Deep semantic matching approach towards dynamic text filtering in micro-blog messages
- UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
- Brown Biggers, IT Operations Manager (Creator)
- Institution
- The University of North Carolina at Greensboro (UNCG )
- Web Site: http://library.uncg.edu/
- Advisor
- Somya Mohanty
Abstract: There is a growing interest in using social media content for Natural Lan¬guage Processing applications. This paper seeks to demonstrate a way to present the changing semantics of Twitter within the context of a crisis event, specifically tweets during Hurricane Irma. Using an implementation of the Word2Vec method of Neural Network training mechanisms developed by Mikolov, et al to create Word Embeddings, this paper will: discuss how the relative meaning of words changes as events unfold; present a mechanism for scoring tweets based upon dynamic, relative context relatedness; and show that similarity between words is not necessarily static.
Deep semantic matching approach towards dynamic text filtering in micro-blog messages
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Created on 12/1/2020
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Additional Information
- Publication
- Thesis
- Language: English
- Date: 2020
- Keywords
- Crisis informatics, Natural language processing, Social media, Text mining, Word embedding
- Subjects
- Natural language processing (Computer science)
- Text data mining
- Social media
- Neural networks (Computer science)