A cross-cultural framework for protecting user privacy in online social media

2013 ◽  
Author(s):  
Blase Ur ◽  
Yang Wang
Keyword(s):  
Social Media ◽  
Cross Cultural ◽  
User Privacy ◽  
Online Social Media ◽  
Cultural Framework

scholarly journals Breaking Social Media Bubbles for Information Globalization: A Cross-Cultural and Cross-Language User-Centered Sense-Making Approach

2020 ◽  
Vol 4 (4) ◽  
pp. 297-305
Author(s):  
Xiaozhong Liu ◽  
Daqing He ◽  
Dan Wu
Keyword(s):  
Social Media ◽  
Active Role ◽  
Cross Cultural ◽  
Sense Making ◽  
Research Activities ◽  
Online Social Media ◽  
The Social ◽  
Media Space ◽  
Language User ◽  
Cross Language

AbstractWith the globalization of data, online social media plays an active role in spreading information and classifying people, and thinking about how to break the solidification of algorithms becomes critical. Current algorithmic research in the social media space often focuses on a single service or language, mainly due to the lack of a way to connect the different bubbles. The panel speakers described their various research activities in which they presented different perspectives on how to break the bubble. This article provides a summary of this interactive panel.

scholarly journals Prevention of Clone Attack in Online Social Media Integrating Secure Data Transmission

2021 ◽  
Vol 9 (VI) ◽  
pp. 2961-2967
Author(s):  
Abishek Kashyap. S
Keyword(s):  
Social Media ◽  
Cyber Attacks ◽  
User Privacy ◽  
Sensitive Data ◽  
Contemporary World ◽  
Legitimate User ◽  
Online Social Media ◽  
Secure Data Transmission ◽  
User Data ◽  
The Individual

Social networking is becoming so essential nowadays and is playing a bigger role in every man’s life for sharing information and knowledge. Also social network is used to see the everyday activities, photos, videos, political agendas and propagandas. Therefore, it is now becoming an important tool to stay updated in this dynamic world. With large chunks of data being generated every second, there is a growing concern about Data protection and user privacy in the Social media network. One of the major concerns being, ‘Fake Users’ - misusing the authorized user’s information like photos and videos without the authorized user’s permission and disguising oneself as a legitimate user. In our contemporary world, many fake profiles are being created for fraudulent activities like money making, malware / virus / Trojan distribution to use user data, especially with malicious intent. In this paper Java static watermarking is proposed. Java static watermark is used in our social media website in order to associate each user's footprint with respect to their unique ID, eliminating the crux of fake users. It is also very evident to say that data present on the cloud is no less prone to cyber-attacks. In this paper, integration of steganography methods for protection of sensitive data on the public cloud server is also proposed to validate its viability and its increased security. The Algorithms used ensure the individual information is kept secret and transmitted in a secure manner with user privacy preserving.

scholarly journals Social Bots Detection via Fusing BERT and Graph Convolutional Networks

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 30
Author(s):  
Qinglang Guo ◽  
Haiyong Xie ◽  
Yangyang Li ◽  
Wen Ma ◽  
Chao Zhang
Keyword(s):  
Social Media ◽  
Large Scale ◽  
Social Robot ◽  
Training Data ◽  
User Privacy ◽  
Transductive Learning ◽  
Convolutional Network ◽  
Online Social Media ◽  
Single Text ◽  
Wide Range

The online social media ecosystem is becoming more and more confused because of more and more fake information and the social media of malicious users’ fake content; at the same time, unspeakable pain has been brought to mankind. Social robot detection uses supervised classification based on artificial feature extraction. However, user privacy is also involved in using these methods, and the hidden feature information is also ignored, such as semi-supervised algorithms with low utilization rates and graph features. In this work, we symmetrically combine BERT and GCN (Graph Convolutional Network, GCN) and propose a novel model that combines large scale pretraining and transductive learning for social robot detection, BGSRD. BGSRD constructs a heterogeneous graph over the dataset and represents Twitter as nodes using BERT representations. Corpus learning via text graph convolution network is a single text graph, which is mainly built for corpus-based on word co-occurrence and document word relationship. BERT and GCN modules can be jointly trained in BGSRD to achieve the best of merit, training data and unlabeled test data can spread label influence through graph convolution and can be carried out in the large-scale pre-training of massive raw data and the transduction learning of joint learning representation. The experiment shows that a better performance can also be achieved by BGSRD on a wide range of social robot detection datasets.

