What is VADER?
VADER is a less resource-consuming sentiment analysis model that uses a set of rules to specify a mathematical model without explicitly coding it. VADER consumes fewer resources as compared to Machine Learning models as there is no need for vast amounts of training data. VADER’s resource-efficient approach helps us to decode and quantify the emotions contained in streaming media such as text, audio or video. VADER doesn’t suffer severely from a speed-performance tradeoff.
VADER stands for Valence Aware Dictionary for sEntiment Reasoning.
Python implementation of VADER – Environment Setup
Standard Python distribution doesn’t come bundled with the VADER module. We’ll be using the popular Python package installer, pip to do so.
A package contains all the files you need for a module. Modules are Python code libraries you can include in your project. We use the following code in Anaconda terminal to install VADER.
!pip install vaderSentiment
from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
analyzer = SentimentIntensityAnalyzer()
VADER has been included in the NLTK package itself. Module NLTK is used for natural language processing. NLTK is an acronym for Natural Language Toolkit and is one of the leading platforms for working with human language data. Alternatively one may use.
!pip install nltk
from nltk.sentiment.vader import SentimentIntensityAnalyzer
analyzer = SentimentIntensityAnalyzer()
Using Pandas Datareader to scrape stock data
import pandas as pd
import numpy as np
import pandas_datareader as pdr
import matplotlib.pyplot as plt
data_amd = pdr.get_data_yahoo(‘AMD’, ’24-Feb-20′)
Visit QuantInsti Blog to read the rest of the article and download the Python code:
Disclosure: Interactive Brokers
Information posted on IBKR Traders’ Insight that is provided by third-parties and not by Interactive Brokers does NOT constitute a recommendation by Interactive Brokers that you should contract for the services of that third party. Third-party participants who contribute to IBKR Traders’ Insight are independent of Interactive Brokers and Interactive Brokers does not make any representations or warranties concerning the services offered, their past or future performance, or the accuracy of the information provided by the third party. Past performance is no guarantee of future results.
This material is from QuantInsti and is being posted with permission from QuantInsti. The views expressed in this material are solely those of the author and/or QuantInsti and IBKR is not endorsing or recommending any investment or trading discussed in the material. This material is not and should not be construed as an offer to sell or the solicitation of an offer to buy any security. To the extent that this material discusses general market activity, industry or sector trends or other broad based economic or political conditions, it should not be construed as research or investment advice. To the extent that it includes references to specific securities, commodities, currencies, or other instruments, those references do not constitute a recommendation to buy, sell or hold such security. This material does not and is not intended to take into account the particular financial conditions, investment objectives or requirements of individual customers. Before acting on this material, you should consider whether it is suitable for your particular circumstances and, as necessary, seek professional advice.
In accordance with EU regulation: The statements in this document shall not be considered as an objective or independent explanation of the matters. Please note that this document (a) has not been prepared in accordance with legal requirements designed to promote the independence of investment research, and (b) is not subject to any prohibition on dealing ahead of the dissemination or publication of investment research.
Any trading symbols displayed are for illustrative purposes only and are not intended to portray recommendations.