AI for social good
The objective of this project is to create a data pipeline system for identifying racist text, with the intention of promoting social good. The proposed system follows a pipelined approach, capable of collecting real-time tweets from Twitter and utilizing natural language processing (NLP) tech...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/166012 |
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sg-ntu-dr.10356-1660122023-04-21T15:38:29Z AI for social good Ruan, Yang Erik Cambria School of Computer Science and Engineering cambria@ntu.edu.sg Engineering::Computer science and engineering The objective of this project is to create a data pipeline system for identifying racist text, with the intention of promoting social good. The proposed system follows a pipelined approach, capable of collecting real-time tweets from Twitter and utilizing natural language processing (NLP) techniques to assign multiple labels such as subjectivity, polarity and intensity score and then identifying if the tweet is racist. Racism score can be obtained by a custom-built model based on transformers techniques with extra few features from knowledge base (SenticNet). The resulting data will be stored in a database for further analysis Bachelor of Engineering (Computer Science) 2023-04-18T07:59:57Z 2023-04-18T07:59:57Z 2023 Final Year Project (FYP) Ruan, Y. (2023). AI for social good. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166012 https://hdl.handle.net/10356/166012 en PSCSE21-0005 application/pdf Nanyang Technological University |
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Nanyang Technological University |
| building |
NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
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DR-NTU |
| language |
English |
| topic |
Engineering::Computer science and engineering |
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Engineering::Computer science and engineering Ruan, Yang AI for social good |
| description |
The objective of this project is to create a data pipeline system for identifying racist text, with
the intention of promoting social good. The proposed system follows a pipelined approach,
capable of collecting real-time tweets from Twitter and utilizing natural language processing
(NLP) techniques to assign multiple labels such as subjectivity, polarity and intensity score
and then identifying if the tweet is racist. Racism score can be obtained by a custom-built
model based on transformers techniques with extra few features from knowledge base
(SenticNet). The resulting data will be stored in a database for further analysis |
| author2 |
Erik Cambria |
| author_facet |
Erik Cambria Ruan, Yang |
| format |
Final Year Project |
| author |
Ruan, Yang |
| author_sort |
Ruan, Yang |
| title |
AI for social good |
| title_short |
AI for social good |
| title_full |
AI for social good |
| title_fullStr |
AI for social good |
| title_full_unstemmed |
AI for social good |
| title_sort |
ai for social good |
| publisher |
Nanyang Technological University |
| publishDate |
2023 |
| url |
https://hdl.handle.net/10356/166012 |
| _version_ |
1764208019053215744 |