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by IQAC KIITKIIT Deemed to be University — Internal Quality Assurance Cell

Publication2025

Classifying Crisis Types and Urgency Levels in Tweets using TF-IDF and LSTM

The record

Type
Publication
Date
1 January 2025
Level
International — held abroad
Journal
Proceedings of 3rd International Conference on Intelligent Cyber Physical Systems and Internet of Things Icoici 2025
Pages
1641-1646
Published
1 January 2025
DOI
10.1109/icoici65217.2025.11252578
Scopus ID
105030320740
Authors
6
Open access
No
Citations
1
International co-authorship
Yes
Co-author countries
IN, SA

Classification

Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.

UN Sustainable Development Goals

  1. 11.5 Significantly reduce deaths and economic losses caused by disasters, including water-related disasters

    TargetPrimaryModerate confidenceJudged

    Hybrid deep learning model classifies disaster crisis types and urgency levels from tweets achieving 82.94% accuracy for emergency response

    Moderate confidence
    The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
    Judged
    Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

  2. 17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing

    TargetSecondaryHigh confidenceRule-derivedrule sdg17-structural-v1

    Structural signal: co-authorship outside India.

    High confidence
    The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
    Rule-derived
    Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
    Produced by
    sdg17-structural-v1, under kortex-publication-v1

Viksit Bharat @2047

  1. vb-4.2 Technology for public service delivery

    Sub-themePrimaryModerate confidenceJudged

    AI-powered crisis monitoring from social media enhances public service disaster response capability

    Produced by
    claude-haiku-4-5-20251001, under kortex-publication-v1

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KIIT Deemed to be University. “Classifying Crisis Types and Urgency Levels in Tweets using TF-IDF and LSTM”. Kortex.

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