryption schemes are widely used in data aggregation and computation specifically for privacy-sensitive information. We review the homomorphic encryption scheme that serves a building block of our proposed profile matching protocols. The profile matching protocols are novel since the comparison of attribute values is considered as the matching operation.
Show more

9 Read more

International researcher mobility and knowledge transfer in the social sciences and humanities

International researcher mobility and knowledge transfer in the social sciences and humanities

The second type of knowledge outcome explored here is categorised as the sharing of knowledge practices. Spatially it can be characterised as ‘transnational’, which refers to enduring social connections between two or more sites that are located in different national-cultural contexts (Basch, Glick Schiller, and Szanton Blanc 1994; Faist 2000; Levitt and Glick Schiller 2004). The phrase ‘knowledge practices’ emphasises the embedded, processual, and social nature of the knowledge types in focus. There are at least five features of transnational knowledge practices, the first of which is that they are embedded in place-specific contexts and in the languages and practices of particular communities. The tacitness of this feature was evident in the ways in which the language used by interviewees alluded to its elusive and intangible nature. For example, interviewees referred to the ‘milieu’, ‘environment’, or ‘atmosphere’ they experienced during their stays abroad. Others parsed this into ways of knowing and ways of doing, reporting on the challenges of orienting themselves to new ways of looking at research problems, and to the opportunities to acquire new study and research skills.
Show more

22 Read more

Learning Using Privileged Information: Similarity Control and Knowledge Transfer

Learning Using Privileged Information: Similarity Control and Knowledge Transfer

The original videos were made using aerial cameras of different resolutions: a low reso- lution camera with wide view (capable to cover large areas quickly) and a high resolution camera with narrow view (covering smaller areas and thus unsuitable for fast coverage of terrain). The goal was to make judgments about presence or absence of targets using wide view camera that could quickly span large surface areas. The narrow view camera could be used during training phase for zooming in the areas where target presence was suspected, but it was not to be used during actual operation of the monitoring system, i.e., during test phase. Thus, the wide view camera with low resolution corresponds to standard information (space X), whereas the narrow view camera with high resolution corresponds to privileged information (space X ∗ ).
Show more

27 Read more

Constructing social networks on the basis of task and knowledge networks using WESTT

Constructing social networks on the basis of task and knowledge networks using WESTT

According to Steiner (1972), tasks can be divided into five basic types: additive, compensatory, disjunctive, conjunctive or discretionary. These task types differ in the degree to which effective performance depends upon the "richness" of information transferred between individual group members. McGrath and Hollingshead (1994) proposed that they differ in the amount of additional information they require. Simple, low ambiguity tasks e.g. additive tasks require no additional information beyond the acquisition of facts, and indeed any evaluative or emotional information may be a hindrance to effective performance. In contrast complex, high ambiguity tasks, such as disjunctive tasks, where there are conflicting interpretations about the situation, do require additional information in order to resolve disagreements through the exchange of subjective views. In addition some tasks will comprise of a combination of these task types. Therefore the effectiveness of the group will be determined by how well the interaction of its members fit the requirement of the task.
Show more

18 Read more

Modeling Unintended Personal-Information Leakage from Multiple Online Social Networks

Modeling Unintended Personal-Information Leakage from Multiple Online Social Networks

The US National Science Foundation (NSF) partially funded this work through its Industry-University Coop- erative Research Center, CyberTrust, CISE/Computing Research Infrastructure, and NetSE programs. Other sup- port includes the US National Institutes of Health grant U54 RR 024380-01 and its Clinical and Translational Sci- ence Award program’s PHS grant (UL1 RR025008, KL2 RR025009, or TL1 RR025010), as well as gifts, grants, or contracts from Wipro Technologies, Fujitsu Labs, Ama- zon’s Web Services in Education program, and the Geor- gia Tech Foundation through its John P. Imlay, Jr. Chair endowment. All opinions, findings, conclusions, and rec- ommendations are those of the authors and don’t necessar- ily reflect the views of the NSF or other funding agencies and companies.
Show more

7 Read more

Novel Epistemic and Predictive Heuristic for Semantic and Dynamic Social Networks Analysis

Novel Epistemic and Predictive Heuristic for Semantic and Dynamic Social Networks Analysis

Basically, text analysis and mining produce a set of statistical models which provide a gateway between syn- tactic and semantic levels in text analysis. The J ACCARD index refinement defined in [13], improves the J ACCARD ’s measure of semantic similarity between terms and corpora. The standard Term Frequency (TF) measure introduced in [14], and the Inverse Document Frequency (IDF) defined in [15] are frequently improved as refinements of TF.IDF measures or so called, such as in [16]. Semantic SNA and ontology building benefit each other, as defined in [17] with a three-dimensional model crossing social graphs, annotations (tags) and consensual ontologies. The latest works in semantic SNA aim at making operational the outlines of SNA using ontologies and Semantic Web languages, and pave the way for statistical and semantic analysis of the Social Web [9] [18]. Our applicative work defines and experiments a structure of social graph based on the semantics of the endogenous content and dedicated to semantic SNA. It enables 1) to retrieve the communities and indi- viduals sharing knowledge denoted by keywords, 2) to rank people activities within communities sharing com- mon knowledge, and 3) to detect and to balance stress at work, based on the collective/individual knowledge use and on the knowledge commonly developed within an enterprise social network.
Show more

