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Authors: Aigerim Mussina 1 ; Paulo Trigo 2 and Sanzhar Aubakirov 1

Affiliations: 1 Department of Computer Science, Al-Farabi Kazakh National University, 71 al-Farabi Ave., Almaty, Kazakhstan ; 2 GuIAA, ISEL - Instituto Superior de Engenharia de Lisboa, Lisbon, Portugal

Keyword(s): Event Detection, Association Rules, What-If Analysis.

Abstract: Event detection on online social networks is one of the comprehensive approaches for analyzing people’s discussions. However, it is not enough to detect an event as people often look for ways to influence the course of an event. Often, in the course of a discussion, the introduction of a new topic can shift the focus to another subject and thus move from one event to another. The causal relationship between topics and events can be explored by extracting association rules among the topics covered in each event. The scenario generation based on those causal relationships can support what-if (counterfactual) analysis and explain transitions between events. In this paper our goal is to generate what-if scenarios among topics of detected events. The association rule approach was chosen as a method for its human-readable output that can be transposed into a counterfactual scenario. We propose methods for time-window constrained topic-based what-if scenario generation founded on market-bas ket analysis. (More)

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Paper citation in several formats:
Mussina, A.; Trigo, P. and Aubakirov, S. (2023). Scenario Generation With Transitive Rules for Counterfactual Event Analysis. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-623-1; ISSN 2184-433X, SciTePress, pages 1047-1051. DOI: 10.5220/0011895000003393

@conference{icaart23,
author={Aigerim Mussina. and Paulo Trigo. and Sanzhar Aubakirov.},
title={Scenario Generation With Transitive Rules for Counterfactual Event Analysis},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2023},
pages={1047-1051},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011895000003393},
isbn={978-989-758-623-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Scenario Generation With Transitive Rules for Counterfactual Event Analysis
SN - 978-989-758-623-1
IS - 2184-433X
AU - Mussina, A.
AU - Trigo, P.
AU - Aubakirov, S.
PY - 2023
SP - 1047
EP - 1051
DO - 10.5220/0011895000003393
PB - SciTePress

- Science and Technology Publications, Lda.
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