Gotowe bibliografie tematyczne / Social networks

Gotowa bibliografia na temat „Social networks”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 31 sierpnia 2024

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Artykuły w czasopismach na temat "Social networks"

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Dunbar, Robin. "Social networks: Human social networks". New Scientist 214, nr 2859 (kwiecień 2012): iv—v. http://dx.doi.org/10.1016/s0262-4079(12)60856-2.

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Trevillion, S. "Social work, social networks and network knowledge". British Journal of Social Work 30, nr 4 (1.08.2000): 505–17. http://dx.doi.org/10.1093/bjsw/30.4.505.

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Sharma, Anita, i Prashant Salwan. "Network Matters! Revisiting Social Networks". Academy of Management Proceedings 2017, nr 1 (sierpień 2017): 17317. http://dx.doi.org/10.5465/ambpp.2017.17317abstract.

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Gemici, Kurtuluş, i Anthony Vashevko. "Visualizing Hierarchical Social Networks". Socius: Sociological Research for a Dynamic World 4 (1.01.2018): 237802311877298. http://dx.doi.org/10.1177/2378023118772982.

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The authors propose a novel technique for the visualization of networks that contain a hierarchical structure: networks in which certain nodes and groups of nodes can be classified through a relation of precedence. Networks with a hierarchical structure frequently arise in sociology and various other disciplines, but the existing methods for visualizing such networks leave much to be desired. The method developed in this work builds on the tradition of visualization in social network analysis; it aims to simultaneously represent the positions of different nodes and the relationships between groups containing the nodes in the network. As such, the proposed visualization method facilitates theoretical and empirical analysis of social structures by algorithmically combining information from the underlying network with the information from the hierarchical structure of the network. The authors illustrate the proposed method with social networks examined through cohesive blocking and k-core decomposition.
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Jadhav, Pranavati, i Dr Burra Vijaya Babu. "Detection of Community within Social Networks with Diverse Features of Network Analysis". Journal of Advanced Research in Dynamical and Control Systems 11, nr 12-SPECIAL ISSUE (31.12.2019): 366–71. http://dx.doi.org/10.5373/jardcs/v11sp12/20193232.

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Zenkovich, K., T. Zhylkybayev, S. Kaysanov i T. Ustinova. "APPLYING SOCIAL MINING RESULTS FROM OPEN SOCIAL NETWORKS". Bulletin of Shakarim University. Technical Sciences 1, nr 2(14) (29.06.2024): 5–10. http://dx.doi.org/10.53360/2788-7995-2024-2(14)-1.

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TThe advent of web-based communities and social networking sites has resulted in a massive amount of social networking data that is embedded with rich sets of meaningful social media knowledge. Social network analysis and the study of social structures using networks and graph theory help to find a systematic method or process for studying social networks. The article reveals the concept of intellectual analysis of social networks. The key aspect of the article is the application of the results of social network analysis to various branches of human activity.Describes the benefits of using Social Mining to identify patterns in big data. Using Social Mining mechanisms, you can find non-trivial and, at first glance, non-obvious patterns in large volumes of information. The article provides examples of software that can be used to quickly collect and analyze data from social networks. Analytics services simplify work and increase opportunities on social networks. Social network analysis provides an effective system for discovering and interpreting online social connections.Social network analytics goes beyond counting likes, reposts and links. This is a comprehensive indepth data analysis that helps to understand what attracts more attention or guide users when accessing the brand through social networks.
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Smith, Edward Bishop, Raina A. Brands, Matthew E. Brashears i Adam M. Kleinbaum. "Social Networks and Cognition". Annual Review of Sociology 46, nr 1 (30.07.2020): 159–74. http://dx.doi.org/10.1146/annurev-soc-121919-054736.

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Social network analysis, now often thought of simply as network science, has penetrated nearly every scientific and many scholarly fields and has become an indispensable resource. Yet, social networks are special by virtue of being specifically social, and our growing understanding of the brain is affecting our understanding of how social networks form, mature, and are exploited by their members. We discuss the expanding research on how the brain manages social information, how this information is heuristically processed, and how network cognitions are affected by situation and circumstance. In the process, we argue that the cognitive turn in social networks exemplifies the modern conception of the brain as fundamentally reprogrammable by experience and circumstance. Far from social networks being dependent upon the brain, we anticipate a modern view in which cognition and social networks coconstitute each other.
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Fuentes Cancell, Dieter Reynaldo, Odiel Estrada Molina i Nilda Delgado Yanes. "Las redes sociales digitales: una valoración socioeducativa. Revisión sistemática." Revista Fuentes 1, nr 23 (2021): 41–52. http://dx.doi.org/10.12795/revistafuentes.2021.v23.i1.11947.

