Identifying sub-events and summarizing disaster-related information from microblogs

Koustav Rudra, Pawan Goyal, Niloy Ganguly, Prasenjit Mitra, Muhammad Imran

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

Abstract

In recent times, humanitarian organizations increasingly rely on social media to search for information useful for disaster response. These organizations have varying information needs ranging from general situational awareness (i.e., to understand a bigger picture) to focused information needs e.g., about infrastructure damage, urgent needs of affected people. This research proposes a novel approach to help crisis responders fulfill their information needs at different levels of granularities. Specifically, the proposed approach presents simple algorithms to identify sub-events and generate summaries of big volume of messages around those events using an Integer Linear Programming (ILP) technique. Extensive evaluation on a large set of real world Twitter dataset shows (a). our algorithm can identify important sub-events with high recall (b). The summarization scheme shows (6 - -30%) higher accuracy of our system compared to many other state-of-the-art techniques. The simplicity of the algorithms ensures that the entire task is done in real time which is needed for practical deployment of the system.

Original languageEnglish (US)
Title of host publication41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
PublisherAssociation for Computing Machinery, Inc
Pages265-274
Number of pages10
ISBN (Electronic)9781450356572
DOIs
StatePublished - Jun 27 2018
Event41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 - Ann Arbor, United States
Duration: Jul 8 2018Jul 12 2018

Other

Other41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018
CountryUnited States
CityAnn Arbor
Period7/8/187/12/18

Fingerprint

Disasters
Linear programming

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design
  • Information Systems

Cite this

Rudra, K., Goyal, P., Ganguly, N., Mitra, P., & Imran, M. (2018). Identifying sub-events and summarizing disaster-related information from microblogs. In 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018 (pp. 265-274). Association for Computing Machinery, Inc. https://doi.org/10.1145/3209978.3210030
Rudra, Koustav ; Goyal, Pawan ; Ganguly, Niloy ; Mitra, Prasenjit ; Imran, Muhammad. / Identifying sub-events and summarizing disaster-related information from microblogs. 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery, Inc, 2018. pp. 265-274
@inproceedings{abb0dec4e1824301b8530486c8060dce,
title = "Identifying sub-events and summarizing disaster-related information from microblogs",
abstract = "In recent times, humanitarian organizations increasingly rely on social media to search for information useful for disaster response. These organizations have varying information needs ranging from general situational awareness (i.e., to understand a bigger picture) to focused information needs e.g., about infrastructure damage, urgent needs of affected people. This research proposes a novel approach to help crisis responders fulfill their information needs at different levels of granularities. Specifically, the proposed approach presents simple algorithms to identify sub-events and generate summaries of big volume of messages around those events using an Integer Linear Programming (ILP) technique. Extensive evaluation on a large set of real world Twitter dataset shows (a). our algorithm can identify important sub-events with high recall (b). The summarization scheme shows (6 - -30{\%}) higher accuracy of our system compared to many other state-of-the-art techniques. The simplicity of the algorithms ensures that the entire task is done in real time which is needed for practical deployment of the system.",
author = "Koustav Rudra and Pawan Goyal and Niloy Ganguly and Prasenjit Mitra and Muhammad Imran",
year = "2018",
month = "6",
day = "27",
doi = "10.1145/3209978.3210030",
language = "English (US)",
pages = "265--274",
booktitle = "41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018",
publisher = "Association for Computing Machinery, Inc",

}

Rudra, K, Goyal, P, Ganguly, N, Mitra, P & Imran, M 2018, Identifying sub-events and summarizing disaster-related information from microblogs. in 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery, Inc, pp. 265-274, 41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018, Ann Arbor, United States, 7/8/18. https://doi.org/10.1145/3209978.3210030

Identifying sub-events and summarizing disaster-related information from microblogs. / Rudra, Koustav; Goyal, Pawan; Ganguly, Niloy; Mitra, Prasenjit; Imran, Muhammad.

41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery, Inc, 2018. p. 265-274.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

TY - GEN

T1 - Identifying sub-events and summarizing disaster-related information from microblogs

AU - Rudra, Koustav

AU - Goyal, Pawan

AU - Ganguly, Niloy

AU - Mitra, Prasenjit

AU - Imran, Muhammad

PY - 2018/6/27

Y1 - 2018/6/27

N2 - In recent times, humanitarian organizations increasingly rely on social media to search for information useful for disaster response. These organizations have varying information needs ranging from general situational awareness (i.e., to understand a bigger picture) to focused information needs e.g., about infrastructure damage, urgent needs of affected people. This research proposes a novel approach to help crisis responders fulfill their information needs at different levels of granularities. Specifically, the proposed approach presents simple algorithms to identify sub-events and generate summaries of big volume of messages around those events using an Integer Linear Programming (ILP) technique. Extensive evaluation on a large set of real world Twitter dataset shows (a). our algorithm can identify important sub-events with high recall (b). The summarization scheme shows (6 - -30%) higher accuracy of our system compared to many other state-of-the-art techniques. The simplicity of the algorithms ensures that the entire task is done in real time which is needed for practical deployment of the system.

AB - In recent times, humanitarian organizations increasingly rely on social media to search for information useful for disaster response. These organizations have varying information needs ranging from general situational awareness (i.e., to understand a bigger picture) to focused information needs e.g., about infrastructure damage, urgent needs of affected people. This research proposes a novel approach to help crisis responders fulfill their information needs at different levels of granularities. Specifically, the proposed approach presents simple algorithms to identify sub-events and generate summaries of big volume of messages around those events using an Integer Linear Programming (ILP) technique. Extensive evaluation on a large set of real world Twitter dataset shows (a). our algorithm can identify important sub-events with high recall (b). The summarization scheme shows (6 - -30%) higher accuracy of our system compared to many other state-of-the-art techniques. The simplicity of the algorithms ensures that the entire task is done in real time which is needed for practical deployment of the system.

UR - http://www.scopus.com/inward/record.url?scp=85051464585&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85051464585&partnerID=8YFLogxK

U2 - 10.1145/3209978.3210030

DO - 10.1145/3209978.3210030

M3 - Conference contribution

AN - SCOPUS:85051464585

SP - 265

EP - 274

BT - 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018

PB - Association for Computing Machinery, Inc

ER -

Rudra K, Goyal P, Ganguly N, Mitra P, Imran M. Identifying sub-events and summarizing disaster-related information from microblogs. In 41st International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2018. Association for Computing Machinery, Inc. 2018. p. 265-274 https://doi.org/10.1145/3209978.3210030