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نتیجه جستجو - social network analysis

تعداد مقالات یافته شده: 99
ردیف عنوان نوع
1 تحلیل شبکه اجتماعی: بررسی ارتباطات برای پیشرفت علم پرستاری نظامی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 30
زمینه: دانشمندان پرستار نظامی در شاخه های وابسته به خدمات گنجانده شده اند (ارتش ، نیروی دریایی ، نیروی هوایی) با مأموریت های مختلف ، اما با هدف منحصر به فرد تولید و انتشار تحقیقات موثر بر سلامتی و رفاه ذینفعان وزارت دفاع.
هدف: این پروژه همکاری بین تحقیقات پرستاری TriService را بررسی می کند اعضای برنامه (TSNRP) ، به دنبال فرصت هایی برای تقویت ، متنوع سازی و گسترش همکاری تحقیقاتی هستند.
روش: تجزیه و تحلیل شبکه های اجتماعی (SNA) تحقیق تجربی از روابط بین بازیگران اجتماعی در سطوح مختلف تجزیه و تحلیل است . یک ارزیابی الکترونیکی SNA و نمونه برداری کلی برای بررسی همکاری های فعلی دانشمندان پرستار نظامی دکترای آماده (136 ( N= استفاده شد.
یافته ها: شبکه همکاری TSNRP دارای ساختار پیچیده خدمات محور است با بازیگران سطح بالا که دیگران به دنبال مشاوره ، دانش یا مهارت آنها هستند و به عنوان اتصالات یا پلهای مختلف در بین شعب خدمات فعالیت می کنند.
بحث: از نظر دانشمندان نظامی ، SNA در شناسایی افراد با نفوذ ، تجسم فرصت های مشاوره درون خدماتی ، طراحی سیاست های پاسخگو و جهت دهی فرصت های شغلی برای دانشمندان تازه کار نقش مهمی دارد.
کلید واژه ها: همکاری های حرفه ای دانشمندان پرستار | تحلیل شبکه اجتماعی | شبکه های اجتماعی | پرستاری نظامی | زمینه
مقاله ترجمه شده
2 A fuzzy based hybrid decision framework to circularity in dairy supply chains through big data solutions
چارچوب تصمیم ترکیبی مبتنی بر فازی برای مدور بودن در زنجیره های تامین لبنیات از طریق راه حل های داده های بزرگ-2021
This study determines the potential barriers to achieving circularity in dairy supply chains; it proposes a framework which covers big data driven solutions to deal with the suggested barriers. The main contribution of the study is to propose a framework by making ideal matching and ranking of big data solutions to barriers to circularity in dairy supply chains. This framework further offers a specific roadmap as a practical contribution while investigating companies with restricted resources. In this study the main barriers are classified as ‘eco- nomic’, ‘environmental’, ‘social and legal’, ‘technological’, ‘supply chain management’ and ‘strategic’ with twenty-seven sub-barriers. Various big data solutions such as machine learning, optimization, data mining, cloud computing, artificial neural network, statistical techniques and social network analysis have been suggested. Big data solutions are matched with circularity focused barriers to show which solutions succeed in overcoming barriers. A hybrid decision framework based on the fuzzy ANP and the fuzzy VIKOR is developed to find the weights of the barriers and to rank the big data driven solutions. The results indicate that among the main barriers, ‘economic’ was of the highest importance, followed by ‘technological’, ‘environmental’, ‘strategic’, ‘supply chain management’ then ‘social and legal barrier’ in dairy supply chains. In order to overcome circularity focused barriers, ‘optimization’ is determined to be the most important big data solution. The other solutions to overcoming proposed challenges are ‘data mining’, ‘machine learning’, ‘statistical techniques’ and ‘artificial neural network’ respectively. The suggested big data solutions will be useful for policy makers and managers to deal with potential barriers in implementing circularity in the context of dairy supply chains.
