Analyzing and Boosting the Data Availability in Decentralized Online Social Networks

2015 ◽  
Vol 12 (2) ◽  
pp. 47-72
Author(s):  
Songling Fu ◽  
Ligang He ◽  
Xiangke Liao ◽  
Chenlin Huang ◽  
Kenli Li ◽  
...  
Keyword(s):  
Social Networks ◽  
Quantitative Analysis ◽  
Online Social Networks ◽  
Storage Capacity ◽  
Critical Factor ◽  
Data Availability ◽  
Simulation Experiments ◽  
Extensive Simulation ◽  
Novel Method ◽  
Decentralized Online Social Networks

Maintaining Data Availability (DA) is a big challenge in Decentralized Online Social Networks (DOSN). Nowadays, the limitation of the storage capacity in DOSN becomes a critical factor that jeopardizes the DA. Therefore, it is desired to determine the relation between the storage capacity of DOSN and the level of DA, and develop an approach to mitigating the limitation of storage capacity. This paper addresses these issues. In this paper, a probabilistic DA model over storage capacity is established. A novel method is then proposed to predict the DA on the fly. Further, a Cloud-assisted DOSN (CDOSN) framework is proposed to enhance the storage capacity and the DA in DOSN. This paper conducts the detailed quantitative analysis about the storage capacity and the DA in CDOSN. Extensive simulation experiments have been conducted to evaluate the effectiveness of the DA model, the on-the-fly prediction and the CDOSN framework.

scholarly journals Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Songling Fu ◽  
Ligang He ◽  
Xiangke Liao ◽  
Kenli Li ◽  
Chenlin Huang
Keyword(s):  
Social Networks ◽  
Mobile Devices ◽  
Online Social Networks ◽  
Storage Capacity ◽  
Data Availability ◽  
Novel Method ◽  
Smart Mobile ◽  
The Impact ◽  
Availability Model ◽  
Decentralized Online Social Networks

Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs). The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs) due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

scholarly journals Augmented Context-Based Conceptual User Modeling for Personalized Recommendation System in Online Social Networks

2020 ◽  
Vol 14 (3) ◽  
pp. 1-19
Author(s):  
Ammar Alnahhas ◽  
Bassel Alkhatib
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Recommendation System ◽  
Contextual Information ◽  
Detailed Comparison ◽  
Personalized Recommendation ◽  
User Models ◽  
Proposed Model ◽  
Recommendation Algorithms ◽  
Novel Method

As the data on the online social networks is getting larger, it is important to build personalized recommendation systems that recommend suitable content to users, there has been much research in this field that uses conceptual representations of text to match user models with best content. This article presents a novel method to build a user model that depends on conceptual representation of text by using ConceptNet concepts that exceed the named entities to include the common-sense meaning of words and phrases. The model includes the contextual information of concepts as well, the authors also show a novel method to exploit the semantic relations of the knowledge base to extend user models, the experiment shows that the proposed model and associated recommendation algorithms outperform all previous methods as a detailed comparison shows in this article.

scholarly journals Decentralized Online Social Networks

2010 ◽  
pp. 349-378 ◽  
Author(s):  
Anwitaman Datta ◽  
Sonja Buchegger ◽  
Le-Hung Vu ◽  
Thorsten Strufe ◽  
Krzysztof Rzadca
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Decentralized Online Social Networks

Evaluating the Presence of Greek Tourism-Related Public Sector Entities in Online Social Networks

2019 ◽  
Vol 6 (1) ◽  
pp. 15-40
Author(s):  
Konstantinos Vrettos ◽  
Dimitris Gouscos
Keyword(s):  
Social Networks ◽  
Quantitative Analysis ◽  
Public Sector ◽  
Online Social Networks ◽  
Structured Interviews ◽  
Tourism Product ◽  
Tourism Sector ◽  
General Government ◽  
Quantitative Results ◽  
Do So

Social networks have become one of the most popular tools in promoting the tourism product. This applies to National Tourism Agencies, as well as tourism-related general government bodies (GGBs) and local authorities (LAs). This study examines such organizations alongside selected chief administration officials (CAOs) that are related with the tourism sector and attempts to evaluate their presence in three social networks: Facebook, Twitter and YouTube. In order to do so, this article builds upon and expands on existing social networks' metrics, incorporating them into metrics of online followership. The quantitative analysis results in a ranking of best performers, from which the authors select three good performers in order to follow with a qualitative analysis of semi-structured interviews. By merging the quantitative results with the feedback from the interviews the authors propose a basic normative social networks management toolkit for tourism-related public entities, found to be comprised of six thematic axes.

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