The Impact of User Diversity on the Willingness to Disclose Personal Information in Social Network Services

2013 ◽  
pp. 174-193 ◽  
Author(s):  
Anne Kathrin Schaar ◽  
André Calero Valdez ◽  
Martina Ziefle
Keyword(s):  
Social Network ◽  
Personal Information ◽  
Network Services ◽  
Willingness To Disclose ◽  
Social Network Services ◽  
The Impact

scholarly journals The Impact of South Korea Golf Resort Social Network Services Advertising and Online Word of Mouth on Consumer Brand Value

2020 ◽  
Vol 12 (11) ◽  
pp. 4339 ◽  
Author(s):  
Taesoo Cho ◽  
Taeyoung Cho ◽  
Guosong Zhao ◽  
Hao Zhang
Keyword(s):  
Social Network ◽  
South Korea ◽  
Word Of Mouth ◽  
Low Cost ◽  
Network Services ◽  
Online Word Of Mouth ◽  
Consumer Experiences ◽  
Social Network Services ◽  
The Impact ◽  
Positive Effect

Today, social network services (SNS) advertising is frequently utilized by enterprises to communicate with consumers as it provides the best marketing effect using low-cost media. Since the value of SNS is increasing, managers need to look for more effective methods of utilizing the existing SNS channels. This study aims to provide suggestions for attracting customers and gaining an advantage amid the stiff competition among similar golf courses. To achieve the goal of this study, a questionnaire-based survey was conducted at six golf resorts in South Korea where SNS advertising has been used to enhance consumer experiences. The study found that SNS advertising and online word of mouth regarding golf resorts have a positive effect on emotive, social, and price values. Moreover, SNS advertising for golf resorts had a positive effect on the quality function value, while online word of mouth had no effect.

scholarly journals Factors influencing students’ satisfaction and its impact on their loyalty for the University: Case Study at The University of Jordan-Aqaba Branch

2022 ◽  
Vol 11 (1) ◽  
pp. 1-18
Author(s):  
Prof. Dr. Ra’ed Masa’deh ◽  
◽  
Maram Omar Alsmadi ◽  
Ahed Mostafa Ameen Alsmadi ◽  
Ala'a Ziad Zayyad ◽  
...  
Keyword(s):  
Social Network ◽  
Positive Impact ◽  
Network Services ◽  
Measurement Tool ◽  
Social Network Services ◽  
University Of Jordan ◽  
The University ◽  
The Impact ◽  
Students Satisfaction

This study aimed to measure the impact of several antecedent factors on student’s satisfaction (i.e., academic aspects, non-academic aspects, program issues, reputation, access, quality of university facility, university location and social network services) and the mediator factor of students’ satisfactions' impact on student’s loyalty on the university of Jordan-Aqaba Brunch. Measurement tool was developed to examine the relationship between the study variables. The sample of 379 was used from the university of Jordan-Aqaba brunch students. Results indicated that academic aspects, non-academic aspects, reputation, university location and social network services impacted students' satisfaction directly. In the other hand, program issues, access and quality of university facility did not impact students' satisfaction. However, there was a positive impact of students' satisfaction on students' loyalty.

scholarly journals Extraction of mosaic regions through projection and filtering of features from image big data

2021 ◽  
Vol 18 (2) ◽  
pp. 553-574
Author(s):  
Seok-Woo Jang
Keyword(s):  
Big Data ◽  
Social Network ◽  
Aspect Ratio ◽  
Human Body ◽  
Personal Information ◽  
Multimedia Data ◽  
Network Services ◽  
Geometrical Features ◽  
The Face ◽  
Social Network Services

When uploading multimedia data such as photos or videos on social network services, websites, and so on, certain parts of the human body or personal information are often exposed. Therefore, it is frequent that the face of a person is blurred out to protect the portrait right of a particular person, and that repulsive objects are covered with mosaic blocks to prevent others from feeling disgusted. In this paper, an algorithm that detects mosaic regions blurring out certain blocks based on the edge projection is proposed. The proposed algorithm initially detects the edge and uses the horizontal and vertical line edge projections to detect the mosaic candidate blocks. Subsequently, geometrical features such as size, aspect ratio and compactness are used to filter the candidate mosaic blocks, and the actual mosaic blocks are finally detected. The experiment results showed that the proposed algorithm detected mosaic blocks more accurately than other methods.

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