Keywords: Dairy supply chain | Barriers | Circular economy | Big data solution | Fuzzy ANP - VIKOR | Group decision making system
مقاله انگلیسی
3 Tabu search for min-max edge crossing in graphs
جستجوی تابو برای عبور از لبه های حداقل حداکثر در گراف ها -2020
Graph drawing is a key issue in the field of data analysis, given the ever-growing amount of information available today that require the use of automatic tools to represent it. Graph Drawing Problems (GDP) are hard combinatorial problems whose applications have been widely relevant in fields such as social network analysis and project management. While classically in GDPs the main aesthetic concern is re- lated to the minimization of the total sum of crossing in the graph (min-sum), in this paper we focus on a particular variant of the problem, the Min-Max GDP, consisting in the minimization of the maximum crossing among all egdes. Recently proposed in scientific literature, the Min-Max GDP is a challenging variant of the original min-sum GDP arising in the optimization of VLSI circuits and the design of in- teractive graph drawing tools. We propose a heuristic algorithm based on the tabu search methodology to obtain high-quality solutions. Extensive experimentation on an established benchmark set with both previous heuristics and optimal solutions shows that our method is able to obtain excellent solutions in short computation time.
Keywords: Combinatorial optimization | Graph drawing | Metaheuristics
مقاله انگلیسی
4 Robust link prediction in criminal networks: A case study of the Sicilian Mafia
پیش بینی پیوند قوی در شبکه های جنایی: مطالعه موردی مافیای سیسیلی-2020
Link prediction exercises may prove particularly challenging with noisy and incomplete networks, such as criminal networks. Also, the link prediction effectiveness may vary across different relations within a social group. We address these issues by assessing the performance of different link prediction algorithms on a mafia organization. The analysis relies on an original dataset manually extracted from the judicial documents of operation ‘‘Montagna”, conducted by the Italian law enforcement agencies against individuals affiliated with the Sicilian Mafia. To run our analysis, we extracted two networks: one including meetings and one recording telephone calls among suspects, respectively. We conducted two experiments on these networks. First, we applied several link prediction algorithms and observed that link prediction algorithms leveraging the full graph topology (such as the Katz score) provide very accurate results even on very sparse networks. Second, we carried out extensive simulations to investigate how the noisy and incomplete nature of criminal networks may affect the accuracy of link prediction algorithms. The experimental findings suggest the soundness of link predictions is relatively high provided that only a limited amount of knowledge about connections is hidden or missing, and the unobserved edges follow some kind of generative law. The different results on the meeting and telephone call networks indicate that the specific features of a network should be taken into careful consideration.
Keywords: Criminal networks | Social network analysis | Network science | Link prediction in uncertain graphs
مقاله انگلیسی
5 When all seemed lost. A social network analysis of the waste-related environmental movement in Campania, Italy
یک تحلیل شبکه اجتماعی از جنبش زیست محیطی مربوط به زباله ها در کامپانیا ، ایتالیا-2020
The Italian region of Campania and its capital Naples have epitomized waste management failure in Europe since 2008 when international media covered extensively the waste crisis occurring there. In response to the crisis, the Italian national government took an authoritarian turn in waste policies and criminalized citizens’ grievances and mobilizations against waste-facility siting in Campania. The state authorities’ intervention gained popular consent and obscured the multifaceted and unjust geographies of waste management in the region. It was a serious blow for the waste-related justice movement in Campania. However, just when waste management seemed under control the movement re-emerged stronger and more effective than it had been prior to the 2008 crisis. Activists created a new counter narrative and liberated themselves from the constraints imposed by the repressive measures of the national government. They built a new frame around the unhealthy space, whose expansion, they maintained, was caused by the waste-related contamination. Yet the strength of the movement and its transformation following 2008 can only be fully understood when the structural property and the components of the EJ activists’ networks are also considered. We apply a Social Network Analysis to show how an effective environmental justice movement requires a cohesive and robust network as well as a comprehensive narrative. The waste-related movement in Campania went from being an archipelago of isolated clusters of organizations with a plural but fragmented claims (before 2008), to a tightly interconnected network supporting a unified political platform (after 2008). We link together the reframing of the movement around health issues with the reconfiguration of activist networks. We use the Campania case to show how environmental justice movements might overcome repression and criminalization and progress toward social justice and ecologically sound transformations.
