On the impact of users availability in OSNs

Boutet, Antoine; Kermarrec, Anne-Marie; Merrer, Erwan Le; Kempen, Alexandre van

doi:10.1145/2181176.2181180

Cited by 10 publications

(14 citation statements)

References 15 publications

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“…Note that users tend to be online when their friends are online [30]. From this point of view, a user may consider the UOT as a parameter to recognise those friends who are not his/her close friends.…”

Section: Edge Weightmentioning

confidence: 99%

Data availability improvement in peer‐to‐peer online social networks

Koohpar

Fatemi

Raji

2020

IET Information Security

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Section: Edge Weightmentioning

confidence: 99%

Data availability improvement in peer‐to‐peer online social networks

Koohpar

Fatemi

Raji

2020

IET Information Security

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“…The rationale behind our approach is that the availability status of a user u at a future time t i+1 of the day d could depend on the availability status of u at the same time t i+1 of the previous days d − 1, d − 2, … d − x. For example, as shown in other works, 29,30 users of the OSNs seem to connect to the service with a periodic trend. In particular, groups of students of the same school connect to the OSN outside the hours of lessons and expose a periodical time pattern in their connections.…”

Section: Our Approach: a Linear Predictor Based On Time Intervalsmentioning

confidence: 99%

“…Indeed, the coefficient vector w b achieved the best average accuracy (about 0.85[±0 29]. for MaxTimeSlot and 0.769[±0.36] for MaxSumSlot) if compared with the coefficient vector w a (about 0.82[±0 30].…”

mentioning

confidence: 99%

Predicting the availability of users' devices in decentralized online social networks

Salve

Guidi

Mori

2017

Concurrency and Computation

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The understanding of the user temporal behavior is a crucial aspect for all those systems that rely on user resources for daily operations, such as decentralized online social networks (DOSNs).Indeed, DOSNs exploit the devices of their users to take on and share the tasks needed to provide services such as storing the published data. In the last years, the increasing popularity of DOSN services has changed the way of how people interact with each other by enabling users to connect to these services at any time by using their personal devices (such as notebooks or smartphones).As a result, the availability of data in these systems is strongly affected (or reflected) by the temporal behavior of their users in terms of connections to DOSNs. In this paper, we propose the use of linear predictors to address the problem of the availability of user devices and, hence, data in DOSNs. To validate the proposed approaches, we evaluated their performance conducting a set of simulations exploiting a dataset of temporal information concerning the connections to Facebook collected from a set of users. KEYWORDSavailability prediction, decentralized online social networks, user behavior INTRODUCTIONIn the last years, online social networks (OSNs) have proliferated by attracting millions of users that share a large number of contents with each other. According to the International Telecommunication Union (ITU)*, OSNs have reached a global penetration rate of 31%. The evolution of mobile technology (such as smartphones and tablets) is the major driver that makes social networking the most popular online activity, which captures 30% of the time spent by users each day on the Internet † , i.e., about 1 hour and 50 minutes. The most popular OSNs are based on a centralized architecture where the service provider takes control over users' information. However, the centralized structure has several relevant drawbacks. For instance, during the last years, users' privacy in OSNs becomes an ever-increasing concern because private information of the users is exploited by the centralized OSN providers for several purposes. 1,2 Privacy and system scalability are two of the main issues that have led to the decentralization of the social networks.A decentralized online social network (DOSN) 3 is an OSN implemented in a decentralized way (such as peer-to-peer architecture). For instance, Diaspora ‡ and Friendica § are two of the currently available DOSNs that attract more than 669 000 users, and they are based on a network of independent, federated servers that are managed by the users. RetroShare ¶ is another available DOSN that allows users to create friend-to-friend connection for sharing data. In DOSNs, there is no centralized authority since users' devices are exploited to store and manage users' data. For this reason, the decentralization of OSNs requires efficient solutions for dealing with data availability arising when users' devices disconnect from the system. Indeed, the problem of data availability occurs because data of a user should...

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“…Instead of replicas in [15] authors propose to store data blocks on nodes by considering their availability. Papers [16] and [17] present new techniques to predict users' availability based on their historical behaviour and authors in [18] demonstrate that the online presence of OSN users tend to be correlated to those of their friends.…”

Section: Data Availability In Dosnsmentioning

confidence: 99%

DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks

Guidi

Amft

Salve

et al. 2015

Peer-to-Peer Netw. Appl.

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Online Social Networks (OSNs) are becoming more and more popular on the Web. Distributed Online Social Networks (DOSNs) are OSNs which do not exploit a central server for storing users data and enable users to have more control on their profile content, ensuring a higher level of privacy. In a DOSN there are some technical challenges to face. ness, information diffusion, and data availability. In this paper we show how our system manages the problem of data availability by proposing a new P2P dynamic trusted storage approach. By following the Dunbar concept, our system stores the data of a user only on a restricted number of friends which have regular contacts with him/her. Differently from other approaches, nodes chosen to keep data replicas are not statically defined but dynamically change according to users churn. In according to our previous work, we use only two online profile replicas at time. By using real Facebook data traces we prove that our approach offers high availability.

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On the impact of users availability in OSNs

Cited by 10 publications

References 15 publications

Data availability improvement in peer‐to‐peer online social networks

Data availability improvement in peer‐to‐peer online social networks

Predicting the availability of users' devices in decentralized online social networks

DiDuSoNet: A P2P architecture for distributed Dunbar-based social networks

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