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The future and already current industrial revolution 4.0 demand the introduction of a digital transformation in the higher education contributing to the formation of competent professionals, for which, they are evidenced in the pedagogies and emergent technologies, an increase of didactic experiences in the use of the digital social networks. In this research a systematic review to identify current trends in the use of online social networks for educational purposes are performed. PRISMA protocol was used and analyzed 79 studies present in the database Scopus. In the systematic review, the following questions are answered: What types of designs predominate in the scientific literature? What is the dependentindependent pairs of variables? And What are the current trends in the use of digital social networks for educational purposes? As a result of this research, Facebook is reaffirmed as the social network most used by educators and the need for the integrated and varied use of these networks. It concludes with the defense of the following trends: university institutional communication policies from the curricular levels; the development of creativity, cultural convergence and media diversification; educational innovation; media culture and academic digital identity
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Levin, Ilya, Mark Korenblit i Vadim Talis. "STUDY OF SOCIAL NETWORKS’ DYNAMICS BY SIMULATION WITHIN THE NODEXL-EXCEL ENVIRONMENT". Problems of Education in the 21st Century 54, nr 1 (20.06.2013): 125–37. http://dx.doi.org/10.33225/pec/13.54.125.

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The present study is an analysis of the learning activity, which constitutes simulation of networks and studying their functioning and dynamics. The study is based on using network-like learning environments. Such environments allow building computer models of the network graphs. According to the suggested approach, the students construct dynamic computer models of the networks' graphs, thus implementing various algorithms of such networks’ dynamics. The suggested tool for building the models is the software environment comprising network analysis software NodeXL and a standard spreadsheet Excel. The proposed approach enables the students to visualize the network's dynamics. The paper presents specific examples of network models and various algorithms of the network's dynamics, which were developed based on the proposed approach. Key words: learning environments, modelling, social networks.
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Banham, Gary. "Social networks". Philosophers' Magazine, nr 50 (2010): 22–23. http://dx.doi.org/10.5840/tpm20105038.

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Rozprawy doktorskie na temat "Social networks"

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Schuhart, Russell G. "Hacking social networks examining the viability of using computer network attack against social networks". Thesis, Monterey, Calif. : Naval Postgraduate School, 2007. http://bosun.nps.edu/uhtbin/hyperion.exe/07Mar%5FSchuhart.pdf.

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Thesis (M.S. in Information Systems and Operations)--Naval Postgraduate School, March 2007.
Thesis Advisor(s): David Tucker. "March 2007." Includes bibliographical references (p. 55-56). Also available in print.
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Tarasenko, O. M. "Social networks". Thesis, Sumy State University, 2015. http://essuir.sumdu.edu.ua/handle/123456789/40502.

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Nowadays millions of people use social networks. They got used to surfing on the Internet because it is quick and very easy to discover anything you wish. You don‘t need to think of suggestions and ideas. At least what you need is to be able to type correctly.
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Farry, Michael P. (Michael Patrick). "Sensor networks for social networks". Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/36764.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.
Includes bibliographical references (p. 51-55).
This thesis outlines the development of software that makes use of Bayesian belief networks and signal processing techniques to make meaningful inferences about real-world phenomena using data obtained from sensor networks. The effectiveness of the software is validated by applying it to the problem of detecting face-to-face social interactions between groups of people, given data readings from sensors that record light, temperature, acceleration, sound, and proximity. This application represents a novel method for social network construction which is potentially more accurate and less intrusive than traditional methods, but also more meaningful than newer methods that analyze digitally mediated communication.
by Michael P. Farry.
M.Eng.
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Araújo, Ricardo Matsumura de. "Memetic networks : problem-solving with social network models". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/25515.

