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Identifying Shooting Tweets with Deep Learning and Keywords Filtering: Comparative Study.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Identifying Shooting Tweets with Deep Learning and Keywords Filtering: Comparative Study./
作者:	Mohamed, Ammar Ahmed Abdelhalim.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	50 p.
附註:	Source: Masters Abstracts International, Volume: 83-04.
Contained By:	Masters Abstracts International83-04.
標題:	Information technology. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28730863
ISBN:	9798535577340

Identifying Shooting Tweets with Deep Learning and Keywords Filtering: Comparative Study.
Mohamed, Ammar Ahmed Abdelhalim.

Identifying Shooting Tweets with Deep Learning and Keywords Filtering: Comparative Study. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 50 p.

Source: Masters Abstracts International, Volume: 83-04.

Thesis (M.S.)--University of Cincinnati, 2021.

This item must not be sold to any third party vendors.

During large-scale crises, 911 call centers often become inundated by high call volume, making it difficult for citizens to request help. When this is the case, people may turn to social media for support. This also happens when someone may wish to discuss an incident, such as hearing gunshots, but feel unsure if calling 911 is the most appropriate action. 911 does not typically monitor social media platforms for these types of requests due to challenges in sorting and filtering relevant information. To support the fast identification of important information to be shared with first responders, this research focuses on analyzing social media posts to determine the relevancy of social media posts about shooting incidents and emergencies. It compares the accuracy and relevancy of two methods of filtering social media data. The first is filtering tweets using keywords related to shooting and manually labeling them based on their relevancy to shooting events. The second method is by training a Transfer Learning model to determine the relevancy of collected tweets. The comparison results show that the machine learning technique is more accurate in identifying relevant tweets than the keyword filtering technique.

ISBN: 9798535577340Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Social media

Identifying Shooting Tweets with Deep Learning and Keywords Filtering: Comparative Study.
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