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Abstract
Identifying and mitigating the spread of fake information is a challenging issue that has become dominant with the rise of social media. We consider a generalization of the Domination problem that can be used to detect a set of individuals who, once immunized, can prevent the spreading of fake narratives. The considered problem, namedDistance Vector Domination generalizes both distance and multiple domination, at individual (i.e., vertex) level. We study the parameterized complexity of the problem according to several standard and structural parameters. We prove the W[1]-hardness of the problem with respect to neighborhood diversity, even when all the distances are 1. We also give fixed-parameter algorithms for some variants of the problem and parameter combinations.
Work partially supported by project SERICS (PE00000014) under the MUR National Recovery and Resilience Plan funded by the European Union - NextGenerationEU.
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Notes
- 1.
For a positive integera, we use [a] to denote the set of integers\([a] = \{1, 2, \ldots , a\}\).
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Authors and Affiliations
Department of Psychology, University of Campania “L.Vanvitelli”, Caserta, Italy
Gennaro Cordasco
Department of Computer Science, University of Salerno, Fisciano, Italy
Luisa Gargano & Adele A. Rescigno
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Correspondence toGennaro Cordasco.
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Comenius University in Bratislava, Bratislava, Slovakia
Rastislav Královič
Czech Academy of Sciences, Prague, Czech Republic
Věra Kůrková
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Cordasco, G., Gargano, L., Rescigno, A.A. (2025). Distance Vector Domination. In: Královič, R., Kůrková, V. (eds) SOFSEM 2025: Theory and Practice of Computer Science. SOFSEM 2025. Lecture Notes in Computer Science, vol 15538. Springer, Cham. https://doi.org/10.1007/978-3-031-82670-2_14
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