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Sistemas sociais têm se tornado cada vez mais relevantes para a Ciência da Computação em geral e para a Inteligência Artificial em particular. Tal interesse iniciou-se pela necessidade de analisar-se sistemas baseados em agentes onde a interação social destes agentes pode ter um impacto no resultado esperado. Uma tendência mais recente vem da área de Processamento Social de Informações, Computação Social e outros métodos crowdsourced, que são caracterizados por sistemas de computação compostos de pessoas reais, com um forte componente social na interação entre estas. O conjunto de todas interações sociais e os atores envolvidos compõem uma rede social, que pode ter uma forte influência em o quão eficaz ou eficiente o sistema pode ser. Nesta tese, exploramos o papel de estruturas de redes em sistemas sociais que visam a solução de problemas. Enquadramos a solução de problemas como uma busca por soluções válidas em um espaço de estados e propomos um modelo - a Rede Memética - que é capaz de realizar busca utilizando troca de informações (memes) entre atores interagindo em uma rede social. Tal modelo é aplicado a uma variedade de cenários e mostramos como a presença da rede social pode melhorar a capacidade do sistema em encontrar soluções. Adicionalmente, relacionamos propriedades específicas de diversas redes bem conhecidas ao comportamento observado para os algoritmos propostos, resultando em um conjunto de regras gerais que podem melhorar o desempenho de tais sistemas sociais. Por fim, mostramos que os algoritmos propostos são competitivos com técnicas tradicionais de busca heurística em diversos cenários.
Social systems are increasingly relevant to computer science in general and artificial intelligence in particular. Such interest was first sparkled by agent-based systems where the social interaction of such agents can be relevant to the outcome produced. A more recent trend comes from the general area of Social Information Processing, Social Computing and other crowdsourced systems, which are characterized by computing systems composed of people and strong social interactions between them. The set of all social interactions and actors compose a social network, which may have strong influence on how effective the system can be. In this thesis, we explore the role of network structure in social systems aiming at solving problems, focusing on numerical and combinatorial optimization. We frame problem solving as a search for valid solutions in a state space and propose a model - the Memetic Network - that is able to perform search by using the exchange of information, named memes, between actors interacting in a social network. Such model is applied to a variety of scenarios and we show that the presence of a social network greatly improves the system capacity to find good solutions. In addition, we relate specific properties of many well-known networks to the behavior displayed by the proposed algorithms, resulting in a set of general rules that may improve the performance of such social systems. Finally, we show that the proposed algorithms can be competitive with traditional heuristic search algorithms in a number of scenarios.
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Trevillion, Steven. "Social work and social networks". Thesis, Brunel University, 1998. http://bura.brunel.ac.uk/handle/2438/5522.

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An exploration of the relationship between patterns of social interaction and social work practice which incorporates thirteen publications. The thread running throughout is the way in which new forms of social care practice are made possible by cross-boundary linkages. A 'Critical Review' sets the context and analyses the works. This is followed by the first published work which applies anthropological models to the study of social marginalisation. The second publication introduces the social network concept and investigates patterns of reciprocity and dependency in social care. The next section of the thesis consists of a 'commentary' on the Griffiths and Wagner Reports. This is followed by a closely related work arguing that there is a fundamental opposition between market and network models of social and community care. The thesis then looks at the ways the culture concept can be used to illuminate the cross-boundary practices associated with community care. The concept of culture and its relationship to cross-boundary working is developed more fully in the next section where it is argued that collaboration culture is paradoxical because it incorporates both respect for difference and a commitment to collective action and that resolving this paradox through collaborative work is a complex and skilled activity. The next section introduces a comparative dimension and suggests that studies of collaboration could be based on looking at the ways in which modern welfare systems try to solve the problem of potential fragmentation and lack of coherence. The work which follows on from this makes use of discourse analysis and network analysis to compare and contrast the rhetoric of partnership and collaboration with the way in which individuals think about their day-to-day cross-boundary work. This raises questions about the changing nature of working relationships in the field of social care and is followed by an investigation into the nature and effects of globalisation on social work in Europe. 'The Co-operation Concept in a Team of Swedish Social Workers' is an attempt to develop a cross-national framework for the analysis of community care focused on the cross-boundary networks of a team of hospital based social workers in Stockholm. The thesis then returns to somewhat broader concerns by means of a work which investigates the contribution of theories of social interaction to theories of social work. These concerns permeate the penultimate section on networking but in a more applied and specific way. The book which constitutes this section of the thesis argues that there is a distinctive theory of networking and that it can be applied to the whole range of social welfare and social care specialisms. The final work explores the impact of globalisation on the ways in which social workers currently experience their roles and develop their sense of professional identity.
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Becirovic, Ema. "On Social Choice in Social Networks". Thesis, Linköpings universitet, Kommunikationssystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138578.

