Targeted Twitter Sentiment Analysis for Brands Using Supervised Feature Engineering and the Dynamic Architecture for Artificial Neural Networks-Reference-Cited by-同舟云学术

Targeted Twitter Sentiment Analysis for Brands Using Supervised Feature Engineering and the Dynamic Architecture for Artificial Neural Networks

Published:2016-10 Issue:4 Volume:33 Page:1034-1058
ISSN:0742-1222
Container-title:Journal of Management Information Systems
language:en
Short-container-title:Journal of Management Information Systems

Author:

Ghiassi Manoochehr,Zimbra David,Lee Sean

Publisher

Informa UK Limited

Subject

Information Systems and Management,Management Science and Operations Research,Computer Science Applications,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/07421222.2016.1267526

Reference36 articles.

1. Sentiment analysis in multiple languages

2. Bakliwal, A.; Foster, J.; van der Puil, J.; O’Brien, R.; Tounsi, L.; and Hughes, M. Sentiment analysis of political tweets: Towards an accurate classifier. InProceedings of the ACL Workshop on Language in Social Media, Atlanta, GA: LASM, 2013, pp. 49–58.

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