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Publications

Publications by LIAAD

2019

Identifying, Ranking and Tracking Community Leaders in Evolving Social Networks

Authors
Cordeiro, M; Sarmento, RP; Brazdil, P; Kimura, M; Gama, J;

Publication
Complex Networks and Their Applications VIII - Volume 1 Proceedings of the Eighth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019, Lisbon, Portugal, December 10-12, 2019.

Abstract
Discovering communities in a network is a fundamental and important problem to complex networks. Find the most influential actors among its peers is a major task. If on one side, studies on community detection ignore the influence of actors and communities, on the other hand, ignoring the hierarchy and community structure of the network neglect the actor or community influence. We bridge this gap by combining a dynamic community detection method with a dynamic centrality measure. The proposed enhanced dynamic hierarchical community detection method computes centrality for nodes and aggregated communities and selects each community representative leader using the ranked centrality of every node belonging to the community. This method is then able to unveil, track, and measure the importance of main actors, network intra and inter-community structural hierarchies based on a centrality measure. The empirical analysis performed, using two temporal networks shown that the method is able to find and tracking community leaders in evolving networks. © 2020, Springer Nature Switzerland AG.

2019

Centrality and community detection: a co-marketing multilayer network

Authors
Fernandes, A; Goncalves, PCT; Campos, P; Delgado, C;

Publication
Journal of Business and Industrial Marketing

Abstract
Purpose: Based on the data obtained from a questionnaire of 595 people, the authors explore the relative importance of consumers, checking whether socioeconomic variables influence their centrality, detecting the communities within the network to which they belong, identifying consumption patterns and checking whether there is any relationship between co-marketing and consumer choices. Design/methodology/approach: A multilayer network is created from data collected through a consumer survey to identify customers’ choices in seven different markets. The authors focus the analysis on a smaller kinship and cohabitation network and apply the LART network community detection algorithm. To verify the association between consumers’ centrality and variables related to their respective socioeconomic profile, the authors develop an econometric model to measure their impact on consumer’s degree centrality. Findings: Based on 595 responses analysing individual consumers, the authors find out which consumers invest and which variables influence consumers’ centrality. Using a smaller sample of 70 consumers for whom they know kinship and cohabitation relationships, the authors detect communities with the same consumption patterns and verify that this may be an adequate way to establish co-marketing strategies. Originality/value: Network analysis has become a widely used technique in the extraction of knowledge on consumers. This paper’s main (and novel) contribution lies in providing a greater understanding on how multilayer networks represent hidden databases with potential knowledge to be considered in business decisions. Centrality and community detection are crucial measures in network science which enable customers with the highest potential value to be identified in a network. Customers are increasingly seen as multidimensional, considering their preferences in various markets. © 2019, Emerald Publishing Limited.

2019

Impact of Genealogical Features in Transthyretin Familial Amyloid Polyneuropathy Age of Onset Prediction

Authors
Pedroto, M; Jorge, A; Mendes Moreira, J; Coelho, T;

Publication
Practical Applications of Computational Biology and Bioinformatics, 12th International Conference, PACBB 2018, Toledo, Spain, 20-22 May, 2018.

Abstract

2019

The 2nd International Workshop on Narrative Extraction from Text: Text2Story 2019

Authors
Jorge, AM; Campos, R; Jatowt, A; Bhatia, S;

Publication
Lecture Notes in Computer Science - Advances in Information Retrieval

Abstract

2019

Guest Editorial: Special Issue on Data Mining for Geosciences

Authors
Jorge, A; Lopes, RL; Larrazabal, G; Nikhalat Jahromi, H;

Publication
Data Mining and Knowledge Discovery

Abstract

2019

Classifying Heart Sounds Using Images of Motifs, MFCC and Temporal Features

Authors
Nogueira, DM; Ferreira, CA; Gomes, EF; Jorge, AM;

Publication
Journal of Medical Systems

Abstract

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