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Kollektiva beslut blir en del av vardagen när grupper av människor står inför val. Vi anpassar ofta våra personliga övertygelser med hänsyn till våra vänner. Vi är naturligt beroende av lyckan hos dem som står oss nära. I det här exjobbet undersöker vi en befintlig empatimodell som används för att välja en vinnare från en uppsättning alternativ genom att använda poängbaserade omröstningsprocedurer. Vi visar att en liten modifikation av modellen är tillräcklig för att kunna använda överlägsna omröstningsprocedurer som bygger på parvisa jämförelser av alternativen. Sammanfattningsvis visar vi att det i grunden inte finns någon anledning att använda poängbaserade omröstningsprocedurer i de föreslagna modellerna, eftersom ett mer önskvärt resultat uppnås genom att använda de överlägsna omröstningsprocedurerna.
Social choice becomes a part of everyday life when groups of people are faced with decisions to make. We often adjust our personal beliefs with the respect to our friends. We are inherently dependent on the happiness of those near us. In this thesis, we investigate an existing empathy model that is used to select a winner in a set of alternatives by using scoring winner selection methods. We show that a slight modification of the model is enough to be able to use superior winner selection methods that are based on pairwise comparisons of alternatives. We show that there is essentially no reason to use scoring winner selection methods in the models proposed as a more desirable result is achieved by using superior winner selection methods.
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Vallapu, Sai Krishna. "Towards Network False Identity Detection in Online Social Networks". Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10246101.

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In this research, we focus on identifying false identities in social networks. We performed a detailed study on different string matching techniques to identify user profiles with real or fake identity. In this thesis, we focus on a specific case study on sex offenders. Sex offenders are not supposed to be online on social networking sites in few states. To identify the existence of offenders in social networks, we ran experiments to compare datasets downloaded from Facebook and offender registries. To identify the most suitable string matching technique to solve this particular problem, we performed experiments on various methods and utilized the most appropriate technique, the Jaro-Winkler algorithm. The major contribution of our research is a weight based scoring function that is capable of identifying user records with full or partial data revealed in social networks. Based on our data samples created using metadata information of Facebook, we were able to identify the sex offender profiles with real identity and seventy percent of the sex offenders with partial information.

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You, Bo. "Hub-Network for Distance Computation in Large Social Networks". Kent State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=kent1412601464.

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Bodriagov, Oleksandr. "Social Networks and Privacy". Licentiate thesis, KTH, Teoretisk datalogi, TCS, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166818.