Keywords: Environmental justice | Grassroot environmentalism | Waste management | Social network analysis
مقاله انگلیسی
6 Collaborative relationship discovery in BIM project delivery: A social network analysis approach
کشف رابطه همکاری در تحویل پروژه BIM: یک رویکرد تحلیل شبکه های اجتماعی-2020
A deeper understanding of collaboration among various stakeholders is imperative towards the success of the Building Information Modelling (BIM) enabled project delivery. A systematic research framework is proposed to properly analyze dynamic changes in stakeholders and their relationships by deploying social network analysis (SNA), assisting in stakeholder management. First, the work breakdown structure (WBS) is performed to organize a BIM project (i.e., rail project) into 4 levels: project name, stage, process, and activity. Second, different stakeholders are clarified based on the activity level over the whole project using interviews and surveys. Third, a project-level social network containing both the project ontology and stakeholders is established, from which cooperation information is then precisely extracted and stakeholder-level social networks with only stakeholders being nodes are created. Finally, SNA is carried out at both network- and node- levels. The results show that: (i) It is feasible to mine the collaboration information between different stakeholders through a project-level social network, (ii) The most active and central actor in each stage is continually changing, and the degree centrality and betweenness centrality are polarized between the stakeholders, (iii) There is a trend for a central stakeholder to be active and a broker at the same time, such as architect (#3), BIM coordinator (#4), BIM modeler (#6), civil & structural engineer (#9), and mechanical & electrical engineer (#18), and (iv) BIM coordinator (#4) should be given more attention, especially from the tender stage on. The research can contribute to both theoretical and practical development: (a) A new novel approach that could make the dynamic collaboration characteristics explicit was proposed with SNA, (b) A good knowledge of the dynamic collaboration attributes among different stakeholders in BIM-based rail projects could encourage a better project outcome
Keywords: BIM | Social network analysis | Stakeholder management | Rail projects | Relationship discovery
مقاله انگلیسی
7 Managing minority opinions in micro-grid planning by a social network analysis-based large scale group decision making method with hesitant fuzzy linguistic information
مدیریت نظرات اقلیت ها در برنامه ریزی خرد شبکه ای با استفاده از روش تصمیم گیری گروهی مقیاس بزرگ مبتنی بر تحلیل شبکه های اجتماعی با اطلاعات زبانی فازی مردد-2020
The growth of global electricity demand has put forward higher requirements for power distribution networks. The high cost of the large-scale power system and the voice for the use of renewable energy impel the birth of the micro-grid which plays a complementary role in the power generation of large-scale power system. The construction of micro-grid planning is complex and many stakeholders’ opinions should be considered for a comprehensive evaluation. Furthermore, the development of social big data techniques, such as e-marketplace and e-democracy, makes experts have social relationships among them. This study aims to develop a consensus model to manage minority opinions for largescale group decision making with social network analysis for micro-grid planning. To deal with the vague and uncertain features in complex micro-grid planning problems, experts are supposed to use hesitant fuzzy linguistic term sets to express their opinions. A social network analysis-based clustering method is introduced to classify experts. Besides, in a large-scale group decision making problem, the opinions of experts should be fully considered, especially the minority opinions. This model considers the minority opinions in a micro-grid planning problem and provides an approach to manage these opinions. Finally, we use an illustrative example concerning the micro-grid planning decision making in Ali district in Tibet to demonstrate the effectiveness and practicability of the proposed model.
Keywords: Micro-grid planning | Large-scale group decision making | Social network analysis | Minority opinions | Hesitant fuzzy linguistic term sets | Consensus
مقاله انگلیسی
8 Eco-friendliness and fashion perceptual attributes of fashion brands: An analysis of consumers’ perceptions based on twitter data mining
سازگاری با محیط زیست و ویژگی های ادراکی مد برندهای مد: تحلیلی از درک مصرف کنندگان براساس داده کاوی توییتر-2020
This study explores if there is a convergence between the concepts of fashion and eco-friendliness in consumer perception of a fashion brand.We assume that increased eco-friendly perception will influence the brand image positively, with this impact being much higher for luxury than for high and fast fashion brands. The hypotheses are tested using data collected from Twitter. We analyzed the fashion clothing brands with the highest number of followers on the Socialbakers list and applied a novel social network mining methodology that allows measuring the relationship between each brand and two perceptual attributes (fashion and eco-friendliness). The method is based on attribute exemplarsdthat is, Twitter accounts that represent a perceptual attribute. Our exemplars catalyze social media conversations on fashion (identified in our research by the keywords “fashion,” “glamour,” and “style”) and ecofriendliness (keywords “environment” and “ethical business”). Based on social network analysis theory, we computed a similarity function between the followers of the exemplars and those of the brand. The results suggest that there is a correlation between the fashion and the eco-friendliness perceptual attributes of a brand; however, this correlation is far stronger for luxury brands than for high and fast fashion brands. The difference in the correlations confirms the recent tendency of fashion luxury brand to increasingly consider treating environmental issues as part of their core business and not just as added value to the brand’s offer.
