Quantitative Methods in Transportation

Teodorović, Dušan; Nikolic, Milos Lj.

doi:10.1201/9780429286919

Cited by 4 publications

(1 citation statement)

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“…Also, for finding the communities within the network Force Atlas2 algorithmhasbeenused.SperlìG.anddelPuenteG.haveexploredsocialnetworkfromdifferent perspectives.Theyhavepresentedastudytoanalyzethesocialnetworkbasicstructure,properties, centrality,influenceandalsonetworkmodelling.ABio-inspiredapproachtooptimizethenetwork hasbeendiscussed,forthisartificialbeecolonyalgorithmisused (Wedde,Farooq&Zhang,2004). In Teodorovic & Dell'Orco (2005) authors have presented a bio-inspired approach to find out theinitialsetofnodeswhicharecriticalinfastconvergencetowardoptimalsolutioninminimal possible time. Key personalities within the social media network Twitter have been explored, whichcanmaximizetheinfluenceonviralcampaigns.Forthisartificialbeecolonyalgorithmis usedandperformanceisevaluatedusingthere-tweetnetworkofpopulartwitterhashtag.Wang Y.in2017proposedanapproachStreamInfluenceMaximization(SIM)toidentifykinfluential userswhocanmaximizetheinfluenceoverasocialaction.AndalsoInfluentialcheckpointsto productivelysupporttheSIMqueriesoverafastspeedsocialactions (Karaboga&Basturk,2007).…”

Section: Related Workmentioning

confidence: 99%

Artificial Bee Colony-Based Influence Maximization Approach for Social Coding Portal GitHub

Arora

Bana

Shah

et al. 2019

International Journal of Swarm Intelligence Research

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Influence maximization is the main source of virality of any social media post/marketing activity. In recent trends, influence maximization has moved towards analytic approach instead of just being a suggestive metaphor for various social media paradigm. In this article, ego-centric approach and a bio-inspired algorithm is applied on social coding community, Github, for influence maximization. First, developers' and projects' egocentric network-based studies are conducted to find out influential developer and project based on varying social media measures. Second, artificial bee colony (ABC) bio-inspired algorithm is used to select social bees (i.e., developers set and projects set in rapid convergence towards an optimal solution to achieve influence maximization). Algorithm result ensures the best solution in terms of social community connectivity path optimization in less run time while finding most influential social bees.

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Section: Related Workmentioning

confidence: 99%