The Social Feature-Based Priority Relation Graph of Mobile Social Networks

It has been recently assessed that the quantity of social media clients are generally around two billion; in addition, it is foreseen that this number would altogether ascend in an incentive because of the expanding utilization of PDAs, which thus brings about the expanding utilization of mobile social networks. Developed nations have their own guideline for posting and getting to the substance from/to the social media. Numerous nations didn’t outline any guideline for posting internet based social media substance. This paper dismembers about the peril components of social media and the proposed guideline of the government of India for Social Media posting. The purpose of this investigation is to make the attention about the social media issues and the need of immediate and effective regulation against the publication and proliferation of sexually abusive web content like kid erotic entertainment, assault and assault recordings and frightful material through Internet.

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Link Prediction in Facebook using Web Scrapping and Deep Learning Techniques

International Journal of Advanced Trends in Computer Science and Engineering ◽

10.30534/ijatcse/2021/271012021 ◽

2021 ◽

Vol 10 (1) ◽

pp. 194-197

Keyword(s):

Social Networks ◽

Deep Learning ◽

Link Prediction ◽

Machine Learning Techniques ◽

Feature Engineering ◽

Internet Technologies ◽

Learning Techniques ◽

The Social ◽

Feature Based ◽

Day By Day

As Internet technologies develop continuously social networks are getting more popular day by day. People are connected with each other via virtual applications. Using the Link Prediction in social networks more people get connected, may be they are friends, may be work together at the same workplace and may be their education are. Machine learning techniques are used to analyze the link between the nodes of the network and also create a better link prediction model through deep learning. The objective of this research is to measure the performance using the different techniques to predict link between the social networks. Using deep learning, feature engineering can be reduced for link prediction. In this research, the feature based learning is used to predict the link for better performance. Dataset is obtained by scraping the profile of Facebook users and they are used along with the random forest and graph convolution neural network to measure the performance of link prediction in social networks.

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Dynamic social feature-based diffusion in mobile social networks

2015 IEEE/CIC International Conference on Communications in China (ICCC) ◽

10.1109/iccchina.2015.7448738 ◽

2015 ◽

Cited By ~ 1

Author(s):

Xiao Chen ◽

Kaiqi Xiong

Keyword(s):

Social Networks ◽

Mobile Social Networks ◽

Feature Based

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Cognitive maps of social features enable flexible inference in social networks

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2021699118 ◽

2021 ◽

Vol 118 (39) ◽

pp. e2021699118

Author(s):

Jae-Young Son ◽

Apoorva Bhandari ◽

Oriel FeldmanHall

Keyword(s):

Social Networks ◽

Computational Models ◽

Cognitive Maps ◽

Machine Learning Algorithms ◽

Open Questions ◽

Feature Spaces ◽

The Social ◽

Social Features ◽

Feature Based ◽

Statistical Relationships

In order to navigate a complex web of relationships, an individual must learn and represent the connections between people in a social network. However, the sheer size and complexity of the social world makes it impossible to acquire firsthand knowledge of all relations within a network, suggesting that people must make inferences about unobserved relationships to fill in the gaps. Across three studies (n = 328), we show that people can encode information about social features (e.g., hobbies, clubs) and subsequently deploy this knowledge to infer the existence of unobserved friendships in the network. Using computational models, we test various feature-based mechanisms that could support such inferences. We find that people’s ability to successfully generalize depends on two representational strategies: a simple but inflexible similarity heuristic that leverages homophily, and a complex but flexible cognitive map that encodes the statistical relationships between social features and friendships. Together, our studies reveal that people can build cognitive maps encoding arbitrary patterns of latent relations in many abstract feature spaces, allowing social networks to be represented in a flexible format. Moreover, these findings shed light on open questions across disciplines about how people learn and represent social networks and may have implications for generating more human-like link prediction in machine learning algorithms.

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As Manifestações no Brasil e a formação de redes sociais móveis no contexto da sociedade atual │ The protests in Brazil and the formation of mobile social networks in the context of today's society

Liinc em Revista ◽

10.18617/liinc.v10i1.660 ◽

2014 ◽

Vol 10 (1) ◽

Author(s):

Sandra Henriques

Keyword(s):

Social Networks ◽

Mobile Communication ◽

Online Social Networks ◽

Information Technologies ◽

Mobile Social Networks ◽

Information And Communications Technologies ◽

The Social ◽

Communications Technologies ◽

Social Protests ◽

Mobile Information

RESUMO Este artigo propõe-se a compreender como as manifestações sociais no Brasil, ocorridas em junho de 2013, foram difundidas por meio das redes sociais na internet e como as tecnologias móveis de comunicação e informação tiveram papel chave na ampliação e potencialização dessas informações na sociedade brasileira durante os eventos, transformando-os em redes sociais conectadas por aparatos móveis. O artigo utiliza o método fenomenológico-hermenêutico (GAMBOA, 2002) como suporte para o questionamento acerca de como as redes sociais móveis podem ser observadas nas manifestações sociais ocorridas no Brasil em junho de 2013. O referencial teórico traz como aporte os estudos relacionados às redes sociais na internet (RECUERO, 2009), às tecnologias móveis de comunicação e informação (MANOVICH, 2005; SANTAELLA, 2013) e às manifestações sociais (CASTELLS, 2013), dentre outros. Durante o processo, foi possível observar que a utilização das tecnologias móveis de comunicação e informação foi fundamental para a ampliação e disseminação das manifestações sociais no Brasil e para a formação de redes sociais móveis.Palavras-chave: Redes sociais na internet; Tecnologias móveis de comunicação e informação; Redes sociais móveis; Manifestações sociais no Brasil. ABSTRACT This paper tries to comprehend how the social protests that happened in June 2013 in Brazil radiated through social networks in the web and how mobile communication and information technologies had a key role in amplifying and empowering this information in Brazilian society during those events, turning them into social networks connected through mobile devices. This paper uses the phenomenological-hermeneutics method (GAMBOA, 2002) to support the question as to how mobile social networks can be observed in the 2013 social demonstrations in the country. The theoretical references stand on studies about online social networks (RECUERO, 2009), mobile information and communications technologies (MANOVICH, 2005; SANTAELLA, 2013) and social protests (CASTELLS, 2013), among others. During this process, it was possible to observe that the use of mobile information and communications technologies was essential to amplify and spread the social demonstrations in Brazil and to form mobile social networks. Keywords: Social networks on the Internet; Mobile communication and information technologies; Mobile social networks; Social manifestations in Brazil.

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