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Summarizing Microblogs During Emergency Events: A Comparison of Extractive Summarization Algorithms

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Emerging Technologies in Data Mining and Information Security

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 813))

Abstract

Microblogging sites, notably Twitter, have become important sources of real-time situational information during emergency events. Since hundreds to thousands of microblogs (tweets) are generally posted on Twitter during an emergency event, manually going through every tweet is not feasible. Hence, summarization of microblogs posted during emergency events has become an important problem in recent years. Several summarization algorithms have been proposed in the literature, both for general document summarization, as well as specifically for summarization of microblogs. However, to our knowledge, there has not been any systematic analysis on which algorithms are more suitable for summarization of microblogs posted during disasters. In this work, we evaluate and compare the performance of 8 extractive summarization algorithms in the application of summarizing microblogs posted during emergency events. Apart from comparing the performances of the algorithms, we also find significant differences among the summaries produced by different algorithms over the same input data.

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Notes

  1. 1.

    Availability of implementations: Frequency Summarizer (http://glowingpython.blogspot.in/2014/09/text-summarization-with-nltk.html), Mead (http://www.summarization.com/mead/), SumBasic (https://github.com/EthanMacdonald/SumBasic), LexRank, LSA and LUHN are available as part of the Python Sumy package (https://pypi.python.org/pypi/sumy). COWTS (proposed in our prior work [5]) and ClusterRank were implemented by us.

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Author information

Authors and Affiliations

  1. Indian Institute of Engineering Science and Technology Shibpur, Shibpur, India

    Soumi Dutta, Vibhash Chandra, Kanav Mehra, Asit Kumar Das & Saptarshi Ghosh

  2. Institute of Engineering and Management, Kolkata, 700091, India

    Soumi Dutta & Sujata Ghatak

  3. Indian Institute of Technology Kharagpur, Kharagpur, 721302, India

    Saptarshi Ghosh

Authors
  1. Soumi Dutta
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  2. Vibhash Chandra
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  3. Kanav Mehra
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  4. Sujata Ghatak
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  5. Asit Kumar Das
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  6. Saptarshi Ghosh
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Corresponding author

Correspondence to Soumi Dutta .

Editor information

Editors and Affiliations

  1. Machine Intelligence Research Labs, Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer and System Sciences, Visva-Bharati University, Santiniketan, West Bengal, India

    Paramartha Dutta

  3. Department of Computer Science and Engineering, University of Kalyani, Kalyani, India

    Jyotsna Kumar Mandal

  4. Institute of Engineering and Management, Kolkata, West Bengal, India

    Abhishek Bhattacharya

  5. Institute of Engineering and Management, Kolkata, West Bengal, India

    Soumi Dutta

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Dutta, S., Chandra, V., Mehra, K., Ghatak, S., Das, A.K., Ghosh, S. (2019). Summarizing Microblogs During Emergency Events: A Comparison of Extractive Summarization Algorithms. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 813. Springer, Singapore. https://doi.org/10.1007/978-981-13-1498-8_76

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