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

Publication2024

Comparative Analysis of Sentiment Classification using Feature Engineering for Social Media

The record

Type
Publication
Date
1 January 2024
Level
National
Journal
Proceedings 2024 5th International Conference on Image Processing and Capsule Networks Icipcn 2024
Pages
434-440
Published
1 January 2024
DOI
10.1109/icipcn63822.2024.00077
Scopus ID
85204783749
Authors
6
Open access
No
Citations
1
International co-authorship
No
Co-author countries
IN

Classification

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UN Sustainable Development Goals

  1. 9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending

    TargetPrimaryModerate confidenceJudged

    Machine learning comparative analysis of sentiment classification models for social media data mining supporting customer attitude assessment and marketing strategy.

    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

Viksit Bharat @2047

  1. vb-3 Innovation, Science and Technology

    ThemePrimaryModerate confidenceJudged

    Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 9 label. Machine learning comparative analysis of sentiment classification models for social media data mining supporting customer attitude assessment and marketing strategy.

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

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KIIT Deemed to be University. “Comparative Analysis of Sentiment Classification using Feature Engineering for Social Media”. Kortex.

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