Influence maximization on temporal networks: a review
Influence maximization (IM) is an important topic in network science where a small seed set
is chosen to maximize the spread of influence on a network. Recently, this problem has …
is chosen to maximize the spread of influence on a network. Recently, this problem has …
Computational sustainability: Computing for a better world and a sustainable future
Computational sustainability: computing for a better world and a sustainable future Page 1 56
COMMUNICATIONS OF THE ACM | SEPTEMBER 2019 | VOL. 62 | NO. 9 Computational …
COMMUNICATIONS OF THE ACM | SEPTEMBER 2019 | VOL. 62 | NO. 9 Computational …
Artificial intelligence for social good: A survey
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and
advance artificial intelligence to address societal issues and improve the well-being of the …
advance artificial intelligence to address societal issues and improve the well-being of the …
Social-network-assisted worker recruitment in mobile crowd sensing
J Wang, F Wang, Y Wang, D Zhang… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Worker recruitment is a crucial research problem in Mobile Crowd Sensing (MCS). While
previous studies rely on a specified platform with a pre-assumed large user pool, this paper …
previous studies rely on a specified platform with a pre-assumed large user pool, this paper …
Predicting Human Decision-Making
Designing intelligent agents that interact proficiently with people necessitates the prediction
of human decision-making. We present and discuss three prediction paradigms for …
of human decision-making. We present and discuss three prediction paradigms for …
LIDDE: A differential evolution algorithm based on local-influence-descending search strategy for influence maximization in social networks
L Qiu, X Tian, J Zhang, C Gu, S Sai - Journal of Network and Computer …, 2021 - Elsevier
Influence maximization aims to select k seed nodes from social networks so that the
expected number of nodes activated by the seed nodes can be maximized. With the …
expected number of nodes activated by the seed nodes can be maximized. With the …
[PDF][PDF] Uncharted but not Uninfluenced: Influence Maximization with an uncertain network
This paper focuses on new challenges in influence maximization inspired by non-profits' use
of social networks to effect behavioral change in their target populations. Influence …
of social networks to effect behavioral change in their target populations. Influence …
[PDF][PDF] End-to-End Influence Maximization in the Field.
This work is aims to overcome the challenges in deploying influence maximization to
support community driven interventions. Influence maximization is a crucial technique used …
support community driven interventions. Influence maximization is a crucial technique used …
Efficient and effective influence maximization in social networks: a hybrid-approach
Influence Maximization (IM) is the problem of finding a seed set composed of k nodes that
maximize their influence spread over a social network. Kempe et al. showed the problem to …
maximize their influence spread over a social network. Kempe et al. showed the problem to …
[PDF][PDF] Bridging the gap between theory and practice in influence maximization: Raising awareness about HIV among homeless youth.
This paper reports on results obtained by deploying HEALER and DOSIM (two AI agents for
social influence maximization) in the real-world, which assist service providers in …
social influence maximization) in the real-world, which assist service providers in …