Applying prefetching in Online Social Network to gain social intelligence

Thangaraj, Muthuraman; Meenatchi, V. T.

doi:10.1109/iccci.2015.7218066

Cited by 1 publication

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For community detection, clustering algorithms and statistical methods are highlighted. [32]; [33]; [34] (DLACD) Distributed learning automata based [35] (CL) Clustering [33]; [36]; [37] (WTS) Weak Tie Score [38] (BCL) BIGClam Overlaping Community detection [39] (CNN) Clauset-Newman-Moore [40] (WIC) Within and Inter Community [41] (CM) Centrality Measures [42]; [43]; [44]; [45]; [46] (RW) Random Walk [47] (DI) Difussion (MLR) Multivariate Linear Regression [48] (CM) Centrality Measures [49]; [50]; [51]; [52]; [53]; [54]; [55] (SM) Statistical Methods [56]; [57]; [58]; [59]; [60]; [61]; [31]; [62] (BoW) Bag of Words [34] (SVM) Support Vector Machine [43] In summary, the results of this search allow us to conclude that research on the phenomena occurring in the context of digital social networks has been marked by the implementation of methods and techniques that allow taking advantage of the potential of the content available on the web, the increase in online interactions and technological evolution. In exponential growth, the collective behavior underlying social networks is undoubtedly a source of knowledge that requires further research.…”

Section: Background a Social Network Analysismentioning

confidence: 99%

Hybrid Onion Layered System for the Analysis of Collective Subjectivity in Social Networks

Moreno-Sandoval

Pomares-Quimbaya

2022

IEEE Access

View full text Add to dashboard Cite

This research aims to analyze the Digital Social Networks (DSN) behavior, constructed from the network's relationships, interactions, and expressions of users' private states through collective subjectivity. For this purpose, an onion-ring system called COSSOL has been built in a case study for Twitter, following a hybrid approach to integrate Machine Learning classifiers and structural metrics from Computational Linguistics and Computational Sociology disciplines, respectively. The paper designs two experimentation scenarios divided into cases of collective subjectivity analysis for Colombia under different levels of communities' granularity. The first case validates the system by performing a cointegration test on the metrics of each construct for the onion rings' communities. The results show that some communities better propagate their subjective expressions against the disclosed topic when they have a higher network density and a common polarity. Moreover, the most stable communities in polarity towards a topic are those whose members are highly connected. Conversely, communities with a higher centrality index in a subset of members do not exhibit stability in collective subjectivity towards a topic disclosed in that community. The second case validates the model with a series of Social Network Analysis (SNA) metrics with a polarity layer to describe the second onion ring subcommunities and their temporal variation through community recalculation. The results show no polar distributions similar to the bimodal ones representing consensus in the values of the common Thinking Acting and Feeling (TAF) forms. In addition, general negative sentiment is identified for the ten most representative nodes of the subcommunities analyzed.

show abstract