Revealing the relationship network behind link spam

Author(s):  
Apostolis Zarras ◽  
Antonis Papadogiannakis ◽  
Sotiris Ioannidis ◽  
Thorsten Holz
Author(s):  
Tatiani De Azevedo Lobo ◽  
Marli M. Moraes Da Costa

Resumo: O presente ensaio busca apresentar e fomentar algumas questões pertinentes ao debate contemporâneo sobre a pobreza, demonstrando a importância do tema no cenário mundial. Para tanto, inicialmente discorre-se sobre a construção histórico-social da pobreza e suas características contemporâneas. Com efeito, aponta-se a limitação dos fatores tradicionalmente apresentados como causadores da pobreza, como cultura, genética, geografia etc. Além disso, apresentam-se as formas atuais de monitorar o fenômeno, como o coeficiente de Gini e o IDH. Posteriormente, aborda-se a distribuição mundial da pobreza. Nesse ponto, colaciona-se que a pobreza é um problema mundial. No entanto, é perceptível que o Sul ainda concentra maior número de indivíduos pobres do que o Norte. Na esteira dos últimos dados da pesquisa realizada pelas Nações Unidas, houve uma nítida ascensão do Sul, especialmente nos indicadores sociais ligados à educação. A seguir, trata-se do capital social e da Teoria das Capacidades, apresentando-se novas abordagens da pobreza. Assim, o capital social trata de uma ideia utilizada para verificar a rede de relacionamento dos indivíduos. Já a Teoria das Capacidades está ligada com a ideia de oportunidade da liberdade. Por fim, estuda-se as políticas públicas, bem como seu aspecto fragmentário. Conclui-se, assim, sobre a necessidade de implementação de políticas públicas elaboradas sob a égide de novos paradigmas, a fim de possibilitar o tratamento específico do fenômeno da pobreza, conforme as peculiaridades de cada local. Para tanto foi utilizado neste trabalho o método de abordagem hipotético-dedutivo, o método de procedimento monográfico e a técnica de pesquisa, operacionalizados por meio do emprego de vasta pesquisa bibliográfica. Abstract: This essay seeks to provide and foster some relevant to the contemporary debate on poverty issues, demonstrating the importance of the issue on the world stage. For this purpose, initially spoke about the historical and social construction of poverty and its contemporary features. Indeed, he pointed out the limitation of the factors traditionally presented as the cause of poverty, as a culture, genetics, geography, etc. Furthermore, we presented the current ways of monitoring the phenomenon, such as the Gini coefficient and the HDI. Subsequently addressed the global distribution of poverty. At this point, if collated that poverty is a worldwide problem. However, it is apparent that the South still more concentrated than the poor North individuals. In the wake of recent data from research conducted by the United Nations, there was a sharp rise in the South, especially in social indicators related to education. Next, we treated the capital and the Theory of Capabilities, presenting new approaches to poverty. Thus, social capital is an idea used to verify the relationship network of individuals. Already Capabilities Theory is linked with the idea of freedom of opportunity. Finally, we studied public policy, as well as its fragmentary appearance. Thus, it is concluded on the need to implement public policies prepared under the aegis of new paradigms to enable specific treatment of the phenomenon of poverty, according to the peculiarities of each site. For that was used in this work the method of hypothetical-deductive approach, the method of procedure and the monographic research technique, operationalized through the use of extensive academic research.


Author(s):  
Hua Li ◽  
Qingqing Lou ◽  
Qiubai Sun ◽  
Bowen Li

In order to solve the conflict of interests of institutional investors, this paper uses evolutionary game model. From the point of view of information sharing, this paper discusses four different situations. Only when the sum of risk and cost is less than the penalty of free riding, the evolution of institutional investors will eventually incline to the stable state of information sharing. That is, the phenomenon of hugging. The research shows that the institutional investors are not independent of each other, but the relationship network of institutional investors for the purpose of information exchange. The content of this paper enriches the research on information sharing of institutional investors.


2018 ◽  
Vol 2018 ◽  
pp. 1-16
Author(s):  
Jun Long ◽  
Lei Zhu ◽  
Zhan Yang ◽  
Chengyuan Zhang ◽  
Xinpan Yuan

Vast amount of multimedia data contains massive and multifarious social information which is used to construct large-scale social networks. In a complex social network, a character should be ideally denoted by one and only one vertex. However, it is pervasive that a character is denoted by two or more vertices with different names; thus it is usually considered as multiple, different characters. This problem causes incorrectness of results in network analysis and mining. The factual challenge is that character uniqueness is hard to correctly confirm due to lots of complicated factors, for example, name changing and anonymization, leading to character duplication. Early, limited research has shown that previous methods depended overly upon supplementary attribute information from databases. In this paper, we propose a novel method to merge the character vertices which refer to the same entity but are denoted with different names. With this method, we firstly build the relationship network among characters based on records of social activities participating, which are extracted from multimedia sources. Then we define temporal activity paths (TAPs) for each character over time. After that, we measure similarity of the TAPs for any two characters. If the similarity is high enough, the two vertices should be considered as the same character. Based on TAPs, we can determine whether to merge the two character vertices. Our experiments showed that this solution can accurately confirm character uniqueness in large-scale social network.


