Research on China’s city network based on users’ friend relationships in online social networks: a case study of Sina Weibo

GeoJournal ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. 937-946 ◽  
Author(s):  
Zhen Feng ◽  
Wang Bo ◽  
Chen Yingxue
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Sina Weibo ◽  
City Network

scholarly journals Debate on online social networks at the time of COVID-19: An Italian case study

2021 ◽  
Vol 23 ◽  
pp. 100136
Author(s):  
Martino Trevisan ◽  
Luca Vassio ◽  
Danilo Giordano
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Italian Case

Emergent Data Mining Tools for Social Network Analysis

2015 ◽  
pp. 1539-1556
Author(s):  
Dhiraj Murthy ◽  
Alexander Gross ◽  
Alex Takata
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
Network Analysis ◽  
Online Social Networks ◽  
Data Extraction ◽  
Future Directions ◽  
Effective Development ◽  
Mining Tools

This chapter identifies a number of the most common data mining toolkits and evaluates their utility in the extraction of data from heterogeneous online social networks. It introduces not only the complexities of scraping data from the diverse forms of data manifested in these sources, but also critically evaluates currently available tools. This analysis is followed by a presentation and discussion on the development of a hybrid system, which builds upon the work of the open-source Web-Harvest framework, for the collection of information from online social networks. This tool, VoyeurServer, attempts to address the weaknesses of tools identified in earlier sections, as well as prototype the implementation of key functionalities thought to be missing from commonly available data extraction toolkits. The authors conclude the chapter with a case study and subsequent evaluation of the VoyeurServer system itself. This evaluation presents future directions, remaining challenges, and additional extensions thought to be important to the effective development of data mining tools for the study of online social networks.

scholarly journals GroupFound: An effective approach to detect suspicious accounts in online social networks

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772249 ◽  
Author(s):  
Bo Feng ◽  
Qiang Li ◽  
Xiaowen Pan ◽  
Jiahao Zhang ◽  
Dong Guo
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Social Relationship ◽  
False Positive Rate ◽  
High Detection Rate ◽  
Sina Weibo ◽  
Social Communities ◽  
Positive Rate ◽  
Local Graph ◽  
Relationship Of

Online social networks are an important part of people’s life and also become the platform where spammers use suspicious accounts to spread malicious URLs. In order to detect suspicious accounts in online social networks, researchers make a lot of efforts. Most existing works mainly utilize machine learning based on features. However, once the spammers disguise the key features, the detection method will soon fail. Besides, such methods are unable to cope with the variable and unknown features. The works based on graph mainly use the location and social relationship of spammers, and they need to build a huge social graph, which leads to much computing cost. Thus, it is necessary to propose a lightweight algorithm which is hard to be evaded. In this article, we propose a lightweight algorithm GroupFound, which focuses on the structure of the local graph. As the bi-followers come from different social communities, we divide all accounts into different groups and compute the average number of accounts for these groups. We evaluate GroupFound on Sina Weibo dataset and find an appropriate threshold to identify suspicious accounts. Experimental results have demonstrated that our algorithm can accomplish a high detection rate of [Formula: see text] at a low false positive rate of [Formula: see text].

scholarly journals How to measure information similarity in online social networks: A case study of Citeulike

2017 ◽  
Vol 418-419 ◽  
pp. 46-60 ◽  
Author(s):  
Danielle H. Lee ◽  
Peter Brusilovsky
Keyword(s):  
Social Networks ◽  
Online Social Networks

Data mining and social web semantics: a case study on the use of hashtags and memes in Online Social Networks

2017 ◽  
Vol 15 (12) ◽  
pp. 2276-2281 ◽  
Author(s):  
Pedro Pinto ◽  
Ingrhid Theodoro ◽  
Marcos Arrais ◽  
Jonice Oliveira
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Online Social Networks ◽  
Social Web

scholarly journals Comunidades em redes sociais na internet: um estudo de caso dos fotologs brasileiros | Communities in Social Networks on the internet: a case study of Brazilian photologs

2008 ◽  
Vol 4 (1) ◽  
Author(s):  
Raquel Recuero
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Social Ties ◽  
Online Social Network ◽  
Virtual Community ◽  
Capital Social ◽  
Social Forms ◽  
Computer Mediated

Resumo Redes sociais online são grupos de atores que se constituem através da interação mediada pelo computador. Essas interações são capazes de estabelecer novas formas sociais de grupos e comunidades. Através da discussão de diversos conceitos de comunidade e comunidade virtual, propõe-se o estudo das comunidades virtuais como uma forma de rede social. Esse debate teórico é discutido então no campo de estudo constituído pelo Fotolog, durante os anos de 2005 e 2006. O fotolog é um sistema que permite aos usuários a publicação de fotografias, textos e comentários. Dos dados coletados através de formas qualitativas e quantitativas, propomos uma tipologia para as comunidades virtuais baseada em sua estrutura (a rede em si) e sua composição (tipos de laços sociais e capital social). Esses tipos são definidos como comunidades virtuais emergentes, comunidades virtuais de associação e comunidades virtuais híbridas.Palavras-chave redes sociais, comunidades virtuais, fotolog.Abstract Online social networks are groups of actors formed by computer-mediated social interaction. These interactions are capable of establishing new social forms of groups and communities. Based on a discussion over several concepts of community and virtual community we propose the virtual community as a specific form of online social network. This theoretical debate is brought to the field studying the system named Fotolog during 2005 and 2006. Fotolog (www.fotolog.com) is a web service that allows for its users to post photographs or images with an associated text and other users may comment on each other’s posts. From the collected data, we propose a typology for communities found in these networks, based on their structure (network) and composition (social ties and social capital). We define three types of communities as associative virtual communities, emergent virtual communities and hybrid virtual communities.Keywords social networks, virtual communities, fotolog. 

Competitive Influence Blocking in Online Social Networks: A Case Study on WeChat

2018 ◽  
Author(s):  
Chang Yao ◽  
Yuanxing Zhang ◽  
Xiaomei Zhang ◽  
Kaigui Bian ◽  
Lingyang Song
Keyword(s):  
Social Networks ◽  
Online Social Networks
Sign in / Sign up

Export Citation Format

Share Document