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Centralized online social networks pose a threat to their users’ privacy as social network providers have unlimited access to users’ data. Decentralized social networks address this problem by getting rid of the provider and giving control to the users themselves, meaning that only the end-users themselves should be able to control access of other parties to their data. While there have been several proposals and advances in the development of privacy- preserving decentralized social networks, the goal of secure, efficient, and available social network in a decentralized setting has not been fully achieved. This thesis contributes to the research in the field of security for social networks with focus on decentralized social networks. It studies encryption-based access control and man- agement of cryptographic keys/credentials (required for this access control) via user accounts with password-based login in decentralized social networks. First, this thesis explores the requirements of encryption for decentralized social networks and proposes a list of criteria for evaluation that is then used to assess existing encryption- based access control systems. We find that all of them provide confidentiality guarantees (of the content itself), while privacy (of information about the content or access policies) is either not addressed at all or it is addressed at the expense of system’s performance and flexibility. We highlight the potential of two classes of privacy preserving schemes in the decen- tralized online social network (DOSN) context: broadcast encryption schemes with hidden access structures and predicate encryption (PE) schemes, and propose to use them. Both of these classes contain schemes that exhibit desirable properties and better fulfill the criteria. Second, the thesis analyses predicate encryption and adapts it to the DOSN context as it is too expensive to use out of the box. We propose a univariate polynomial construction for access policies in PE that drastically increases performance of the scheme but leaks some part of the access policy to users with access rights. We utilize Bloom filters as a means of decreasing decryption time and indicate objects that can be decrypted by a particular user. The thesis demonstrates that adapted scheme shows good performance and thus user experience by making a newsfeed assembly experiment. Third, the thesis presents a solution to the problem of management of cryptographic keys for authentication and communication between users in decentralized online social networks. We propose a password-based login procedure for the peer-to-peer (P2P) setting that allows a user who passes authentication to recover a set of cryptographic keys required for the application. In addition to password logins, we also present supporting protocols to provide functionality related to password logins, such as remembered logins, password change, and recovery of the forgotten password. The combination of these protocols allows emulating password logins in centralized systems. The results of performance evaluation indicate that time required for logging in operation is within acceptable bounds.
Centraliserade sociala online nätverk utgör ett hot mot användarnas integritet. Detta eftersom leverantörer av sociala nätverkstjänster har obegränsad tillgång till användarnas information. Decentraliserade sociala nätverk löser integritetsproblemet genom att eliminera leverantörer och ge användarna kontroll över deras data. Innebörden av detta är att användarna själva får bestämma vem som får tillgång till deras data. Även om det finns flera förslag och vissa framsteg i utvecklingen avseende integritetsbevarande decentraliserade sociala nätverk, har målet om säkra, effektiva, och tillgängliga sociala nätverk i en decentraliserad miljö inte uppnåtts fullt ut. Denna avhandling bidrar till forskning inom säkerhet avseende sociala nätverk med fokus på decentraliserade sociala nätverk. Avhandlingen inriktas på krypteringsbaserad åtkomstkontroll och hantering av kryptografiska nycklar (som krävs för denna åtkomstkontroll) med hjälp av användarkonton med lösenordsbaserad inloggning i decentraliserade sociala nätverk. Först undersöker denna avhandling krav på kryptering för decentraliserade sociala nätverk och föreslår utvärderingskriterier. Dessa utvärderingskriterier används sedan för bedömning av befintliga krypteringsbaserade system för åtkomstkontroll. Vår utredning visar att samtliga garanterar sekretess av själva innehållet. Integritet av information om innehållet eller åtkomstprinciper är dock inte skyddat alls, alternativt skyddade på bekostnad av systemets prestanda och flexibilitet. Vi lyfter fram potentialen i två klasser av integritetsbevarande system i DOSN sammanhang: broadcast-krypteringssystem med dolda tillgångsstrukturer och predikat krypteringssystem; vi föreslår användning av dessa system. Båda dessa klasser innehåller system som uppvisar önskvärda egenskaper och uppfyller kriterier på ett bättre sätt. För det andra analyserar avhandlingen predikat kryptering och anpassar denna till DOSN sammanhang, eftersom det är för dyrt att använda som det är. Vi föreslår en ”univariate polynomial construction” för åtkomstprinciper i predikat kryptering som drastiskt ökar systemets prestanda, men läcker någon del av åtkomstprincipen till användare med åtkomsträttigheter. Vi använder Bloom-filter för att minska dekrypteringstiden och indikera objekt som kan dekrypteras av en viss användare. Genom att göra ett experiment med nyhetsflödessammansättning visas att det anpassade systemet ger goda resultat och därmed användarupplevelse. För det tredje presenterar avhandlingen en lösning på problemet avseende hanteringen av kryptografiska nycklar för autentisering och kommunikation mellan användare i decentraliserade sociala online nätverk. Vi föreslår en lösenordsbaserad inloggningsprocedur för peer-to-peer (P2P) miljön, som gör att användaren som passerar autentisering får återvinna en uppsättning kryptografiska nycklar som krävs för applikationen. Förutom lösenordsinloggning presenterar vi också stödprotokoll för att ge relaterat funktionalitet, såsom inloggning med lagrade lösenord, lösenordsbyte, och återställning av bortglömda lösenord. Kombinationen av dessa protokoll tillåter simulera lösenordsinloggning i centraliserade system. Prestandautvärderingen visar att tiden som krävs för inloggning är inom acceptabla gränser.

