vaderSentiment
PRAW
vaderSentiment | PRAW | |
---|---|---|
20 | 528 | |
4,179 | 3,321 | |
- | 0.8% | |
0.0 | 7.7 | |
over 1 year ago | 7 days ago | |
Python | Python | |
MIT License | BSD 2-clause "Simplified" License |
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vaderSentiment
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Walmart, Delta, and Starbucks are using AI to monitor employee messages
There's overlap, but many traditional NLP techniques are heuristics based. Here's an example: https://github.com/cjhutto/vaderSentiment
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Turbocharge your application development using WebAssembly with SingleStoreDB
Our code uses VADER (Valence Aware Dictionary and sEntiment Reasoner). VADER is a lexicon and rule-based sentiment analysis tool that can interpret and classify emotions.
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Finding the saltiest NFL fanbase by analyzing 5 years of Reddit posts
My analyses focused on whether word usage within these threads, from 2017-2021, was positive or negative. The average level of positivity vs. negativity — often referred to as the “valence” — was scored using VADER, a language processing tool designed for online settings. Valence was averaged separately for wins and losses, then averaged again to generate a team’s overall valence score; this procedure controls for a team’s loss rate, and thus low scores do not simply reflect that a team frequently loses.
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I want to do a sentiment analysis that classifies tweets into 'positive' and 'negative' , any good resources for doing this?
I did this all as a node project but it looks like there's a python package available here - https://github.com/cjhutto/vaderSentiment
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[OC] Twitter Sentiment On Will Smith Before and After Slap
Sources: Info on VADER, VADER Dictionary (word, score, other data), VADER's special rules, original paper by the authors.
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I made a site that tracks stock mentions and sentiment from over 180 subreddits.
C++, PHP, Javascript and vader
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I made a site that tracks stock and crypto mentions and sentiment from over 180 subreddits.
vader - a sentiment analysis tool developed by researchers at Georgia Tech
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Growing up Muslim I used to get my ass kicked for being “girly”. Dad, if only you could see me now.
It's a fairly standard piece of machine learning called sentiment analysis. Human volunteers rate a corpus of texts as either positive or negative sentiment. A machine learning algorithm is then trained to predict those sentiment scores from the text itself. Sentiment analysis is widely used in comment and review moderation. If you use Python you can play around with open-source examples such as VADER yourself. While they can't always pick up on sarcasm or irony in general they do pretty well on picking up general trends.
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Thoughts/Critiques of an NLP Sentiment Analysis Project
You could try applying VADER (designed to handle social media data esp. Twitter) to tweets containing the word "apple" vs. "banana", and compare the sentiment scores.
- Amazing positivity in this community keep it up!:)
PRAW
- PRAW documentation
- Testing
- `resubmit=False` started resubmitting duplicate URLs Jul 24 2023
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Just curious which person is the most popular user flair.
I'm... not sure I understand the question? PRAW still works just fine for "personal use" of the reddit API.
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How to use use Praw library with access and refresh tokens?
Thank you for pointing out. So there is no need then for the access token? Only with the refresh token is enough? To be honest I took a look at it but I did not expect that to be under authentication as strictly speaking, the user already made the authentication. Also I took a look at the code at https://github.com/praw-dev/praw/blob/master/praw/reddit.py and I did not get a hint whether was possible to pass it or not. I am just saying this to let you know I tried to search for the answer before asking. Again thank you for the help.
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PRAW VS redditwarp - a user suggested alternative
2 projects | 21 Jun 2023
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Migrating subreddits to Lemmy communities
To get the relevant IDs, you can use something like PRAW to query the subreddit for the top 1000 posts for example.
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Reddit Comment Nuke: A Python script to edit and save your Reddit comment history en masse
Huge thanks to the contributors to PRAW, which is the Python package that does all the heavy lifting relating to Reddit's API that I need for this script.
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Why does PRAW's stream_generator() use a BoundedSet limit of 301?
However, in practice duplicate items were yielded with these smaller numbers. So I increased the limit briefly to 250 in October 2016, and then increased it finally to 301 in December 2016 in order to resolve https://github.com/praw-dev/praw/issues/673. That issue provides an explanation for how 301 came to be.
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is there a list of http status code which reddit api returns?
Why? You gotta be ready for any status code. Even 777.
What are some alternatives?
tweets-docker-pipeline - Docker pipeline for streaming tweets and their sentiment score to a Slack channel
asyncpraw - Async PRAW, an abbreviation for "Asynchronous Python Reddit API Wrapper", is a python package that allows for simple access to Reddit's API.
twurl - OAuth-enabled curl for the Twitter API
Pushshift API - Pushshift API
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
pmaw - A multithread Pushshift.io API Wrapper for reddit.com comment and submission searches.
Docker Compose - Define and run multi-container applications with Docker
boto3 - AWS SDK for Python
PostgreSQL - Mirror of the official PostgreSQL GIT repository. Note that this is just a *mirror* - we don't work with pull requests on github. To contribute, please see https://wiki.postgresql.org/wiki/Submitting_a_Patch
Telethon - Pure Python 3 MTProto API Telegram client library, for bots too!
pushwasm - Utility to push a Wasm UDF into SingleStoreDB
django-wordpress - WordPress models and views for Django.