Mining causal knowledge from autism newspapers

Zhai, Yujia; Sun, ShaoJin; Ding,Ying

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https://hdl.handle.net/2142/96747 Copy

Description

Title

Mining causal knowledge from autism newspapers

Author(s)

• Zhai, Yujia
• Sun, ShaoJin
• Ding,Ying

Issue Date

2017

Keyword(s)

• Causal knowledge
• Autism
• Autism newspapers
• Open information extraction

Abstract

Autism is a lifelong developmental disability that affects how people perceive the world and interact with others. It has received enormous attention from both the academia and media. The causes of autism carried by the news media have an even bigger impact on the people’s opinion about autistic people and various treatments. In this research, we use machine reading technique to automatically extract causal relationships from autism news. We reveal the major diseases, causes and symptoms related with autism. We find that vaccine, gene and parenting are the main causes reported in the history of autism news. We also demonstrate the coverage of the causal relationships across time which shows gene has become the most important cause of autism surpass vaccine.

Publisher

iSchools

Series/Report Name or Number

iConference 2017 Proceedings

Type of Resource

text

Language

en

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http://hdl.handle.net/2142/96747

Copyright and License Information

Copyright 2017 Yujia Zhai, ShaoJin Sun, and Ying Ding

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