QC 20150602

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Ammar, Ammar (Ammar T. ). "Search using social networks". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62635.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 59-61).
In this thesis, we present an approach to the problem of personalized web search which makes use of the searcher's social network, in addition to the hyper-link based score used in most search engines. This combination of social and absolute search scores aims to improve the visibility of information that is relevant to the searcher, while maintaining any absolute measures of document importance . In our approach we adopt a flexible framework for combining information from different sources using Rank Aggregation techniques. Our search system, implemented using Java and Python, covers all the events and web pages present on MIT owned websites. We discuss the theory, design,and implementation of this system in details.
by Ammar Ammar.
M.Eng.
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Książki na temat "Social networks"

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Raatma, Lucia. Social networks. Ann Arbor, Mich: Cherry Lake Pub., 2010.

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Nguyen, Hien T., i Vaclav Snasel, red. Computational Social Networks. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42345-6.

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Panteli, Niki, red. Virtual Social Networks. London: Palgrave Macmillan UK, 2009. http://dx.doi.org/10.1057/9780230250888.

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Abraham, Ajith, i Aboul-Ella Hassanien, red. Computational Social Networks. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4048-1.

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Abraham, Ajith, red. Computational Social Networks. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4051-1.

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Abraham, Ajith, red. Computational Social Networks. London: Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-4054-2.

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Rossmann, Alexander, Gerald Stei i Markus Besch, red. Enterprise Social Networks. Wiesbaden: Springer Fachmedien Wiesbaden, 2016. http://dx.doi.org/10.1007/978-3-658-12652-0.

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Thai, My T., Nam P. Nguyen i Huawei Shen, red. Computational Social Networks. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21786-4.

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Spivet, Bonnie. Using social networks. New York, NY: PowerKids Press, 2012.

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Degenne, Alain. Introducing social networks. London: SAGE, 1999.

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Części książek na temat "Social networks"

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Bolouki, Sadegh, Angelia Nedić i Tamer Başar. "Social Networks". W Handbook of Dynamic Game Theory, 907–49. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-44374-4_32.

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Cioffi-Revilla, Claudio. "Social Networks". W Texts in Computer Science, 89–117. London: Springer London, 2014. http://dx.doi.org/10.1007/978-1-4471-5661-1_4.

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Breslin, John G., Alexandre Passant i Stefan Decker. "Social networks". W The Social Semantic Web, 169–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-01172-6_10.

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Spanke, Matthias. "Social Networks". W Retail Isn't Dead, 71–76. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36650-6_9.

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Bolouki, Sadegh, Angelia Nedić i Tamer Başar. "Social Networks". W Handbook of Dynamic Game Theory, 1–43. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-27335-8_32-1.

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Röll, Franz Josef. "Social Networks". W Handbuch Soziale Praktiken und Digitale Alltagswelten, 1–11. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-08460-8_7-1.

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Schwagereit, Felix, i Steffen Staab. "Social Networks". W Encyclopedia of Database Systems, 1–7. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_1226-2.

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Röll, Franz Josef. "Social Networks". W Handbuch Soziale Praktiken und Digitale Alltagswelten, 117–27. Wiesbaden: Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-08357-1_7.

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Cioffi-Revilla, Claudio. "Social Networks". W Texts in Computer Science, 141–92. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-50131-4_4.

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Schnugg, Claudia. "Social Networks". W Palgrave Studies in Business, Arts and Humanities, 73–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04549-4_5.

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Streszczenia konferencji na temat "Social networks"

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Caragiannis, Ioannis, i Evanthia Tsitsoka. "Deanonymizing Social Networks Using Structural Information". W Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/169.

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We study the following fundamental graph problem that models the important task of deanonymizing social networks. We are given a graph representing an eponymous social network and another graph, representing an anonymous social network, which has been produced by the original one after removing some of its nodes and adding some noise on the links. Our objective is to correctly associate as many nodes of the anonymous network as possible to their corresponding node in the eponymous network. We present two algorithms that attack the problem by exploiting only the structure of the two graphs. The first one exploits bipartite matching computations and is relatively fast. The second one is a local search heuristic which can use the outcome of our first algorithm as an initial solution and further improve it. We have applied our algorithms on inputs that have been produced by well-known random models for the generation of social networks as well as on inputs that use real social networks. Our algorithms can tolerate noise at the level of up to 10%. Interestingly, our results provide further evidence to which graph generation models are most suitable for modeling social networks and distinguish them from unrealistic ones.
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Kumar, Ravi, Alexander Tuzhilin, Christos Faloutsos, David Jensen, Gueorgi Kossinets, Jure Leskovec i Andrew Tomkins. "Social networks". W the 14th ACM SIGKDD international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1402017.

