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Paper Abstract and Keywords
Presentation 2021-12-17 12:10
Proposal of classification method based on the usefulness of Twitter account in student job hunting
Yuasa Takeo, Kunieda Yositosi (Ritsumeikan Univ)
Abstract (in Japanese) (See Japanese page) 
(in English) With the spread of coronavirus infection, it has become difficult to collect information face-to-face with students who are looking for a job. As a result, students are forced to engage in non-face-to-face activities, and the use of SNS such as Twitter, Facebook, and Instagram is rapidly increasing as a means of collecting information. At the same time, the need for IT literacy for collecting information on SNS is also increasing. Therefore, in this paper, we propose a method to classify useful information and non-useful information for students in job hunting on Twitter, which is suitable for non-face-to-face and sharing of important information. The proposed method uses correlation and regression analysis to determine the causal relationship between the usefulness of the account and the traces that occur in the operation of Twitter.
Keyword (in Japanese) (See Japanese page) 
(in English) Twitter / correlation analysis / regression analysis / causal inference / classification / usefulness / /  
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Conference Information
Committee HCGSYMPO  
Conference Date 2021-12-15 - 2021-12-17 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
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Paper Information
Registration To HCGSYMPO 
Conference Code 2021-12-HCGSYMPO 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Proposal of classification method based on the usefulness of Twitter account in student job hunting 
Sub Title (in English)  
Keyword(1) Twitter  
Keyword(2) correlation analysis  
Keyword(3) regression analysis  
Keyword(4) causal inference  
Keyword(5) classification  
Keyword(6) usefulness  
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1st Author's Name Yuasa Takeo  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ)
2nd Author's Name Kunieda Yositosi  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ)
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Speaker Author-1 
Date Time 2021-12-17 12:10:00 
Presentation Time 15 minutes 
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