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dc.contributor.authorDemaine, Erik D.
dc.contributor.authorHajiaghayi, MohammadTaghi
dc.contributor.authorMahini, Hamid
dc.contributor.authorMalec, David L.
dc.contributor.authorRaghavan, S.
dc.contributor.authorSawant, Anshul
dc.contributor.authorZadimoghaddam, Morteza
dc.date.accessioned2015-11-23T16:25:54Z
dc.date.available2015-11-23T16:25:54Z
dc.date.issued2014-04
dc.identifier.isbn9781450327442
dc.identifier.urihttp://hdl.handle.net/1721.1/99998
dc.description.abstractWe study the power of fractional allocations of resources to maximize our influence in a network. This work extends in a natural way the well-studied model by Kleinberg, Kempe, and Tardos (2003), where a designer selects a (small) seed set of nodes in a social network to influence directly, this influence cascades when other nodes reach certain thresholds of neighbor influence, and the goal is to maximize the final number of influenced nodes. Despite extensive study from both practical and theoretical viewpoints, this model limits the designer to a binary choice for each node, with no chance to apply intermediate levels of influence. This model captures some settings precisely, such as exposure to an idea or pathogen, but it fails to capture very relevant concerns in others, for example, a manufacturer promoting a new product by distributing five "20% off" coupons instead of giving away a single free product. While fractional versions of problems tend to be easier to solve than integral versions, for influence maximization, we show that the two versions have essentially the same computational complexity. On the other hand, the two versions can have vastly different solutions: the added flexibility of fractional allocation can lead to significantly improved influence. Our main theoretical contribution is to show how to adapt the major positive results from the integral case to the fractional case. Specifically, Mossel and Roch (2006) used the submodularity of influence to obtain their integral results; we introduce a new notion of continuous submodularity, and use this to obtain matching fractional results. We conclude that we can achieve the same greedy (1-1/e-ε)-approximation for the fractional case as the integral case, and that other heuristics are likely to carry over as well. In practice, we find that the fractional model performs substantially better than the integral model, according to simulations on real-world social network data.en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (CAREER Award 1053605)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CCF-1161626)en_US
dc.description.sponsorshipUnited States. Office of Naval Research. Young Investigator Program (Award N000141110662)en_US
dc.description.sponsorshipUnited States. Defense Advanced Research Projects Agency (United States. Air Force Office of Scientific Research Grant FA9550-12-1-0423)en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/2566486.2568039en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourcearXiven_US
dc.titleHow to influence people with partial incentivesen_US
dc.typeArticleen_US
dc.identifier.citationErik D. Demaine, MohammadTaghi Hajiaghayi, Hamid Mahini, David L. Malec, S. Raghavan, Anshul Sawant, and Morteza Zadimoghadam. 2014. How to influence people with partial incentives. In Proceedings of the 23rd international conference on World wide web (WWW '14). ACM, New York, NY, USA, 937-948.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorDemaine, Erik D.en_US
dc.contributor.mitauthorZadimoghaddam, Mortezaen_US
dc.relation.journalProceedings of the 23rd international conference on World wide web (WWW '14)en_US
dc.eprint.versionOriginal manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dspace.orderedauthorsDemaine, Erik D.; Hajiaghayi, MohammadTaghi; Mahini, Hamid; Malec, David L.; Raghavan, S.; Sawant, Anshul; Zadimoghadam, Mortezaen_US
dc.identifier.orcidhttps://orcid.org/0000-0003-3803-5703
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


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