---
# System prepended metadata

title: 社交情緒AI訓練筆記

---

[HackMD 使用教學](/fNYeUVJNQr6G6ZA5nwn9oA)
[HackMD 快速入門教學](/GinelCA0ThGlIDP1TJ19HA)

**目錄清單**
[TOC]

資料獲取
===
**Twint:**
>Twitter信息爬取工具，可以在不使用TwitterAPI情況下，爬取特定用戶上的推文。
GitHub:[https://github.com/twintproject/twint](https://github.com/twintproject/twint)

**安裝指令**:
```
pip3 install twint
```
**<font color="red">若出現問題可以嘗試安裝 Visual C++ 環境 </font>**

**建議安裝**:
>Visual C++環境 || [Vsiual Studio Build Tools](https://visualstudio.microsoft.com/zh-hant/downloads/)

參考、引用論文
===
| 論文名稱 | 引用技術 | date |
|:-------- |:-------- |:-----|
| [Twitter mood predicts the stock market](https://arxiv.org/abs/1010.3003)     | namely OpinionFinder that measures positive vs. negative mood and Google-Profile of Mood States (GPOMS)     | Thu, 14 Oct 2010 18:55:52 UTC  |
|[Tweet Influence on Market Trends: Analyzing the Impact of Social Media Sentiment on Biotech Stocks](https://arxiv.org/abs/2402.03353)| VADER sentiment analysis &  ARIMA (AutoRegressive Integrated Moving Average) and VAR (Vector AutoRegression) models to forecast stock market performance|Fri, 26 Jan 2024 15:43:27 UTC|

情緒分析
===
**VADER**:
>(Valence Aware Dictionary and sEntiment Reasoner)：一種基於規則的情感分析工具，專門用於分析社交媒體文本中的情感。
GitHub:[https://github.com/cjhutto/vaderSentiment](https://github.com/cjhutto/vaderSentiment)














