Aspect-Based Financial Sentiment Analysis using Deep Learning

By Hitkul Jangid, Shivangi Singhal, Rajiv Ratn Shah, Roger Zimmermann. 2018

72 citations recorded by the source corpus.

Aspect based sentiment analysis aims to detect an aspect (i.e. features) in a given text and then perform sentiment analysis of the text with respect to that aspect. This paper aims to give a solution for the FiQA 2018 challenge subtask 1. We perform aspect-based sentiment analysis on the microblogs and headlines of financial domain. We use a multi-channel convolutional neural network for sentiment analysis and a recurrent neural network with bidirectional long short-term memory units to extract aspect from a given headline or microblog. Our proposed model produces a weighted average F1 score of 0.69 for the aspect extraction task and predicts sentiment intensity scores with a mean squared error of 0.112 on 10-fold cross validation. We believe that the developed system has direct applications in the financial domain.

Subfields: Artificial Intelligence, Management Science and Operations Research

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Omer Berat Sezer
2. M. Ugur Gudelek
3. Nhan Cach Dang
4. A. Ozbayoglu
5. Fernando De la Prieta Pintado
6. María N. Moreno García
7. Iqbal H. Sarker
8. Mohammad Mustafa Taye

In Management Science and Operations Research

1. M. Ugur Gudelek
2. Omer Berat Sezer
3. A. Ozbayoglu
4. Weiwei Jiang
5. Longbing Cao

Citations in the corpus

• Deep Learning for Financial Applications : A Survey (2020, methodology): “[187] Stock sentiment analysis from StockTwits 2015 StockTwits messages LSTM, Doc2Vec,”
• Sentiment Analysis Based on Deep Learning: A Comparative Study (2020, methodology): “[6] Financial sentiment analysis CNN, LSTM, RNN Financial tweets Aspect-based sentiment analysis”
• Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions (2021, background): “Similarly, domain knowledge in medical image analysis [58], financial sentiment analysis [49], cybersecurity analytics [94, 103] as well as conceptual data model in which semantic information, (i.e., meaningful for a system, rather than merely correlational) [45, 121, 131] is etc [13, 80].”