Predicting the scale of information diffusion in social network services

2013 ◽  
Vol 20 ◽  
pp. 100-104 ◽  
Author(s):  
Zheng-ren LI ◽  
Ting-jie LÜ ◽  
Wen-hua SHI ◽  
Xiao-hang ZHANG
Keyword(s):  
Social Network ◽  
Information Diffusion ◽  
Network Services ◽  
Social Network Services

Identity Perception and Information Diffusion in Social Network Services

2015 ◽  
Vol 2015 (1) ◽  
pp. 16908
Author(s):  
Young-Kyu Kim ◽  
Dongwon Lee ◽  
Janghyuk Lee ◽  
Ji-Hwan Lee
Keyword(s):  
Social Network ◽  
Information Diffusion ◽  
Network Services ◽  
Social Network Services ◽  
Identity Perception

scholarly journals Privacy-Preserving Discovery of Topic-Based Events from Social Sensor Signals: An Experimental Study on Twitter

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Duc T. Nguyen ◽  
Jai E. Jung
Keyword(s):  
Social Network ◽  
Information Diffusion ◽  
Relevant Information ◽  
Network Services ◽  
Social Software ◽  
Smart Devices ◽  
Social Events ◽  
The Social ◽  
Social Network Services ◽  
Social Sensor

Social network services (e.g., Twitter and Facebook) can be regarded as social sensors which can capture a number of events in the society. Particularly, in terms of time and space, various smart devices have improved the accessibility to the social network services. In this paper, we present a social software platform to detect a number of meaningful events from information diffusion patterns on such social network services. The most important feature is to process the social sensor signal for understanding social events and to support users to share relevant information along the social links. The platform has been applied to fetch and cluster tweets from Twitter into relevant categories to reveal hot topics.

scholarly journals An Information Recommendation Technique Based on Influence and Activeness of Users in Social Networks

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Recommendation Systems ◽  
Network Services ◽  
The Past ◽  
User Behaviors ◽  
User Influence ◽  
User Activity ◽  
Information Recommendation ◽  
Social Network Services

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.

Face hallucination and recognition in social network services

2014 ◽  
Vol 71 (6) ◽  
pp. 2035-2049 ◽  
Author(s):  
Feng Jiang ◽  
Seungmin Rho ◽  
Bo-Wei Chen ◽  
Xiaodan Du ◽  
Debin Zhao
Keyword(s):  
Social Network ◽  
Network Services ◽  
Face Hallucination ◽  
Social Network Services
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