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"Social networks". W 2013 5th Conference on Information and Knowledge Technology (IKT). IEEE, 2013. http://dx.doi.org/10.1109/ikt.2013.6620133.

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Becker, Laura, i Key Pousttchi. "Social networks". W the 14th International Conference. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2428736.2428767.

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Costa, Carlos J., i Manuela Aparicio. "Social networks". W the 2013 International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2503859.2503875.

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"Social networks". W 2016 8th International Symposium on Telecommunications (IST). IEEE, 2016. http://dx.doi.org/10.1109/istel.2016.7881878.

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Ariza, Maurício, Antonio João Gonçalves de Azambuja, Jéferson Campos Nobre i Lisandro Zambenedetti Granville. "Automated Social Engineering Attacks using ChatBots on Professional Social Networks". W Workshop de Gerência e Operação de Redes e Serviços. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/wgrs.2023.747.

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The growth of the internet and social networks has intensified human interactions, raising the risk of cyberattacks. Social Engineering targets those human relationships in the cyber environment, using technology as a support to exploit natural human failures. Research has shown the capacity of Social Engineering attacks, however, there are few papers focusing on the evolution and trust of ChatBots and automation as a support for those attacks. This paper presents an analysis of the capacity of professional social networks to detect and block automated Social Engineering threats to their users. The approach developed allowed us to identify the characteristics of the trust relationship between the user, the social network, and the ChatBot resulting from the established interaction, and failures on the part of social networks to identify and block this kind of behavior. To this end, an automated Social Engineering bot was developed. The analysis and discussion of the results allow demonstration of the security vulnerabilities present in professional networks and in building the user’s trust relationship with the ChatBot.
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Perez, Luis G., Beatriz Montes-Berges i Maria del Rosario Castillo-Mayen. "Boosting social networks in Social Network-Based Recommender System". W 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2011. http://dx.doi.org/10.1109/isda.2011.6121693.

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"Unsocial Networks - Restoring the Social in Social Networks". W 2009 42nd Hawaii International Conference on System Sciences. IEEE, 2009. http://dx.doi.org/10.1109/hicss.2009.486.

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Abufouda, Mohammed, i Katharina Anna Zweig. "Interactions around social networks matter: Predicting the social network from associated interaction networks". W 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2014. http://dx.doi.org/10.1109/asonam.2014.6921574.

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Raporty organizacyjne na temat "Social networks"

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Vyncke, E. IPv6 over Social Networks. RFC Editor, kwiecień 2009. http://dx.doi.org/10.17487/rfc5514.

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Fernandez, Jasmine, Michaela Bonnett, Teri Garstka i Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, czerwiec 2024. http://dx.doi.org/10.61152/hdnz4028https://www.orangesparkleball.com/innovation-library-blog/2024/5/30/sunbelt2024-exploring-social-care-network-structures.

