Personalized Recommendation System for the Social Network Services Based on Psychographics

2010 ◽  
Author(s):  
Hoon-Ki Lee ◽  
Jung-Tae Kim ◽  
Jong-Hoon Lee ◽  
Eui-Hyun Paik
Keyword(s):  
Social Network ◽  
Recommendation System ◽  
Network Services ◽  
Personalized Recommendation ◽  
The Social ◽  
Social Network Services

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.

Brand Analysis in Social Network Services: Results from Content Analysis in Twitter Regarding the US Smartphone Market

2017 ◽  
Vol 14 (02) ◽  
pp. 1740008 ◽  
Author(s):  
Arash Hajikhani ◽  
Jari Porras ◽  
Helinä Melkas
Keyword(s):  
Social Network ◽  
Network Services ◽  
Innovation Strategy ◽  
User Profiles ◽  
Multiple User ◽  
Front End ◽  
Twitter Data ◽  
The Social ◽  
The Us ◽  
Social Network Services

Marketing is the front-end strategy of firms to communicate the value of their products or services to customers; therefore, innovations in marketing have tremendous value in comparison to the whole innovation strategy of firms. The emergence of social network services (SNSs) as a dominant communication platform among firms and users provides an opportunity to evaluate the innovativeness of a firm’s marketing strategy. With an analysis of Twitter data, the study indicates how users react to content from different profile types. This result could inspire firms and the social media strategists of companies to diversify their content over multiple user profiles.

scholarly journals University campus social network system for knowledge sharing

2012 ◽  
Vol 9 (4) ◽  
pp. 1721-1737 ◽  
Author(s):  
Zhao Du ◽  
Xiaolong Fu ◽  
Can Zhao ◽  
Ting Liu ◽  
Qifeng Liu
Keyword(s):  
Social Network ◽  
Knowledge Sharing ◽  
Evaluation Method ◽  
Online Social Network ◽  
Network Services ◽  
Personalized Recommendation ◽  
Network System ◽  
University Campus ◽  
Digital Resources ◽  
Social Network Services

Public online social network services have achieved dazzling success in recent years. As a result, vertical social network services for universities are expected warmly by campus users. As the majority of activities in university campus are knowledge and social interaction intensive, one of the core functions of campus social network system is to facilitate knowledge sharing on campus. In the cyberspace of universities, knowledge is stored in various kinds of digital resources such as documents, photos, videos etc. In this paper, we discuss the design and implementation of our campus social network system, concentrating on knowledge sharing mechanism in the system. The knowledge sharing mechanism has five features including the utilization of users? personal social network to facilitate the dissemination of digital resources, the use of a six-tuple model based tagging to realize the unified labeling for digital resources, the fine-grained access control based on friend lists for safer knowledge sharing, the adoption of a multiscale evaluation method for digital resources and personalized recommendation for digital resource with social graph based collaborative filtering as its core idea. With all these considerations, we expect to improve the efficiency and effectiveness of knowledge while enlarging the dissemination scope of digital resources carrying it in cyberspace of universities.

scholarly journals Social Overload and Discontinuance Intention on Facebook: A Comparative Study

2021 ◽  
Vol 13 (22) ◽  
pp. 12556
Author(s):  
Chaeyoung Lim ◽  
Jongchang Ahn
Keyword(s):  
Social Network ◽  
Comparative Study ◽  
Cultural Context ◽  
Structural Equation ◽  
Psychological Reactance ◽  
Network Services ◽  
Equation Modeling ◽  
The Social ◽  
Social Features ◽  
Social Network Services

When users begin to feel uncomfortable about the influence of social network services (SNSs) on their lives, they react with various discontinuance behaviors. This comparative study intends to provide a comprehensive explanation of how the fatigue or regret phenomenon is related -to users’ diverse reactions against SNSs. This study attempts to answer two questions: 1) How do specific types of relationships influence social overload from SNS interactions on Facebook? and 2) How does social overload threaten the free usage of services and lead to users’ dissatisfaction with SNSs, and how do these constructs influence users’ intent to discontinue usage of SNSs? To this end, we test a reactance model with Facebook users (n = 433) using Partial Least Squares Structural Equation Modeling (PLS-SEM). This study found significant results of the reactance mechanism using samples from two countries, Korea and Japan, which support the generalizability of the reactance mechanism in SNS fatigue. The path of the psychological reactance mechanism in SNSs could differ by country. We also found that reactions toward persona non grata in SNSs differed by country. Our findings suggest that the specific cultural context should be considered when analyzing social overload in SNSs. In previous studies, insufficient attention has been paid to the social features or contexts of SNS. This study proposes a new categorization of relationships in the context of SNSs through the persona non grata concept. As SNSs are social platforms, emotions perceived from the social features of SNSs are an important construct that motivates people to continue using SNSs. Therefore, promoting free activities for users can be an important strategy for maintaining their motivation to use the service. It should be noted that the sample used in this study was slightly unbalanced by the inclusion of a greater proportion of young participants.

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.

Sign in / Sign up

Export Citation Format

Share Document