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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 project aims to give a solution for the FiQA 2018 challenge subtask 1.

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aspect-based-sentiment-analysis deep-learning machine-learning sentiment-analysis

aspect-based-financial-sentiment-analysis's Introduction

Ashish Vishvasrao Salunkhe

Hi there! 👋

I'm Ashish Vishvasrao Salunkhe, a data science aficionado with a keen eye for building impactful data products using cutting-edge tools.

About Me

I'm currently pursuing a Master of Information Management at the University of Maryland, College Park, while gaining practical experience in various roles. My academic journey equips me with a strong foundation in statistics, user research, big data infrastructure, and machine learning.

I'm actively seeking opportunities to contribute to open-source projects and collaborate on data-driven solutions that make a real difference.

My Skills

  • Data Enthusiast: I'm passionate about exploring the potential of data science across various domains.
  • Software Engineer: With a computer engineering background, I enjoy building robust and maintainable software solutions.
  • Data Engineer: I'm proficient in designing and building scalable data pipelines and data architectures.
  • Product Management: I've defined product vision, conducting market research, prioritizing features based on data and user needs.
  • User Experience: User research, wireframing, prototyping, design thinking, implemented a user-centric approach to product development.
  • Agile Project Management: Worked effectively in cross-functional teams, prioritizing tasks, and managing development lifecycles.

Get in Touch

Feel free to reach out to me via Email or connect with me on LinkedIn. Let's chat about data science, software engineering, or any tech-related challenge!

GitHub Stats



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aspect-based-financial-sentiment-analysis's Issues

How to process data when a sentence has multiple targets

Hi! Because there are only json files in the repository, there is no csv file in the code. How to process data when a sentence has multiple targets? Can you provide the preprocess code?

For example
"1443": {
"sentence": "Saudi Aramco, Shell plan to break up Motiva, divide up assets",
"info": [
{
"snippets": "['Shell plan to break up Motiva, divide up assets']",
"target": "Saudi Aramco",
"sentiment_score": "-0.142",
"aspects": "['Corporate/Strategy/Reorganization']"
},
{
"snippets": "['plan to break up Motiva, divide up assets']",
"target": "Shell",
"sentiment_score": "-0.102",
"aspects": "['Corporate/Strategy/Reorganization']"
}
]
},

Where do I find the checkpoint/config?

How do I get these files

##use downloaded model, change path accordingly
BERT_VOCAB= '/home/ashish/FiQA/uncased_L-12_H-768_A-12/vocab.txt'
BERT_INIT_CHKPNT = '/home/ashish/FiQA/uncased_L-12_H-768_A-12/bert_model.ckpt'
BERT_CONFIG = '/home/ashish/FiQA/uncased_L-12_H-768_A-12/bert_config.json'

Are you able to share the complete codes?

Hi, Ashish Salunkhe
I am a student who is interested in NLP and currently I am studying Aspect based sentiment analysis myself.
I have read your paper "Aspect Based Sentiment Analysis on Financial Data using Transferred Learning Approach using Pre-Trained BERT and Regressor Model", and think it is really applicable and great job, especially in financial domain..
I tried to replicate your work but face some problems, so could you share the codes for this project if possible?
I would be really grateful. Thank you.

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