Sentiment analysis of disaster tweets : comparative analysis of preprocessed data / Elleah Kim J. Jarin, Rhio Mae Manaog and John Rey M. Naguit
Material type:
TextPublication details: Manila : National University, 2018Description: xiv, 40 leaves : illustrations ; 28 cmLOC classification: - UGT CCIT BSCS .J37 2018
Thesis
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National University - Manila | LRC - Main Thesis | Computer Science | UGT CCIT BSCS .J37 2018 c.1 (Browse shelf(Opens below)) | c.1 | Available | UGTHE000001449 |
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| UGT CCIT BSCS .H59 2015 Implementing a language identification system for Philippine languages / | UGT CCIT BSCS .I33 2008 c.1 Floring's supermarket point of sale and inventory system / | UGT CCIT BSCS .I33 2008 c.2 Floring's supermarket point of sale and inventory system / | UGT CCIT BSCS .J37 2018 c.1 Sentiment analysis of disaster tweets : comparative analysis of preprocessed data / | UGT CCIT BSCS .J37 2018 c.2 Sentiment analysis of disaster tweets : comparative analysis of preprocessed data / | UGT CCIT BSCS .J37 2018 c.3 Sentiment analysis of disaster tweets : comparative analysis of preprocessed data / | UGT CCIT BSCS .L36 2002 my NUphones / |
Includes bibliographical references.
Title page -- National/International Conference Acceptance Letter -- Approval sheet -- Panel recommendation sheet -- Certificate of grammar checked -- Acknowledgement -- Abstract -- Table of contents -- List of tables -- List of figures -- List of equations -- Chapter I. Introduction -- Chapter II. Review of related literature and studies -- Chapter III. Design and methodology -- Chapter IV. Results, and discussion -- Chapter V. Conclusion and recommendations -- References -- Appendices.
This paper introduces models for disaster-related tweets. The emphasis is on Twitter information created during and after the devastation of Typhoon Yolanda, which affected the Philippines in November 2013.
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