---
title: Graph Embedding for Sentiment Analysis
url: https://www.ml-quant.com/papers/ssrn/4576625/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4576625
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4576625
featured: 2023-09-21
citations: unknown
topic: LLMs & Text
---


# Graph Embedding for Sentiment Analysis

The research suggests a self-supervised method for Persian sentiment analysis using combined representation learning and Siamese Network, using a self-supervised approach to enhance feature vectors from graph-structured data.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4576625
- Identifier: SSRN 4576625
- Released: 2023-09-19
- First featured: Quant Letter No. 16 (2023-09-21): https://www.ml-quant.com/issues/2023-09-21/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: LLMs & Text

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