title: Learning from Bees: An Approach for Influence Maximization on Viral Campaigns.
abstract: Maximisation of influence propagation is a key ingredient to any viral marketing or socio-political campaigns. However, it is an NP-hard problem, and various approximate algorithms have been suggested to address the issue, though not largely successful. In this paper, we propose a bio-inspired approach to select the initial set of nodes which is significant in rapid convergence towards a sub-optimal solution in minimal runtime. The performance of the algorithm is evaluated using the re-tweet network of the hashtag #KissofLove on Twitter associated with the non-violent protest against the moral policing spread to many parts of India. Comparison with existing centrality based node ranking process the proposed method significant improvement on influence propagation. The proposed algorithm is one of the hardly few bio-inspired algorithms in network theory. We also report the results of the exploratory analysis of the network kiss of love campaign.
authors.affiliation: Department of Futures Studies, University of Kerala, Kariavattom, Kerala, India - 695 581.
authors.forename: C Prem
authors.initials: CP
authors.lastname: Sankar
authors.affiliation: IIITM-K, Thiruvananthapuram, Kerala, India - 695 581.
authors.forename: Asharaf
authors.initials: A
authors.lastname: S
authors.affiliation: Department of Futures Studies, University of Kerala, Kariavattom, Kerala, India - 695 581.
authors.forename: K Satheesh
authors.identifier: http://orcid.org/0000-0003-2458-4031
authors.initials: KS
authors.lastname: Kumar
mesh_terms: D000465:Algorithms; D000819:Animal Communication; D000818:Animals; D001516:Bees / Q000502:physiology*; D033181:Information Dissemination / Q000379:methods*; D011057:Politics; D060756:Social Networking