Classifying facts and opinions in Twitter messages: a deep learning-based approach-Reference-Cited by-同舟云学术

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Classifying facts and opinions in Twitter messages: a deep learning-based approach

Published:2018-01-02 Issue:1 Volume:1 Page:29-39
ISSN:2573-234X
Container-title:Journal of Business Analytics
language:en
Short-container-title:Journal of Business Analytics

Author:

Chatterjee Swayambhu¹,Deng Shuyuan²,Liu Jun¹,Shan Ronghua¹,Jiao Wu³

Affiliation:

1. College of Business and Information Systems, Dakota State University, Madison, SD, USA

2. Seidman College of Business, Grand Valley State University, Grand Rapids, MI, USA

3. College of Business Administration, Northern Illinois University, DeKalb, IL, USA

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Information Systems,Management Information Systems

Link

https://www.tandfonline.com/doi/pdf/10.1080/2573234X.2018.1506687

Reference37 articles.

1. Detecting Fake Websites: The Contribution of Statistical Learning Theory

2. Putting Money Where the Mouths Are: The Relation Between Venture Financing and Electronic Word-of-Mouth

3. Twitter mood predicts the stock market

4. New Avenues in Opinion Mining and Sentiment Analysis

5. A Hybrid Attribute Selection Approach for Text Classification

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2. Introducing technological disruption: how breaking media attention on corporate events impacts online sentiment;Journal of Business Analytics;2023-10-31

3. Use of Compression Analytics to Detect Deception;2023 10th International Conference on Behavioural and Social Computing (BESC);2023-10-30

4. Online complaint handling: a text analytics-based classification framework;Marketing Intelligence & Planning;2023-04-28

5. Classification of Tweets Into Facts and Opinions Using Recurrent Neural Networks;International Journal of Technology and Human Interaction;2023-03-10

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