Aspect-Based Financial Sentiment Analysis using Deep Learning-Reference-Cited by-同舟云学术

Aspect-Based Financial Sentiment Analysis using Deep Learning

Published:2018 Issue: Volume: Page:
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Container-title:Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW '18
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Author:

Jangid Hitkul¹,Singhal Shivangi¹,Shah Rajiv Ratn¹,Zimmermann Roger²

Affiliation:

1. IIIT-Delhi, Delhi, India

2. National University of Singapore, Singapore, Singapore

Publisher

ACM Press

Reference15 articles.

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2. Jasper Friedrichs Debanjan Mahata, Shubham Gupta. 2017. InfyNLP at SMM4H Task 2: Stacked Ensemble of Shallow Convolutional Neural Networks for Identifying Personal Medication Intake from Twitter. In Proceedings of the Second Workshop on Social Media Mining for Health Applications (SMM4H). Health Language Processing Laboratory; 2017, Vol. 1996. 68--71.

3. CJ Hutto Eric Gilbert. 2014. Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Eighth International Conference on Weblogs and Social Media (ICWSM-14). Available at (20/04/16) http://comp. social. gatech. edu/papers/icwsm14. vader. hutto. pdf.

4. Fréderic Godin, Baptist Vandersmissen, Wesley De Neve, and Rik Van de Walle. 2015. Multimedia Lab @ ACL WNUT NER Shared Task: Named Entity Recognition for Twitter Microposts using Distributed Word Representations. In Proceedings of the Workshop on Noisy User-generated Text. 146--153.

5. Soufian Jebbara and Philipp Cimiano. 2016. Aspect-Based Sentiment Analysis Using a Two-Step Neural Network Architecture. In Semantic Web Challenges, Harald Sack, Stefan Dietze, Anna Tordai, and Christoph Lange (Eds.). Springer International Publishing, Cham, 153--167.

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