Impact of Online Social Media on Consumer Decision Making: A Study in Dehradun

2012 ◽  
Vol 3 (5) ◽  
pp. 379-381
Author(s):  
Dr. Aruna Kumar Mishra ◽  
◽  
Narendra Kumar Narendra Kumar ◽  
Abhishek Sharma
Keyword(s):  
Decision Making ◽  
Social Media ◽  
Consumer Decision Making ◽  
Consumer Decision ◽  
Online Social Media

DERADICALISATION IDEAS IN SOCIAL MEDIA THROUGH THE RELIGIOUS-MULTICULTURAL THERAPY APPROACH TO THE DA'WAH CULTURE

2020 ◽  
Vol 24 (1) ◽  
pp. 58
Author(s):  
Anwar Hafidzi
Keyword(s):  
Social Media ◽  
Real World ◽  
Environmental Conditions ◽  
Islamic Law ◽  
Research Tool ◽  
Therapy Approach ◽  
The Real ◽  
Multicultural Therapy ◽  
Online Social Media ◽  
Library Research

This research begins with an understanding of the endemic radicalism of society, not only of the real world, but also of various online social media. This study showed that the avoidance of online radicalism can be stopped as soon as possible by accusing those influenced by the radical radicality of a secular religious approach. The methods used must be assisted in order to achieve balanced understanding (wasathiyah) under the different environmental conditions of the culture through recognizing the meaning of religion. The research tool used is primarily library work and the journal writings by Abu Rokhmad, a terrorist and radicalise specialist. The results of this study are that an approach that supports inclusive ism will avoid the awareness of radicalization through a heart-to-heart approach. This study also shows that radical actors will never cease to argue dramatically until they are able to grasp different views from Islamic law, culture, and families.Keywords: radicalism, deradicalization, multiculturalism, culture, religion, moderate.Penelitian ini berawal dari paham radikalisme yang telah mewabah di masyarakat, bukan hanya di dunia nyata, bahkan sudah menyusup di berbagai media sosial online. Penelitian ini menemukan bahwa cara menangkal radikalisme online dapat dilakukan pencegahan sedini mungkin melalui pendekatan konseling religius multikultural terhadap mereka yang terkena paham radikal radikal. Diantara teknik yang digunakan adalah melalui pemahaman tentang konsep agama juga perlu digalakkan agar memunculkan pemahaman yang moderat (wasathiyah) diberbagai keadaan lingkungan masyarakat. Metode yang digunakan untuk penelitian ini adalah library research dengan sumber utama adalah karya dan jurnal karya Abu Rokhmad seorang pakar dalam masalah terorisme dan radikalisme. Temuan penelitian ini adalah paham radikalisasi itu dapat dihentikan dengan pendekatan hati ke hati dengan mengedepankan budaya yang multikultural. Kajian ini juga membuktikan bahwa pelaku paham radikal tidak akan pernah berhenti memberikan argumen radikal kecuali mampu memahami perbedaan pendapat yang bersumber dari syariat Islam, lingkungan sosial, dan keluarga.Kata kunci: radikalisme, deradikalisasi, multikultural, budaya, agama, moderat.

Customer Revenue Sharing Program in Online Social Media

2012 ◽  
Author(s):  
Fouad H. Mirzaei ◽  
Fredrik Odegaard ◽  
Xinghao Yan
Keyword(s):  
Social Media ◽  
Revenue Sharing ◽  
Online Social Media
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