Location driven influence maximization: Online spread via offline deployment

Q Shi, C Wang, J Chen, Y Feng, C Chen - Knowledge-Based Systems, 2019 - Elsevier
Existing works on influence maximization (IM) aim at finding influential online users as seed
nodes. Originated from these seed nodes, large online influence spread can be triggered …

Influence Maximization in Social Networks: A Survey

H Li, S Yang, M Xu, SS Bhowmick, J Cui - arXiv preprint arXiv:2309.04668, 2023 - arxiv.org
Online social networks have become an important platform for people to communicate,
share knowledge and disseminate information. Given the widespread usage of social …

Influence maximization based on SATS scheme in social networks

X Zhang, M Gao, L Xu, Z Zhou - Computing, 2023 - Springer
Key user identification for messages propagation constitutes one of the most important
topics in social networks. The success of the information spreading depends on the …

Seed-driven geo-social data extraction

S Isaj, TB Pedersen - Proceedings of the 16th international symposium …, 2019 - dl.acm.org
Geo-social data has been an attractive source for a variety of problems such as mining
mobility patterns, link prediction, location recommendation, and influence maximization …

[PDF][PDF] Social media influence analysis Techniques Systematic Literature Review.

Y Sahnoun, M Chaabane, IB Rodriguez - TACC, 2021 - ceur-ws.org
Nowadays, the use of Social Media networks is growing endlessly and rapidly, those
networks have become a substantial pool for unstructured data. Social media influence …

Seed-Driven Geo-Social Data Extraction--Full Version

S Isaj, TB Pedersen - arXiv preprint arXiv:1901.06712, 2019 - arxiv.org
Geo-social data has been an attractive source for a variety of problems such as mining
mobility patterns, link prediction, location recommendation, and influence maximization …

Finding Geo-Social Cohorts in Location-Based Social Networks

MA Saleem, T Calders, TB Pedersen… - Web and Big Data: 5th …, 2021 - Springer
Given a record of geo-tagged activities, how can we suggest groups, or cohorts of likely
companions? A brute-force approach is to perform a spatio-temporal join over past activity …