14 Read more

Effects of the topology of social networks on information transmission

Effects of the topology of social networks on information transmission

In the small-world network example given, the node degree is constant at 4 connections per node. In many real world networks, the distribution of node degrees is not flat, but highly variable. In particular, Barab´asi and Albert (1999) noted that node degrees are often found in a scale-free or exponential distribution. That is, there are many nodes with only a few connections, while a few nodes have many connections. (Another way of putting this is to say that the distribution of node degrees is long- tailed or heavily skewed to the right.) Consider for ex- ample the internet, where most machines are connected to only one or two other machines, whereas major hubs may have many thousands of connections. Barab´asi and Albert suggested the preferential attachment algorithm for generating such networks: nodes are added to the network one at a time, and upon its arrival each node will make one or more connections to existing nodes. However, these connections are not made at random but are allocated preferentially to existing nodes that al- ready have a higher-than-average number of connections. Thus, nodes rich in node degree get even richer as the algorithm continues. Barab´asi and Albert explored the properties of scale-free networks generated using prefer- ential attachment and found that, despite the absence of a regular substrate, they share the critical properties of small world networks: high transitivity and a short aver- age path length. They also have a negative node degree correlation, which means simply that a connection from a high-degree node is likely to lead to a low-degree node and vice versa.
Show more

10 Read more

Cooperative wireless energy harvesting and information transfer in stochastic networks

Cooperative wireless energy harvesting and information transfer in stochastic networks

In this paper, we consider a large-scale wireless ad hoc network with multiple source-destination communication pairs, where the sources operate with wireless energy harvesting. Before data transmission, each source should first harvest the radio frequency energy transferred from its corresponding destination. Since the source-destination distance is long, the efficiency of wireless energy transfer is very low. As a result, the transmission power of the source is weak, which is detrimental to the successful data transmissions. Instead, we introduce a relay in-between each source and destination for the wireless energy transfer and data transmission. The close distance between the relay and the source can improve the energy harvesting efficiency and the data relaying can improve the link robustness. With the assistance from the relay, the area spectrum efficiency is significantly enhanced compared with the non-cooperative system. A series of discrete power levels is defined for the sources and the probability of choosing each power level is analyzed by averaging over the random channel fading. We analyze the data success probabilities through averaging over the uncertain interference caused by the random locations of users, the channel fadings, and the various source transmission powers. The upper and lower approximations of data success probabilities are derived using the stochastic geometry theory for the cooperative energy and data transfer system. The optimal time
Show more

22 Read more

Entrepreneurial Networks and Knowledge Transfer: The Moderating Role of Incubator/Accelerator Affiliation

Entrepreneurial Networks and Knowledge Transfer: The Moderating Role of Incubator/Accelerator Affiliation

There is little empirical evidence on the issue of whether the relationship strength in entrepreneurial networks (RSENs) facilitates tacit knowledge transfer (TKT), and if so, whether incubator/accelerator affiliation affects the relationship between RSENs and TKT. The purpose of this paper is to understand how the startups affiliated to incubator/accelerator (private/public/private-public) are able to improve their innovation capability. This study examines various relationships within the empirical context of Indian manufacturing and service startups. We empirically provide some evidence that formal RSEN influences the extent of TKT, and hence, the innovation capability. The results support that startups in formal entrepreneurial networks gain more if they have public-private incubator/accelerator affiliation. To our knowledge, this is the first attempt to link RSENs to the TKT in the national system of innovation literature. This study also contributes to our understanding of entrepreneurial networks in a non-Western context, i.e., India. In terms of practical implication, it is not only entrepreneurial networks that play an important role in TKT, but also their relationship strength. Hence, we argue that TKT in entrepreneurial networks may be a source of critical competitive advantage for startups in the 21st century. In addition, results provide implication for developing relationship with the members in networks for tacit knowledge. These implications have the potential to direct the policy initiatives.
Show more

15 Read more

Data Efficient Goal Oriented Conversation with Dialogue Knowledge Transfer Networks

Data Efficient Goal Oriented Conversation with Dialogue Knowledge Transfer Networks

In this paper, we present the Dialogue Knowl- edge Transfer Network (DiKTNet), a state- of-the-art approach to goal-oriented dialogue generation which only uses a few example dialogues (i.e. few-shot learning), none of which has to be annotated. We achieve this by performing a 2-stage training. Firstly, we perform unsupervised dialogue representation pre-training on a large source of goal-oriented dialogues in multiple domains, the MetaLWOz corpus. Secondly, at the transfer stage, we train DiKTNet using this representation to- gether with 2 other textual knowledge sources with different levels of generality: ELMo en- coder and the main dataset’s source domains. Our main dataset is the Stanford Multi- Domain dialogue corpus. We evaluate our model on it in terms of BLEU and Entity F1 scores, and show that our approach signifi- cantly and consistently improves upon a se- ries of baseline models as well as over the previous state-of-the-art dialogue generation model, ZSDG. The improvement upon the lat- ter — up to 10% in Entity F1 and the average of 3% in BLEU score — is achieved using only 10% equivalent of ZSDG’s in-domain training data.
Show more

