| """ | |
| a simple script that reads tweets inside a json file, uses openai to compute embeddings and creates two files, metadata.tsv and output.tsv, which cam be used to visualise the tweets and their embeddings in TensorFlow Projector (https://projector.tensorflow.org/) | |
| """ | |
| # obtain tweets.json from https://gist.github.com/gd3kr/948296cf675469f5028911f8eb276dbc | |
| import pandas as pd | |
| import json | |
| from openai import OpenAI |
| /* Enhancements to the Twitter Scraping Script: | |
| This update to the script introduces a more robust mechanism for extracting detailed interaction data from tweets as they are scraped from Twitter. Previously, the script focused on collecting basic content such as the tweet's text. Now, it has been augmented to include a comprehensive extraction of interaction metrics, including replies, reposts, likes, bookmarks, and views, for each tweet. | |
| Key Changes: | |
| 1. Improved Data Extraction: | |
| - The script now searches through all elements within a tweet that have an `aria-label` attribute, filtering for labels that contain key interaction terms (replies, reposts, likes, bookmarks, views). This ensures that only relevant `aria-labels` are considered for data extraction. | |
| 2. Flexible Interaction Data Parsing: |
| //there are issues with how we manage to skip pixels. | |
| //accounts are getting skipped. | |
| let following = []; // Initialize an empty array to hold all elements of people you follow | |
| let formattedFollowers = [] | |
| const scrollInterval = 2000; | |
| const scrollStep = 2000; // Pixels to scroll on each step | |
| let previousFollowingCount = 0; |
| /* | |
| the twitter api is stupid. it is stupid and bad and expensive. hence, this. | |
| Literally just paste this in the JS console on the bookmarks tab and the script will automatically scroll to the bottom of your bookmarks and keep a track of them as it goes. | |
| When finished, it downloads a JSON file containing the raw text content of every bookmark. | |
| for now it stores just the text inside the tweet itself, but if you're reading this why don't you go ahead and try to also store other information (author, tweetLink, pictures, everything). come on. do it. please? | |
| */ |
The list below includes 27950 deleted tweets by meatballsubzero.
Note: GitHub's rendered view of the Gist truncates the list. You can see the full content by clicking the "Raw" link, or by cloning the Gist locally.
This report was generated by ✨cancel-culture✨, an open source project by Travis Brown.
The list below includes 3157 deleted tweets by ComGopnitsa.
This report was generated by ✨cancel-culture✨, an open source project by Travis Brown.
| // | |
| // ContentView.swift | |
| // coremlsd2test | |
| // | |
| // Created by Yasuhito Nagatomo on 2022/12/03. | |
| // | |
| // A sample code using Apple/ml-stable-diffusion library. | |
| // Preparation: | |
| // 1. convert the PyTorch Stable-Diffusion v2 model to coreml models using Apple's tools. | |
| // 2. import the coreml models into the iOS project. |
The tables below show notable Twitter suspension reversals for each day since Elon Musk took over as owner and CEO.
All dates indicate when the suspension or reversal was detected, and the actual suspension or reversal may have been earlier. For most English-language accounts with large followings, this lag will generally not be longer than a few hours, but for accounts that have a small number of followers or that are outside the networks we are tracking, the difference can be larger, and in some cases an account on the list may have had its suspension reversed before 27 October 2022. These dates will get more precise as we refine the report.
Because of these limitations, this report should be considered a starting point for investigation, not a definitive list of suspension reversals.
FINALLY no need for tricks!
bonus tip: for more darkness > https://darkreader.org/