A Large-Scale Analysis of Facebook’s User-Base and User Engagement Growth

Kassa, Yonas Mitike; Cuevas, Antonio

doi:10.1109/access.2018.2885458

Cited by 8 publications

(6 citation statements)

References 26 publications

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“…Unlike many of the previous work on social networking cites that investigate a large selection of OSNs 38 or a dominant OSN entering many countries 39 , our results are limited to a specific product in a single country. In this regard, future research shall investigate how various types of online products diffuse across space and social networks and in different countries.…”

Section: Discussionmentioning

confidence: 95%

The role of geography in the complex diffusion of innovations

Lengyel

Bokányi

Clemente

et al. 2020

Sci Rep

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The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

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Section: Discussionmentioning

confidence: 95%

The role of geography in the complex diffusion of innovations

Lengyel

Bokányi

Clemente

et al. 2020

Sci Rep

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“…We encrypted a message and informed the participant of the specific domain. Attackers are allowed to try several numbers of computations using the worst scenario of a small 4-bit key that can be exhausted in 2 4 operations until a large 256-bit key space. Fig.…”

Section: E Generic Evaluation Of the Model For An Attacker With Sidementioning

confidence: 99%

“…In recent years, information and communication security has evolved into a red-hot issue with notable data breach encompassing giant establishments, such as Facebook, Yahoo, Equifax and others, resulting in greater privacy awareness amongst both consumers and organizations [1]- [3]. The espousal of the internet has impacted every sphere of human lives particularly in the area of communication [4], [5].…”

Section: Introductionmentioning

confidence: 99%

A Deception Model Robust to Eavesdropping Over Communication for Social Network Systems

et al. 2019

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Communication security deals with attributes such as confidentiality, integrity, and availability. The current strategies used to achieve covertness of communication employs encryption. Encryption techniques minimize eavesdropping on the conversation between the conversing parties by transforming the message into an unreadable form. However, it does not prevent or discourage eavesdroppers from stealing and attempting to decrypt the encrypted messages using a brute-force attack or by randomly guessing the key. The probability of the eavesdropper acquiring the key and recovering the message is high as he/she can distinguish a correct key from incorrect keys based on the output of the decryption. This is because a message has some structure-texts, pictures, and videos. Thus, an attempt at decrypting with a wrong key yields random gibberish that does not comply with the expected structure. Furthermore, the consistent increase in computational power implies that stolen encrypted data may gradually debilitate to a brute-force attack. Thus, causing the eavesdropper to learn the content of the message. To this end, the objective of this research is to reinforce the current encryption measures with a decoy-based deception model where the eavesdropper is discouraged from stealing encrypted message by confounding his resources and time. Our proposed model leverages its foundation from decoys, deception, and artificial intelligence. An instant messaging application was developed and integrated with the proposed model as a proof of concept. Further details regarding the design, analysis, and implementation of the proposed model are substantiated. The result shows that the proposed model reinforces state-of-the-art encryption schemes and will serve as an effective component for discouraging eavesdropping and curtailing brute-force attack on encrypted messages.

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“…In studies examining people's motivations for SNS use, socially-oriented motives stand out: Users want to feel connected, be updated about social events, and build and strengthen social relationships (Baumer et al 2013;Dunne, Lawlor, and Rowley 2010;Chen 2011;Quan-Haase and Young 2010;Shao 2009). On the other hand, while Facebook is still growing, especially in Africa and Central Asia (Kassa, Cuevas, and Cuevas 2018), in many countries in the Global North, such as the Netherlands, the growth in user base has slowed down or came to a halt. Importantly, an increasing number of users are leaving Facebook (Frier 2018;Hedencrona 2013;Olson 2013), and apparently due to growing privacy concerns, aggravated by recent data-related scandals (Frier 2018;Scott 2014;Van Hoek 2014).…”

Section: Introductionmentioning

confidence: 99%

Saying no to Facebook: Uncovering motivations to resist or reject social media platforms

Slot

Opree

2021

The Information Society

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Literature on people's motivations for using social network sites is plentiful, yet articles on people's intrinsic motivations for resisting or rejecting them are scarce. This article explores people's motivations for nonuse. A survey was carried out among 210 Facebook nonusers (113 resisters and 97 rejecters) between 18 and 35 years of age. Exploratory factor analysis of the survey data indicated that their motivations for nonuse can be grouped into five categories: platform specific issues, disinterest, time management issues, privacy issues, and social pressure. Overall, resisters were found to be sturdier in their (negative) beliefs than rejecters.

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A Large-Scale Analysis of Facebook’s User-Base and User Engagement Growth

Cited by 8 publications

References 26 publications

The role of geography in the complex diffusion of innovations

The role of geography in the complex diffusion of innovations

A Deception Model Robust to Eavesdropping Over Communication for Social Network Systems

Saying no to Facebook: Uncovering motivations to resist or reject social media platforms

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