11 Read more

A Predictive Sliding Mode Cascade Controller for Nonholonomic Autonomous Systems

A Predictive Sliding Mode Cascade Controller for Nonholonomic Autonomous Systems

12 As with control of mobile robot systems, the USV control problems can be divided into setpoint position [13– 18] and trajectory tracking [19–27] control. In this paper, several examples of nonlinear control laws for the USV setpoint and trajectory tracking control problems are presented. First, SMCs are presented for tracking [27] and setpoint control [28]. The advantage of these controllers is that they require very little computation and can be implemented on the small scale model USV system. A disadvantage of these controllers, however, is that tuning the control parameters can be very non-intuitive and often the optimal parameters for one initial condition can yield poor performance given different initial conditions. Next, a new MPC method is applied to trajectory tracking and setpoint control [29, 30]. MPC is based on solving an open- loop optimal control problem at each sampling instant. As a result, open-loop optimal performance can be achieved regardless of initial conditions, constraints or disturbances. Another advantage of this method is that the setpoint and trajectory tracking controllers use the same formulation. The disadvantage, however, is that the controller requires significant computation time making it challenging to implement on-line for small scale USV systems with relatively fast dynamics. Therefore, a cascade MPC and SMC is presented which effectively combines the fast computation of the sliding mode tracking controller with the optimal performance of the MPC.
Show more

12 Read more

Knowledge transfer

Knowledge transfer

Abstrakt: Téma transferu znalostí je v příspěvku pojednáno z různých úhlů (kontext, výhody, kanály) s cílem vymezit role, které by měly sehrát univerzity, aby přispěly ke zvýšení konkurenceschopnosti evropské ekonomiky. Transfer zna- lostí zahrnuje široké spektrum činností od přítomnosti v médiích a na veřejných akcích, přes participaci na bilaterálních projektech, komerčním výzkumu, využívání odbornosti v partnerských uskupeních nebo na stážích, až po přizvání širší veřejnosti k úpravám studijních programů v zájmu vyšší kvalifikace absolventů. Dále je v příspěvku předmětem hodnocení kontext, v němž se transfer znalostí odehrává a může přispět k zvýšení jeho efektivnosti. Jsou zde identifikovány i kanály využívané pro přenos znalostí včetně návrhu několika kritérií použitelných pro výběr vhodných kanálů v konkrétních podmínkách. Vzhledem k tomu, výhody transferu znalostí přesahují pouhé finanční výnosy, měly by faktory podporující efektivní zavádění transferu znalostí na univerzitách zahrnovat nejen finanční pobídky, ale také kombinaci opatření od výchovy a vzdělávaní odborníků pro řízení transferu znalostí, přes stanovení vhodných způsobů měření výkonnosti v ob- lasti transferu znalostí, programy pro zajištění kvality a postupy odstraňující bariéry a umožňující mobilitu zaměstnanců a volnou výměnu znalostí.
Show more

6 Read more

Social Movements as Communication Networks in the Information Age

Social Movements as Communication Networks in the Information Age

Fourthly, for broader coverage of audience volunteers distribute messages with a request for the help. The help can be different: dissemination of information, production of leaflets, search of sponsors and funds, monetary help. Very often participants of group organize charity auctions and fairs, which are held both internally and remotely. If the fair is held in reality, then volunteers will organize in the cities an action, at which they sell various things (hand-made articles, clothes, pastries, etc.). The funds raised from sale are transferred to the beneficiary by means of one of the payment options stated above. When holding a remote fair of a condition don't change except that the offered goods are spread in the form of the photo and persons interested can get him by mail. The seller also reports the raised funds for assistance to the beneficiary. Fifthly, as money transfers are received, receipt reports are published on the website or in the group. As a rule, such reports are provided daily. Along with it, reports on expenditure of the received means are surely published, the scanned copies of checks or the photo of the bought things, medicines are provided.
Show more

5 Read more

A Predictive Novel Approach of Information Diffusion Over Static and Dynamic Social Networks L. Saidanaik 1, N. Praveenkumar2

A Predictive Novel Approach of Information Diffusion Over Static and Dynamic Social Networks L. Saidanaik 1, N. Praveenkumar2

Static and dynamic networks classification has become applicable to an extending measure of applications, particularly resulting to the ascent of social platforms and social media. Regardless, execution of existing strategies on real-world images is still fundamentally missing, especially when considered the immense bounced in execution starting late reported for the related task of face acknowledgment. In this paper we exhibit that by learning representations through the use of significant Convolution Neural Systems (CNN), a huge augmentation in execution can be acquired on these errands. To this end, we propose a direct Convolution Neural System engineering can be used despite when the measure of learning data is limited. We survey our procedure on the recent Audience benchmark for static and dynamic networks estimation and demonstrate it to radically outflank current state-of-the-art methods.
Show more

7 Read more

Show all 10000 documents...