DISTL: Distributed In-Memory Spatio-Temporal Event-based Storyline Categorization Platform in Social Media

Manu Shukla, Ray Dos Santos, Andrew Fong, Chang-Tien Lu

Abstract

Event analysis in social media is challenging due to endless amount of information generated daily. While current research has put a strong focus on detecting events, there is no clear guidance on how those storylines should be processed such that they would make sense to a human analyst. In this paper, we present DISTL, an event processing platform which takes as input a set of storylines (a sequence of entities and their relationships) and processes them as follows: (1) uses different algorithms (LDA, SVM, information gain, rule sets) to identify events with different themes and allocates storylines to them; and (2) combines the events with location and time to narrow down to the ones that are meaningful in a specific scenario. The output comprises sets of events in different categories. DISTL uses in-memory distributed processing that scales to high data volumes and categorizes generated storylines in near real-time. It uses Big Data tools, such as Hadoop and Spark, which have shown to be highly efficient in handling millions of tweets concurrently.

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Paper Citation


in Harvard Style

Shukla M., Dos Santos R., Fong A. and Lu C. (2016). DISTL: Distributed In-Memory Spatio-Temporal Event-based Storyline Categorization Platform in Social Media . In Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM, ISBN 978-989-758-188-5, pages 39-50. DOI: 10.5220/0005831200390050


in Bibtex Style

@conference{gistam16,
author={Manu Shukla and Ray Dos Santos and Andrew Fong and Chang-Tien Lu},
title={DISTL: Distributed In-Memory Spatio-Temporal Event-based Storyline Categorization Platform in Social Media},
booktitle={Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,},
year={2016},
pages={39-50},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005831200390050},
isbn={978-989-758-188-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Geographical Information Systems Theory, Applications and Management - Volume 1: GISTAM,
TI - DISTL: Distributed In-Memory Spatio-Temporal Event-based Storyline Categorization Platform in Social Media
SN - 978-989-758-188-5
AU - Shukla M.
AU - Dos Santos R.
AU - Fong A.
AU - Lu C.
PY - 2016
SP - 39
EP - 50
DO - 10.5220/0005831200390050