A set of tools for producing and exploring keywords on Twitter and the Wikipedia
Project description
There are six applications in this project: KeywordExplorer, TweetsCountExplorer, TweetDownloader, WikiPageviewExplorer, TweetEmbedExplorer, and ModelExplorer. They, and the classes that support them, can be installed with pip:
pip install keyword-explorer
KeywordExplorer is a Python desktop app that lets you use the GPT-3 to search for keywords and Twitter to see if those keywords are any good.
TweetCountsExplorer is a Python desktop app that lets you explore the quantity of tweets containing keywords over days, weeks or months.
TweetDownloader is a Python desktop app that lets you select and download tweets containing keywords into a database. The number of Tweets can be adjusted so that they are the same for each day or proportional. Users can apply daily and overall limits for each keyword corpora.
WikiPageviewExplorer is a Python desktop app that lets you explore keywords that appear as articles in the Wikipedia, and chart their relative page views.
TweetEmbedExplorer is a Python desktop app for analyzing, filtering, and augmenting tweet information. Augmented information can them be used to create a train/test corpus for finetuning language models such as the GPT-2.
ModelExplorer is a Python desktop app that lets a user interact with a finetuned GPT-2 model trained using EmbeddingExplorer
Full documentation is available at https://github.com/pgfeldman/KeywordExplorer#readme
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