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This research is grounded in the theory that scale-free networks form between many organizations in a community when coordinating social care services and influential hubs in the network emerge (Barabási & Réka, 1999).We explore the variability in the structures of social care networks, focusing on how the diverse needs of community members and the array of providers influence these structures. We posit that the architecture of these networks may hold the key to discerning patterns in community health and social outcomes. Our study examines the resilience of social care networks, defining them as systems designed to enhance interactions among all nodes to meet diverse community needs. We discuss community as a network and community resilience as a process, introducing three key properties—scale-free, small world, and hubness/information spreading scores, for understanding network resilience. We analyzed 20 social care networks, which have been active over an 18-month period using the referral technology tool to send and receive service referrals, providing raw interaction data among organizational nodes. We focused on two primary objectives: 1) Social care networks are more likely to exhibit scale-free properties and contain influential hubs; and 2) There is significant variability among social care networks in terms of scale-free properties and centrality measures. Using the three properties—small world, scale-free, and hubness/information spreading scores—we classified the 20 social care networks into different structural profiles. We analyzed node,edge radius, diameter, to understand the network structure characteristics. Our findings highlighted four distinct network structures, which we ranked from most to least resilient. We discussed the implications of these structures on community-level outcomes, including the potential centralized vulnerability when hubs and information spreaders overlap, creating efficiency during normal operations but also increasing vulnerability to disruptions. Our findings offer insights into the emergent properties of complex systems, particularly in networks intentionally designed to enhance resilience and meet diverse community needs. We conclude by discussing the variability in centrality and structural metrics within the identified groups and propose future research directions to explore the long-term impact of these network structures.
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Fernandez, Jasmine, Michaela Bonnett, Teri Garstka i Meaghan Kennedy. Exploring Social Care Network Structures. Orange Sparkle Ball, czerwiec 2024. http://dx.doi.org/10.61152/hdnz4028.

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This research is grounded in the theory that scale-free networks form between many organizations in a community when coordinating social care services and influential hubs in the network emerge (Barabási & Réka, 1999).We explore the variability in the structures of social care networks, focusing on how the diverse needs of community members and the array of providers influence these structures. We posit that the architecture of these networks may hold the key to discerning patterns in community health and social outcomes. Our study examines the resilience of social care networks, defining them as systems designed to enhance interactions among all nodes to meet diverse community needs. We discuss community as a network and community resilience as a process, introducing three key properties—scale-free, small world, and hubness/information spreading scores, for understanding network resilience. We analyzed 20 social care networks, which have been active over an 18-month period using the referral technology tool to send and receive service referrals, providing raw interaction data among organizational nodes. We focused on two primary objectives: 1) Social care networks are more likely to exhibit scale-free properties and contain influential hubs; and 2) There is significant variability among social care networks in terms of scale-free properties and centrality measures. Using the three properties—small world, scale-free, and hubness/information spreading scores—we classified the 20 social care networks into different structural profiles. We analyzed node,edge radius, diameter, to understand the network structure characteristics. Our findings highlighted four distinct network structures, which we ranked from most to least resilient. We discussed the implications of these structures on community-level outcomes, including the potential centralized vulnerability when hubs and information spreaders overlap, creating efficiency during normal operations but also increasing vulnerability to disruptions. Our findings offer insights into the emergent properties of complex systems, particularly in networks intentionally designed to enhance resilience and meet diverse community needs. We conclude by discussing the variability in centrality and structural metrics within the identified groups and propose future research directions to explore the long-term impact of these network structures.
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McCulloh, Ian, Matthew Webb, John Graham, Kathleen Carley i Daniel B. Horn. Change Detection in Social Networks. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 2008. http://dx.doi.org/10.21236/ada484175.

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Bailey, Michael, Ruiqing Cao, Theresa Kuchler i Johannes Stroebel. Social Networks and Housing Markets. Cambridge, MA: National Bureau of Economic Research, maj 2016. http://dx.doi.org/10.3386/w22258.

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Figlio, David, Sarah Hamersma i Jeffrey Roth. Information Shocks and Social Networks. Cambridge, MA: National Bureau of Economic Research, kwiecień 2011. http://dx.doi.org/10.3386/w16930.

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Fogli, Alessandra, i Laura Veldkamp. Germs, Social Networks and Growth. Cambridge, MA: National Bureau of Economic Research, październik 2012. http://dx.doi.org/10.3386/w18470.

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Macskassy, Sofus. Evolve: Analyzing Evolving Social Networks. Fort Belvoir, VA: Defense Technical Information Center, lipiec 2012. http://dx.doi.org/10.21236/ada564174.

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Acemoglu, Daron, Munther Dahleh, Ilan Lobel i Asuman Ozdaglar. Bayesian Learning in Social Networks. Cambridge, MA: National Bureau of Economic Research, maj 2008. http://dx.doi.org/10.3386/w14040.

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Kerr, William, i Martin Mandorff. Social Networks, Ethnicity, and Entrepreneurship. Cambridge, MA: National Bureau of Economic Research, wrzesień 2015. http://dx.doi.org/10.3386/w21597.

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