Opinion Mining and Sentiment Analysis in Social Media: Challenges and Applications-Reference-Cited by-同舟云学术

Opinion Mining and Sentiment Analysis in Social Media: Challenges and Applications

Published:2018 Issue: Volume: Page:536-548
ISSN:0302-9743
Container-title:HCI in Business, Government, and Organizations
language:
Short-container-title:

Author:

Zhang Wenping,Xu Mengna,Jiang Qiqi

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-91716-0_43

Reference48 articles.

1. ABC News (2016). http://abcnews.go.com/Politics/clinton-trump-leaves-10-unhappy-contest-tightens-conventions/story?id=40615476

2. Agrawal, A., Hamling, T.: Sentiment analysis of tweets to gain insights into the 2016 US election. Columbia Undergrad. Sci. J. 11 (2017)

3. Ashok, M., Rajanna, S., Joshi, P.V., Kamath, S.: A personalized recommender system using machine learning based sentiment analysis over social data. In: 2016 IEEE Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), pp. 1–6. IEEE, March 2016

4. Azar, P.D., Lo, A.W.: Practical applications of the wisdom of Twitter crowds: predicting stock market reactions to FOMC meetings via Twitter feeds. Pract. Appl. 4(2), 1–4 (2016)

5. Bessi, A., Ferrara, E.: Social bots distort the 2016 US presidential election online discussion (2016)

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