Keywords: Fashion brands | Twitter | Consumer perception | Environment | Ethical business | Brand image | Big data
مقاله انگلیسی
9 Ethical implications of network data in business and management settings
پیامدهای اخلاقی داده های شبکه در تنظیمات کسب و کار و مدیریت-2020
Reflecting on the compilation and analysis of a range of network datasets drawn from our own work and some prominent examples, we consider the ethical challenges in dealing with network data in business and management settings. We argue that the managerial processes that characterize such settings introduce particular ethical sensitivities in the stages of commissioning and research design, and when collecting, analyzing and reporting network data. These sensitivities arise from the imperatives of business, motivations for commissioning network analyses and the legal authority that managers have over employees. We argue that ethical considerations are much more pervasive in business and management network research than in many other fields.In this contribution, we present a range of ethical challenges in network research in business and management settings that arise at several stages of the research process. For each issue identified, we describe the ethical problem and propose mitigation remedies. From this reflection, we suggest guidelines for other researchers to consider when designing research projects in this application area.
Keywords: Research ethics | Business networks | Business and management | Organisational networks | Social network analysis
مقاله انگلیسی
10 Socioscope: I know who you are, a robo, human caller or service number
جامعه شناسی: من می دانم شما چه کسی هستید ، یک روبو ، تماس گیرنده انسانی یا شماره خدمات-2020
Telephony technologies (mobile, VoIP, and fixed) have potentially improved the way we communicate in our daily life and have been widely adopted for business and personal communications. At the same time, scammers, criminals, and fraudsters have also find the telephony network an attractive and affordable medium to target end-users with the advertisement, marketing of legal and illegal products, and bombard them with the huge volume of unwanted calls. These calls would not only trick call recipients into disclosing their private information such as credit card numbers, PIN code which can be used for financial fraud but also causes a lot of displeasure because of continuous ringing. The fraudsters, political campaigners can also use telephony systems to spread malicious information (hate political or religious messages) in real-time through audio or text messages, which have serious political and social consequences if malicious callers are not mitigated in a quick time. In this context, the identification of malicious callers would not only minimize telephony fraud but would also bring peace to the lives of individuals. One way to classifies users as a spammer or legitimate is to get feedback from the call recipients about their recent interactions with the caller, but these systems not only bring inconvenience to callees but also require changes in the system design. The call detail records extensively log the activities of users and can be used to categorize them as the spammer and non-spammer. In this paper, we utilize the information from the call detailed records and proposed a spam detection framework for the telephone network that identifies malicious callers by utilizing the social behavioral features of users within the network. To this extent, we first model the behavior of the users as the directed social graph and then analyze different features of the social graph i.e. the Relationship Network and Call patterns of users towards their peers. We then used these features along with the decision tree to classify callers into three classes i.e. human, spammer and call center. We analyzed the call record data-set consisting of more than 2 million users. We have conducted a detailed evaluation of our framework which demonstrates its effectiveness by achieving acceptable detection accuracy and extremely low false-positive rate. The performance results show that the spammers and call center numbers not only have a large number of non-repetitive calls but also have a large number of short duration calls. Similarly, on the other hand, the legitimate callers have a good number of repetitive calls and most of them interacted for a relatively long duration.
Keywords: Social network analysis | Telephone spam detection | Robocalls | Telephone call records | Telemarketers | User characterization
مقاله انگلیسی
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