2019 ◽  
Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
Hai-Cheng Yi ◽  
Kai Zheng ◽  
Yan-Bin Wang

AbstractMotivationEffectively representing the MeSH headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify.ResultsIn this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships) which can be constructed by the rule of tree num. Then, five graph embedding algorithms including DeepWalk (DW), LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed method, we carried out the node classification and relationship prediction tasks. The experimental results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the distinguishable ability of vectors. Thus, it can act as input and continue to play a significant role in any disease-, drug-, microbe- and etc.-related computational models. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network [email protected]


Author(s):  
Lun-song Chen ◽  
Bi-Lin Sun

Based on the survey data of Lishui City, Zhejiang Province, this paper uses the Heckman two-stage model to construct a credit constraint function without selection bias, and explores the relationship between the scale and quality of the relationship network and the credit constraints of rural households. Research shows that the scale of the relationship network is affected adversely by urbanization and networking, having a weaker impact on the formal credit constraints of rural households. The quality of the relationship networks can improve farmers’ awareness of formal credit, reduce transaction exposure, regulate farmers’ behavior and act as a “guarantee”, thereby effectively alleviating farmers’ formal credit constraints. At the same time, the relationship network of farmers is gradually becoming more structured, where farmers' social interests are becoming more purposeful. Additionally, formal financial institutions have set a threshold for farmers’ credit, which requires a certain amount of securities for money.


AWARI ◽  
2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Nicolás Vladimir Chuchco

The measurement of “good governance” has become an object of (e) valuation by international actors. In this regard, it has occupied the attention of investors, donors, private companies, development agencies, academics, journalists, governments, and credit organizations in the last 30 years, accompanied by a greater flow of international investments to under developed economies. Among these indicators, the Worldwide Governance Indicators (WGI) produced by the World Bank stand out. Although these numbers are not used directly by the Bank to condition resources, they are used by organizations such as the Millennium Challenge Corporation (MCC) to decide in which countries allocate financial aid based on the results of some of the dimensions of these indicators. For this reason, this work seeks to investigate the relationships networks that exist between the indicators and the organizations that participate in providing data, asking about what type of organizations produce inputs of certain dimensions, what relationships they have with each other and with others, in terms of participation, and where the central houses that produce these inputs are located geographically. For this, we have analyzed and characterized the relationship network of production about four dimensions of the WGI indicators, according to the organizations that provided data for South America during the period 2017-2018. The main results obtained indicate that a small number of international organizations in the Northern hemisphere have greater participation in the supply of inputs, highlighting private companies or organizations linked to them.


2012 ◽  
pp. 883-896
Author(s):  
Liang Chen ◽  
Anna Wiewiora ◽  
Bambang Trigunarsyah

In sustainable development projects, as well as other types of projects, knowledge transfer is important for the organisations managing the project. Nevertheless, knowledge transfer among employees does not happen automatically and it has been found that the lack of social networks and the lack of trust among employees are the major barriers to effective knowledge transfer. Social network analysis has been recognised as a very important tool for improving knowledge transfer in the project environment. Transfer of knowledge is more effective where it depends heavily on social networks and informal dialogue. Based on the theory of social capital, social capital consists of two parts: conduits network and resource exchange network. This research studies the relationships among performance, the resource exchange network (such as the knowledge network) and the relationship network (such as strong ties network, energy network, and trust network) at the individual and project levels. The aim of this chapter is to present an approach to overcoming the lack of social networks and lack of trust to improve knowledge transfer within project-based organisations. This is to be done by identifying the optimum structure of relationship networks and knowledge networks within small and medium projects. The optimal structure of the relationship networks and knowledge networks is measured using two dimensions: intra-project and inter-project. This chapter also outlines an extensive literature review in the areas of social capital, knowledge management and project management, and presents the conceptual model of the research approach.


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Asim Shahzad ◽  
Nazri Mohd Nawi ◽  
Muhammad Zubair Rehman ◽  
Abdullah Khan

In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.


Author(s):  
Zhen-Hao Guo ◽  
Zhu-Hong You ◽  
De-Shuang Huang ◽  
Hai-Cheng Yi ◽  
Kai Zheng ◽  
...  

Abstract Effectively representing Medical Subject Headings (MeSH) headings (terms) such as disease and drug as discriminative vectors could greatly improve the performance of downstream computational prediction models. However, these terms are often abstract and difficult to quantify. In this paper, we converted the MeSH tree structure into a relationship network and applied several graph embedding algorithms on it to represent these terms. Specifically, the relationship network consisting of nodes (MeSH headings) and edges (relationships), which can be constructed by the tree num. Then, five graph embedding algorithms including DeepWalk, LINE, SDNE, LAP and HOPE were implemented on the relationship network to represent MeSH headings as vectors. In order to evaluate the performance of the proposed methods, we carried out the node classification and relationship prediction tasks. The results show that the MeSH headings characterized by graph embedding algorithms can not only be treated as an independent carrier for representation, but also can be utilized as additional information to enhance the representation ability of vectors. Thus, it can serve as an input and continue to play a significant role in any computational models related to disease, drug, microbe, etc. Besides, our method holds great hope to inspire relevant researchers to study the representation of terms in this network perspective.


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