Clustering in Aggregated User Profiles Across Multiple Social Networks

Virmani, Charu; Pillai, Anuradha; Juneja, Dimple

doi:10.11591/ijece.v7i6.pp3692-3699

Cited by 16 publications

(17 citation statements)

References 29 publications

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“…[61]), and is anticipated to be the theoretical material for the creation of application of emotional internet infidelity detection through profiling based on social network analysis (e.g. [62]) as well as for the developing affective computing (e.g. [63]) which could counsel on emotional Internet infidelity issue.…”

Section: Resultsmentioning

confidence: 99%

Tolerance for Emotional Internet Infidelity and Its Correlate with Relationship Flourishing

Octaviana

Abraham

2018

IJECE

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Until today, there is still controversy whether emotional Internet infidelity or cheating is something that can be tolerated. Existing views are diverse, influenced by geographical factors, cultural and ideological backgrounds, as well as biological theory. This present study initially suggested that the higher the relationship flourishing, the higher the tolerance for the infidelity. In an era where monogamous relationships are dynamized by the multiplication of relationship modes through online social networks, this study becomes increasingly urgent, i.e. to recommend a variable capable of providing a buffering effect to the deleterious effect of the infidelity. The study used correlational design. As much as 210 participants (55 males, 155 females, Mage=37.89 years old, SDage=10.870 years) were recruited in the Greater Area of Jakarta, Indonesia to fill out the Relationship Flourishing Scale and Internet Infidelity Tolerance-Emotional Infidelity Subscale. This study found that relationship flourishing and emotional Internet infidelity are negatively correlated (Spearman’s Rho=-0.172, p<0.05) and there is a moderating role of sex (coeff.=0.3481, p<0.05). That is, those with higher relationship flourishing would have a higher intolerance, especially among men. Such intolerance could lead to marital dissatisfaction and, at worst, divorce. The results of this study have implications for (1) an evaluation of psychometric dimensions of the Relationship Flourishing Scale, (2) the need of proposing moderating variables to be integrated into the correlational model between relationship flourishing and the infidelity, as well as (3) online applications development in detecting and managing the Internet infidelity.

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Section: Resultsmentioning

confidence: 99%

Tolerance for Emotional Internet Infidelity and Its Correlate with Relationship Flourishing

Octaviana

Abraham

2018

IJECE

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“…Obviously, A can be elevated to any matrices product without upsetting the original structure of the attack geography as listed in Equation (2). The performance of the partition algorithm discussed in [17] can be used to obtain a shorter processing time as well as to avoid complexity in calculation cost of which is not beyond O(n 2 ). Moreover, in the case of big data processing, a solution of missing and impaired datasets presented in [18] can be utilized.…”

Section: Attack Analytical Modelmentioning

confidence: 99%

Evaluation of computer network security using attack undirected geography

Jittawiriyanukoon¹

2019

IJEECS

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<span>To secure a wealth of data traversing the computer network at your fingertips is compulsory. But when attack arises at various parts of the network it is difficult to protect, especially when each incident is investigated separately. Geography is a necessary construct in computer networks. The analytics of geography algorithms and metrics to curate insight from a security problem are a critical method of analysis for computer systems. A geography based representation is employed to highlight aspects (on a local and global level) of a security problem which are Eigenvalue, eccentricity, clustering coefficient and cliques. Network security model based on attack undirected geography (AUG) is familiarized. First, analysis based upon association rules is presented then the attack threshold value is set from AUG. The probability of an individual attack edge and associated network nodes are computed in order to quantify the security threat. The simulation is exploited to validate that results are effective.</span>

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“…It is a widely known technique with applications in various fields such as social media [1], Web search results optimization [2], wireless sensor networks [3] and also in biochemical neural networks [4] among others. In most cases, the number of clusters to form is already known and is given as an entry to the clustering algorithm.…”

Section: Introductionmentioning

confidence: 99%

Bat-Cluster: A Bat Algorithm-based Automated Graph Clustering Approach

Boulouard¹,

Haddadi²,

Bouhafer³

et al. 2018

IJECE

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Defining the correct number of clusters is one of the most fundamental tasks in graph clustering. When it comes to large graphs, this task becomes more challenging because of the lack of prior information. This paper presents an approach to solve this problem based on the Bat Algorithm, one of the most promising swarm intelligence based algorithms. We chose to call our solution, "Bat-Cluster (BC)." This approach allows an automation of graph clustering based on a balance between global and local search processes. The simulation of four benchmark graphs of different sizes shows that our proposed algorithm is efficient and can provide higher precision and exceed some best-known values.

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Clustering in Aggregated User Profiles Across Multiple Social Networks

Cited by 16 publications

References 29 publications

Tolerance for Emotional Internet Infidelity and Its Correlate with Relationship Flourishing

Tolerance for Emotional Internet Infidelity and Its Correlate with Relationship Flourishing

Evaluation of computer network security using attack undirected geography

Bat-Cluster: A Bat Algorithm-based Automated Graph Clustering Approach

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