Date of Award

6-16-2016

Document Type

Thesis

Degree Name

Master of Science in Computer Engineering

Department

Department of Electrical and Computer Engineering

First Advisor

Kenneth M. Hopkinson, PhD.

Abstract

This thesis focuses on collection and preprocessing of streaming social media feeds for metadata as well as the visual and textual information. Today, news media has been the main source of immediate news events, large and small. However, the information conveyed on these news sources is delayed due to the lack of proximity and general knowledge of the event. Such news have started relying on social media sources for initial knowledge of these events. Previous works focused on captured textual data from social media as a data source to detect events. This preprocessing framework postures to facilitate the data fusion of images and text for event detection. Results from the preprocessing techniques explained in this work show the textual and visual data collected are able to be proceeded into a workable format for further processing. Moreover, the textual and visual data collected are transformed into bag-of-words vectors for future data fusion and event detection.

AFIT Designator

AFIT-ENG-MS-16-J-001

DTIC Accession Number

AD1054215

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